Scaling digital businesses: Excubate Business Model Audit

Scaling digital businesses:
Excubate Business Model Audit

Many companies have developed and invested into a portfolio of new businesses, many of which are still struggling to move from MVP to a scaling venture with tangible momentum.

The root cause lies in one or more aspects of the business model, e.g. value creation for company and customers, technical ability, data security, team skill & will, adherence to regulation, …

With a very structured, thorough and quick scalability audit, Excubate creates transparency on those aspectsthat are either already set up for scaling success (“green”), need further improvement (“yellow”) or are a major roadblock to growth (“red”).

Case Example: Smart sensor solution in petrochemical industries

Situation & Complication

Our client, a large technology corporation, developed a sensor-based digital solution, for the ongoing monitoring of hazardous leakages. The solution is aimed at large petrochemical plants, where a manual observation or monitoring of pipes is either difficult or not possible at all. Furthermore, the digital solution complemented the complex hardware portfolio of our client. The well working MVP was already being tested with pilot customers and a global, commercial rollout was imminent.

Particular challenging for the client’s product team, was the embedding of this new, digital solution into the complex and hardware-based core business of the corporation.

To ensure & prepare a smooth rollout, Excubate conducted a 4 week business model audit, to identify potential challenges early on and to support our client in leading this product to tangible revenues.

Overview: Business model audit in three phases

Timeline & Project Structure

The audit was conducted in three consecutive phases:

  1. Preparation
    Kickoff workshop at client site to understand status quo and discuss most imminent challenges; Data & material request; Customizing of Excubate best practice audit hypothesis tree to client situation
  2. Execution
    Read through and analyses of all provided materials, interviews with experts, customers and senior stakeholders (including workstream leads); Thorough documentation of insights and results per defined hypothesis
  3. Recommendation & Enablement
    Interpretation of results by identifying & force ranking challenges & gaps; Usage of a green-yellow-red color code to create transparency on most critical aspects; Recommendation of tangible action, based on expert insights, best practices & Excubate experience.

The Excubate team worked in a hybrid, hands-on mode. Interviews with relevant stakeholders were conducted on client-site, remotely or in the Excubate Munich office. The project was delivered by a classical consulting team, with a minor partner allocation (challenger & strategic lead), led by a Project Lead (overall project responsibility) and supported by a Consultant (Research & analytics).

Focus of Analysis & Results

Beyond relationship to the core business, Excubate thoroughly investigated customer requirements & value proposition, general business model design & pricing, operating model & procurement, technical feasibility, as well as legal topics. Our hypothesis driven approach ensured full focus on most critical business model levers.

For each hypothesis a deep dive analysis of the status quo was conducted and a respective results one pager in the logic “the good, the bad, the ugly” was created. Based on these one pagers, a list of tangible recommendations for action were formulated, to mend the identified issues.

In the short time frame of 4 weeks, over 30 interviews were conducted, and a large variety of materials were analyzed, to create the following output:

  1. Assessed hypothesis tree with color coding, to showcase severity of challenges (green, yellow, red)
  2. 30+ detailed one-pagers per hypothesis, documenting status quo and sources, as well as identified roadblocks and recommended solutions
  3. An executive summary of our recommendations for short-term implementation, as well as Excubate’s advice on the product strategy
  4. A full report on all findings, presented in front senior stakeholders

Based on the audit results, our client went on to formulate a 100-day action plan with respective milestones and working streams for the rollout. The launch of the product is now successfully in execution.

Are you interested in a similar business model audit for your company? Do you have any further questions on our methodology?

Feel free to contact our Partner Dr. Markus Anding (markus.anding@excubate.de) or our Project Lead Jan Hartung (jan.hartung@excubate.de) any time!

The Autonomous Electric Vehicle (AEV) – turning point or imperceptible change?

Executive Summary

This article provides a perspective on the current state and future direction of leading automotive nations with regards to two emerging technologies, electric vehicles (EVs) and (semi-)autonomous vehicles (AVs), which we believe will come together (AEVs).  Furthermore, this article intends to equip fleet managers with an understanding of challenges and possibilities that arise from these combined technologies and provide guidance on how to prepare now, ensuring ideal positioning and aiding future competitiveness.

 

Our research shows that leading countries pursue both technologies but approach them with different focus. Generally, countries can be grouped in three different clusters (1. AV first, 2. EV first, 3. balanced approach). Findings further indicate these technologies will change the nature of fleet managers jobs, shifting it more towards a strategic rather than operational role. Converting their fleet to AEV, fleet managers can expect a higher degree of temporal and spatial flexibility, in-creased importance of fleet to employee effectiveness / productivity, higher degree of fleet utilization and thus decreased fleet size, new forms of commercial engagements with OEMs, and resultingly less operational fleet management tasks and reduced fleet costs. To leverage these benefits, fleet managers must transform their role to a more strategic role, contributing organizations transform and overcome challenges in areas of infrastructure, organization culture and change management (taking employees on the journey), use case and business plan definition.

The autonomous electric vehicle (AEV) – turning point or imperceptive change

Introduction

Both, electric and (semi-)autonomous  vehicles, have been under development for several years and are slowly being introduced to the market1. While governments around the world pave the way for accelerated adoption of EVs  , aiding their climate targets, automakers drive the launch of AVs to unlock new business opportunities by cooperating with hyperscaler (e.g., Microsoft, Amazon AWS).2, 3

Given the dominance of electrification (no other upcoming tech. is nearly as dominant) and the general trend of automation (OEMs thrive towards automation), we believe these two trends will come together and shape fleets of tomorrow.

While there are insights on both topics in isolation, we believe the convergence raises many questions about associated challenges and business opportunities for fleet managers. Fleet managers need to understand the benefits and limitations AEVs bring and how managing an autonomous, electric fleet substantially differs from a traditional ICV fleet. The complexity of both technologies and associated topics e.g., technological limitations, legal landscapes, infrastructural conditions, user acceptance, and respective underlying drivers lead to uncertainty. This leaves future-oriented fleet managers with ambiguity on specific actions that need to be taken today.

Providing actionable insight on steps that should be taken now, is the objective of this paper.

To effectively do this, the paper examines the status quo of leading automotive nations and provide an outlook of progress to be expected in the coming years (till 2030). It will than provide a perspective of what an AEV future may look like, examine emerging benefits, and lastly identify potential challenges and issues, fleet manager will need to address soon / now.

 

1: Allianz (2022)

2: Bundesministerium für Umwelt, Naturschutz, nukleare Sicherheit und Verbraucherschutz (2021)

3: Capgemini (2021)

Status quo and 2030 outlook AV & EV based on seven leading automotive nations

While the future (largely electrified and automated fleets) will likely not differ for leading automotive nations, their paths towards this future likely will4. Understanding their paths and likely progress nations will make in years to come is key, as it sets priorities and gives context for actions fleet managers need to take now.

Figure 1 below shows current readiness and expected progress towards AEV until 2030 for the seven leading automotive nations.

4: Further details on the status quo assessment, the projection for the year 2030, and what 100% on each scale imply can be found in the appendix

Figure 1: AV and EV readiness of the seven leading automotive nations

Looking at Figure 1, it can be concluded that every country is different in terms of current state and expected progress to be made. Nonetheless, countries can be grouped in three clusters, based on the likely progress they will make and priorities they set. These cluster are:

 

  1. Japan & South Korea, putting clear and sustained focus on AV first (& EV later)
  2. European countries & the US, looking to develop EV & AV simultaneously (each set a slightly different focus)
  3. China, with its ambition to become the world’s foremost source of renewable energy, pursuing EV first(& AV later)

Cluster 1: Japan & South Korea: AV first, EV later

The first cluster is formed by Japan and South Korea. Both countries have their strength in autonomous driving and are likely to be late adopters of electromobility.

While both countries do have EV ambitions (e.g., Japan wants 50-70% and South Korea 33% of new cars to be EV (and/or hydrogen in case of Korea) by 2030), their recent adoption, production and innovation track record indicates stagnation of EV readiness and adoption5, leading us to believe that only very moderate progress will be made.

More focus is placed on AV, which will likely progress fast. One indicator is the high number of patents filed for AV technologies by Japan’s automotive OEMs, leading to an optimistic AV development forecast5. Looking at SouthKorea, the government’s strategic plan intends 54% of new cars sold to be AVs working at either level 3 or 4, with 12% working at level 4, by 2030. The government has also formed an alliance to help vehicle and component manufacturers collaborate with technology companies. This intensive governmental support for infrastructure development as well as legislative processes is critical and points to a steep future AV trajectory.6

5: Bernhart W., Riederle, S., Hotz, T. et al. (2021)

6: Threlfall, R., Püstow, M., Ng, Philip et al. (2020)

Cluster 2: Europe and us: EV & AV the same time

European countries and US are taking a balanced approach, pursuing both, or in some cases none of the technologies, simultaneously.

Having a closer look at the European countries and expected EV development, Italy’s readiness and outlook are the weakest of examined European nations and expected to be falling further behind, as neither EV nor AV are prioritized technologies for Italy, as for example demonstrated by the slowly expanding but still rather limited range and variety of Italian EVs7.

France competes with Germany for the pole position in Europe EV market. While both countries have their own strengths in the field of EV (Germany has a wider array of EV models and better range, while France has significantly more battery building capacities8), they are similar in terms of political support and societal willingness. This is for example demonstrated by France’s President E. Macron unveiling a €4 billion investment plan for the country’s transport sector modernization, German government’s commitment to building 15 million EVs (app. 40% of cars currently registered in France) and 1 million charging points by 20309, or 61% of French people being willing to buy an EV as their next car10.

Nonetheless, targets and a generally high pace in Europe are driven by the European Union, which passed a regulation only allowing 0-emission cars (mainly EV) being registered as new cars from 203511. This will force countries, like Italy to pick up momentum and motivate leading nations such as Germany or France to push hard, leading to a generally optimistic outlook for EV readiness and adoption.

As for AVs, the European Union is playing less of a driving role. Here national strengths and weaknesses will dictate the pace of initial development. As such, Italy with its limited political stability and inflated cost of AV technologies, is expected to make initially more moderate gains.

On the other hand, France, being the first nation in Europe to have a comprehensive legal framework for AV, intensified focus on AV related research and leading AV relevant cybersecurity capabilities is expected to progress better. This, however, is hampered to some extent, by the lack of local technology player in France, increasing the need for collaboration with international player, such as Waymo12.

Lastly, Germany shows very high AV innovation capabilities, many AV-related patents, and pioneering work in interaction of microprocessor systems, sensors, and actuators (e.g., Simulytic a Siemens AG venture for AV Simulation).13 Germany is also a role model in terms of industry partnerships and made great strides in licensing and legislation. This, however, is hampered by a relatively low willingness of society to adopt AV technologies and sufficient mobile coverage of its road network14.

Nonetheless, due the EU’s single market, close political collaboration, and cultural homogeneity, we believe all countries, while some earlier (e.g., Germany and France) and some later (e.g., Italy), will follow a similar AV adoption trajectory and progress in terms of readiness and adoption until 2030.

As for the United States, in 2021, President Biden set the target to make 50% of all new vehicles sold in 2030 zero-emissions vehicles. The same initiative also promotes the construction of 0,5 million charging stations for EVs and an investment of 2 trillion dollars in green infrastructure projects. Additionally, financial incentives for consumers as well as carmakers are planned15, leading us to believe EV readiness and adoption will experience further progress, if the current political course is maintained.

In terms of AV, the US is strong in areas of cloud computing, AI, and IoT, all crucial technologies for AVs. Furthermore, technologically advanced AV companies, of which the US has many (e.g., Waymo, Apple, Tesla, and GM) benefit from regulatory support, high capital investment, and widespread consumer acceptance16. Considering these points and the great technology advances the US have already made (Waymo is currently able to operate at Level 4 automation17), we see strong development in AV, sustaining the US leadership in this technology.

7: Bernhart W., Riederle, S., Hotz, T. et al. (2021)

8: Plank, W. (2021)

9: Schaal, S. (2022)

10: Alix, C. (2022)

11: Schaal, S. (2022)

12: Threlfall, R., Püstow, M., Ng, Philip et al. (2020)

13: Simulytic (2022)

14: Threlfall, R., Püstow, M., Ng, Philip et al. (2020)

15: The White House (2021)

16: Threlfall, R., Püstow, M., Ng, Philip et al. (2020)

17: Molla, R. (2021)

Clustera 3: China: EV first, AV later

In contrast to other Asian countries, such as Japan and South Korea, China is an example of EV first and AV later. At current China is the biggest producer for EVs and largest EV market in the world, with roughly 50% of all EVs being build and sold here18. Looking into the future, forecasts suggest that while ICEVs will continue to be the backbone of Chinese mobility, 1/3 of vehicles on the market will be BEVs and PHEVs by 203019. Looking further into the future, however, China’s leadership in EV may decline. This is as China recently imposed a mandate on automakers requiring that EVs need to make up (only) 40% of all sales by 2030.20 Comparing the Chinese mandate with the EU Parliament’s decision, it is to be noted that the EU’s decision is much more ambitious, putting Europe potentially ahead of China.

When it comes to AV, China’s known challenges are the need for accurate digital maps and the development of needed policies and standards. In addition, the Chinese 5G network has yet to prove whether it lives up to its hype21, providing a critical and reliable infrastructure, AVs need. Lastly, foreign automakers are subject to strict regulations when it comes to collecting and storing vehicle data, disincentivizing investments in China and severely hinders domestic development.22 Overall, these reasons impede AV adoption and will likely slow China on its journey towards autonomous driving.

18: Mersch, T. (2021)

19: Gomoll, W., Viehmann, S. (2022)

20: Stauffer, N. W. (2020)

21: Threlfall, R., Püstow, M., Ng, Philip et al. (2020)

22: Kugoth, J. (2022)

Conclusion of outlook

Concluding from the above (for Europe), it is likely that we will see levels of electrification between 30 and 40% and early application with adoption of less than 10% of L4 driving automation, especially in leading countries like Germany. This will give fleet managers the chance to rely in part on AEVs and make some initial experience with such technologies. It will likely also mean that OEMs will have started offering cars and complimentary services in new and innovative ways, enabling fleet managers to reduce complexity and total cost of ownership.

AEVs impact on fleets and role of fleet managers

Now that we have understood, where countries are heading and where Europe will likely be within the next decade, this section looks at the impact AEVs ultimately would have on fleets and the role of fleet managers.

We envision that future corporate vehicle fleets will consist of on-demand autonomous (level 3-5), largely electric passenger cars and trucks for transporting employees and goods. Between the providing and using party Mobility-as-a-Service (MaaS) contracts, in which the using party chooses the vehicle category, model, amount, equipment, and exclusivity (vehicle dedicated to one organization, or shared usage), will be the dominant form of commercial engagement. Apart from charging expenses, all costs will be included in a monthly AEV subscription or pay per use fee, which is composed of the value of the subscribed vehicle, the autopilot subscription, insurances, taxes, maintenances, repairs, etc.

Future AEV scenario: Fleet user

Service employees use a fleet app and declare with sufficient notice they require an AEV of a certain type, on a certain day, at a certain time, for a defined number of hours or prespecified trip(s). The vehicle request is automatically checked for availability and confirmed. At the requested time, the vehicle independently drives up to the employee at designated location. The car is unlocked via phone, the vehicle can do relevant checks/verifications itself and navigates to the desired drop-off location at the client side, potentially even serving as shared transportation between multiple company sites or different companies. Employee can use the travel time to prepare for their client meeting. After dropping off the employee, the vehicle might notice that it is no longer roadworthy due to a component error. No more user fees would be incurred for this vehicle until repaired.

The integrated sensors locate the error, and a Blockchain-based smart contract is triggered. Insurance claims are filed and adjudicated based on sensor data records and conditions determined in the smart contract, thus enabling quicker financial compensation for the providing party. The smart contract also triggers the ordering of spare parts from the workshop, to which the vehicle drives itself, if possible. In return, an alternative AEV is automatically called to the site, replacing the damaged vehicle, ensuring fleet uptime, and picking-up the service employee.

Future AEV scenario: fleet manager

Future fleet managers that enter above-described car subscriptions might be, depending on the AEV-MaaS contract details, exempt from historic operational tasks such as:

  • processing accidents and organizing maintenance/repairs
  • communicating with insurance companies or other service providers
  • registering and deregistering vehicles as the provider is responsible for doing this as part of the subscription
  • monitoring legal requirements (e.g., compliance with accident prevention regulations)
  • reporting and controlling costs
  • scheduling vehicles i.e., determining how many and which vehicles for whom, and for how long
  • managing drivers and drivers related tasks (e.g., managing driving licenses, potential license suspensions, …)

Instead, fleet managers would be focusing on more strategic tasks (with a smaller team):

  • Identifying suitable strategic partner, who can meet their organizations need with the most attractive offering
  • Establishing the right engagement model for their organization (exclusive vs shared fleet)
  • Determining the level of outsourcing to / reliance on the OEM (full vs. partial MaaS)
  • Negotiating and maintaining relations with one or more strategic partners
  • Managing KPIs and SLAs for existing partnerships
  • Working out the right level of flexibility (rely freely on actual employee demand) and commitment (predicting usage and committing to basic volume
  • Building and comparing business case scenarios to identify the right partner, model, and engagement
  • Functioning as change agent in their organizations, enabling employees adapting to new means of transport and vehicle interaction

As such, we expect fleet management capabilities in organizations to become smaller (less staff), but more strategic in nature (closer to C-Level).

Key benefits of AEVs for corporate fleets

Building on the above, this section will provide a perspective on the two likely largest benefits AEV will bring to organizations and their fleet, leveraging Germany as a concrete, yet representative case study for leading nations.

Higher degree of temporal and spatial flexibility

Today’s temporal and spatial flexibility of traditional ICEVs is still rather limited as they rely on (safety) drivers and are subject to quiet times and low emission zones (impacting transport of goods in particular). In comparison AEVs, would significantly improve spatial and temporal flexibility and thus23:
  • Reduce transportation times – driver limitations would be eliminated, more direct routes (lesser noise/emission) can be taken, less potential for congestion, and improved ranges (next gen. batterie-prototypes suggest ranges of 1.000+ kilometers24)
  • Improve yearly uptime and vehicle utilization – vehicles move independently, enabling one vehicle to service multiple employees, lesser noise/emission reduces limitations imposed by (local) government, and damaged vehicles are replaced immediately
  • Generate potential for (increased) revenues from transport services – resulting from higher utilization potential
  • Increase scalability/flexibility – independence from driver supply and commercial flexibility
Improve employee productivity –employees are no longer required to focus on driving
23: Holtermann, F. (2022) 24: Menzel, S. (2022)

Reduced fleet related costs of 25-4025:

Today’s fleets are impacted by a number of cost drivers, which AEV could reduce and in some cases eliminate, reducing fleet related costs by between 25% and 40% depending the organizations reliance on its fleet and nature of business. These cost drivers are:

  • Driver – driver dependency would be decreased or eliminated, replacing driver with autonomous capabilities
  • Fleet management operations – OEMs would assume operational responsibilities of fleet managers in case of MaaS contracts, and driver related tasks would fall away, reducing the need for larger, operational fleet management teams
  • Accidents – Automation would reduce the likelihood of accidents occurring and OEMs may have to assume responsibility for accidents and therefore accident-related costs
  • Fuel and vehicle wear – monthly occurring costs per kilometer of EVs are about 20-40% lower than traditional ICEVs26. Autonomous vehicles being able to refuel (and park) when and where it is cheapest, would further increase pot. savings
  • GHG quota – reliance on clean energy would reduce costs for GHG quotas and potentially even provide a source of revenue through GHG quota trading27
  • Parking – costs and potential damages resulting from parking could be eliminated, as vehicles no longer need to park at destination

In conclusion, AEVs hold two major advantages over traditional non autonomous ICEVs, significant savings in fleet related costs as well as increased temporal and spatial flexibility, resulting in higher efficiency. These advantages yield significant gains for organizations, making timely adoption and strategic preparation imperative to competitiveness and thus success in an AEV world.

Now that we have understood, where countries are heading and where Europe will likely be within the next decade, this section looks at the impact AEVs ultimately would have on fleets and the role of fleet managers

25: Keese, S. (2018)

26: Hägler, M., Wischmeyer, N. (2022)

27: Consult appendix for more information on GHG quota

Action fleet managers need to tackle now to overcome underlying challenges

While the previous chapter explained the fundamental advantages of AEVs when adopted in vehicle fleets. This chapter provides recommendations for fleet managers, further leveraging Germany as a representative case.

Fostering adoption & initiating transformation

While AEV as a combined technology, at the maturity described above is not yet available, fleet managers would be well advised to initiate transformations, adopting partial technologies (such as EV or early adoption of partial AV capabilities) now. This would be beneficial as it would allow fleet managers to make a start on the 5 key challenges, they will need to tackle for AEV:

  1. Charging infrastructure (multitude of charging infrastructure will be needed at strategic locations)
  2. Organizational legal frameworks (such as ownership over at-home charging infrastructure, bonus malus system based on CO2 footprint and employee eligibility) 28
  3. EV fleet operations (adaptation of fleet management solutions, which are needed for EV fleets),
  4. Employee readiness and buy-in (smaller transformations will yield learnings around change management and getting employees used to change and partial technologies, will aid later adoption)
  5. Business cases elements (EV transformation will require business cases to be made, which will prepare fleet managers for future AEV business cases, required for decision making)

Achieving the above will take time and getting started earlier on this journey with a lesser transformation, will aid success chances. Therefore, active leadership now and early engagement will be key to success in working with AEV (and maximizing resulting benefits) in the future.

Fostering EV adoption, one practical challenge fleet manager will need to address is the lack of EV availability due to bottlenecks on the part of OEMs, which is currently leading to long waiting times (between 2 and 20 months). The reasons for these are high demand for EVs, the slow conversion of OEM production lines, the ongoing chip/semiconductor shortage and missing components originating from Ukraine. The implication for fleet managers when procuring vehicles is that special equipment and extra requests should be dispensed with wherever possible, as preconfigured leasing vehicles from most brands are usually available immediately or at least much quicker than highly individualized models. In this context, it shows that EVs in novel car subscriptions are often available faster than with purchase or leasing. This has the added benefit of aiding cultural transformation and employee readiness, who are transitioned away from highly personalized “own” company cars and towards transport as a more standardized service.

While EV capabilities, largely due to battery and infrastructure capacities, are still limited, they already provide a feasible option for most people carrying and most good transport fleets. Currently available +500km range on person cars and +350km for e-trucks is sufficient for most business travel/commute and 85% of land transport needs, which comes to 150km or less29. Only heavy duty and long-haul transport are currently not sufficiently solved and less feasible, because of long recharging times and limited suitable charging infrastructure.

Government subsidies, which have historically aided adoption, are also running out, or are being cut back, incentivizing quick action and early adoption now30.

For AV, early adoption is less pressing and feasible, as autonomous driving passenger cars in fleets will remain a niche for the time being and will take years to reach mass adoption. For currently available semi-autonomous driving (level 2-3) the main application area will be the highway since long and monotonous routes without oncoming traffic and passersby are easier to manage for the current state of AI. Automotive OEMs plan initial application tests of self-driving trucks in fleet operations from 2025, primarily on highways and later in inner cities and on federal roads. From 2030, their goal is to be able to realize self-driving trucks as series solutions, which implies that full-time drivers will still be needed until then.31

To gain confidence in this area and build internal knowledge at an early stage, partnerships with automation specialists on automotive OEM side should be pursued and where feasible, pilot projects and driving trials should be sought out. Findings from such engagements will lead to continuous technological improvement and can be incorporated into the OEM’s series production. Whereas fleet managers gain valuable first-hand experience in AV systems, assess automation opportunities, and possibly even receive special conditions in acquisition and use. Special conditions would be particularly beneficial for adoptions, as they could offset initially higher prices/costs, which will be encountered in a novel technology such as AV.

28: Wermke, I. (2022)

29: Liehr, C. (2022)

30: Paulsen, T., Kroher, T. (2022)

31: Enzian, F. (2021)

Conclusion

The composition of corporate fleets is and will keep drastically changing in the years to come and so will the role of a fleet manager.

Both technologies yield significant benefits for commercial fleets and while AEV as a combined and rel. mature technology is still 15+ years away, transformation of corporate fleets is a significant task, which will require action now to ensure ideal positioning/readiness for these technologies in the future.

Adopting existing partial technologies, such as EVs and engaging in relationships with AV driving organizations (such as OEM) is a good way to start preparing now. As transformation, however, will be multidisciplinary (5 key challenges will need to be tackled), C-Level and fleet managers may be well advised to engage external, expert support and identify the right strategy and starting point for them, aid with stakeholder and change management, help evolve company policies and legal frameworks, and identify and engage in the right partnerships.

Appendix

Status quo of AV & EV readiness

The current level of development in electromobility along the x-axis is based on three indicators. The first indicator is technology, which describes the current state of technological development in EVs made by OEMs in the country in question. The second indicator is industry, which refers to the regional value added in the EVs industry by national production of vehicles, systems, and components. The third indicator is the market, which deals with the size of the domestic market for EVs, based on current customer demand.32

100% on the x-axis would imply that the respective country a) achieved a technological EV development that is as good as or even better than current performance metrics of ICEVs, b) has ambitious political climate reduction targets with meaningful measures that are fully compatible with the Paris agreement, c) has a very significant regional value added in the EV industry by national production of vehicles and components, and d) has a society in which major parts accept and demand EVs.

The current level of development in autonomous driving along the y-axis is based on four indicators. The first indicator is policy and legislation which is evaluated by the variables AV regulations, government-funded AV pilots, AV-focused agencies, future orientation of government, efficiency of legal system in challenging regulations, government readiness for change, and data-sharing environment. The second indicator is technology and innovation which is evaluated by the variables industry partnerships, AV technology firm headquarters, AV-related patents, industry investments in AV, availability of the latest technologies, innovation capabilities, cybersecurity, market share of electric cars, and assessment of cloud computing, AI and IoT. The third indicator is infrastructure, which is evaluated by the variables EV charging stations, 4G coverage, quality of roads, technology infrastructure change readiness, mobile connection speed, and broadband. The fourth indicator is consumer acceptance, which is evaluated based on population living near test areas, civil society technology use, consumer ICT adoption, digital skills, individual readiness, and online ride-hailing market penetration.33

100% on the y-axis would imply that the country in question a) has policies and legislation in place that allow level 4-5 AVs, b) has achieved the necessary degree of technology and innovation to enable level 4-5 AVs, c) has established the necessary road and network infrastructure that allows level 4-5 AVs, and d) has a society in which major parts accept and demand level 4-5 AVs.

32: Bernhart W., Riederle, S., Hotz, T. et al. (2021)

33: Threlfall, R., Püstow, M., Ng, Philip et al. (2020)

Projection of AV & EV Readiness

We think that the main influencing factor and first driving force for the future development of the national EV markets are the national and international CO2 emission guidelines for achieving the specified climate targets. If these guidelines did not exist, automakers would continue to market ICEVs as they have in the past. It is likely that the more stringent the emissions guidelines, the more a regional EV market will need to develop to meet the regulations, so underlying variables such as charging infrastructure, consumer demand, and technology development will follow suit. Looking at climate targets as a starting point for the development of each regional EV market, the countries with the most ambitious and binding, yet achievable, climate targets are likely to develop the strongest.

The CAT (Climate Action Tracker) evaluates countries according to policies and actions, domestic targets, fair share targets, and climate financing on a scale from critically insufficient, highly insufficient, insufficient, almost insufficient, and Paris agreement compatible. With this framework it is identified whether: a) government promises for targets and action in its country are ambitious with respect to global least-cost mitigation pathways, acknowledging that most developing countries will need support to achieve this level, b) government promises for action in its country with its own resources and, if relevant, the financing of action abroad represent a fair contribution to global efforts, c) developed country governments are providing sufficient support to developing countries OR developing countries are making plans to use support provided by developed countries, d) governments are putting in place real policies and action in line with global least-cost mitigation pathways or fair share principles and are on track to meeting their promises.34

According to the CAT’s current assessment, the climate measures of the EU, the USA and Japan are insufficient, while the measures of China and South Korea are rated as highly insufficient. Using these assessments of policy directions to project the current level of EVs development into the future, we expect the EU, US, and Japan to develop more strongly, while China and South Korea will develop more slowly by 2030. Germany continues to catch up with China in terms of electromobility.35

Looking at the development of autonomous driving, it differs from the development of electromobility. There is no generally applicable guideline that prescribes the increased use of AVs, for example, to increase road safety. Rather, the driving force is the industry’s desire to capitalize on business potential and gain a competitive advantage by offering its customers the benefit of getting from point A to point B in a convenient and safe manner. Again, the principle of cause and effect applies, i.e., if industry ambitions expressed in investment to support technological AV development are high, other underlying variables such as infrastructure investment, technological innovation, and the regulatory environment will follow to support the desired development. However, actual regional consumer demand and acceptance are non-negligible factors that must be considered in this context.

The AV-related investment assessment refers to the countries of investing organizations, rather than where the investment is made. For the assessment, all AV-related investments listed by Topio Networks and Crunchbase Pro were considered. The consumer acceptance assessment is based on the individual criteria population living near test areas, civil society technology use, consumer ICT adoption and digital skills, individual readiness, and online ride-hailing market penetration. Evaluating the current level of investment in AV technology by each country industry, as well as current consumer acceptance, the following ranking occurs: USA, South Korea, China, Germany, Japan, France, Italy. These evaluations imply that the U.S., as an early adopter in the AV space, is performing better overall than the other countries, providing a favorable basis for strong future development, and maintaining leadership in terms of overall AV adoption.36

34: Climate Action Tracker (2022) [1]

35: Climate Action Tracker (2022) [2]

36: Threlfall, R., Püstow, M., Ng, Philip et al. (2020)

37: Bernhart W., Riederle, S., Hotz, T. et al. (2021)

EV readiness: underlying status quo and forecast assessment37:

AV readiness: underlying status quo and forecast assessment38:

Overview of automated driving levels39:

No automated driving function: The driver is fully responsible for longitudinal guidance (maintaining speed, accelerating, braking) and lateral guidance (steering). There are no intervening systems, only warning ones.

Autonomous level 1 – assisted driving: The assistance system can take over longitudinal activities of the vehicle. This level includes e.g., speed cruise control, adaptive cruise control, brake assistant.

Autonomous level 2 – partially automated driving: In certain situations, the driver can transfer longitudinal as well as lateral guidance to the system. As with level 1, the driver must constantly monitor the system and traffic events and be able to take control of the vehicle immediately at any time. This level includes e.g., overtaking functions, lane keeping assistance and automatic parking.

Autonomous level 3 – highly automated driving: The system fully takes over the driving task, but only in special use cases i.e., on certain routes, for a limited time and when the traffic situation is appropriate (e.g., on highways). The driver can turn away from the traffic and no longer must permanently monitor the system. However, he must be able to resume the driving task when prompted by the system.

Autonomous level 4 – full automation: The vehicle can navigate on almost every route, even in highly complex urban traffic situations, and doesn’t need monitoring from the driver who could theoretically sleep while being in the driver’s seat. If the driving tasks are no longer handled by the system, the driver needs to take over.

Autonomous level 5 – driverless driving: In contrast to Level 3 and 4, fully autonomous driving requires neither driving ability nor a driver’s license – the steering wheel and pedals are therefore dispensable. The vehicle takes over all driving functions on all types of roads, in all speed ranges and environmental conditions. Rides without passengers become possible.

GHG quotas: The legislation stipulates how many tons of CO2 a mineral oil company may emit. For every gram of CO2 that exceeds this reference value, the oil company must pay a penalty. The electric fleet emits fewer CO2 emissions than currently specified by the legislator. If oil companies exceed the reference value, they can make up the difference with the emissions saved by the e-cars, buy the GHG quota and thus avoid penalty payments.

39: BMW (2020)

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Alix, C. (2022). When shopping for a new car, French people say they will mainly opt for a hybrid or electric vehicle. Retrieved from: https://www.eib.org/en/press/all/2022-040-when-shopping-for-a-new-car-french-people-say-they-will-mainly-opt-for-a-hybrid-or-electric-vehicle [on June 28, 2022] Homepage: https://www.eib.org/en/index.htm

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BMW (2020). Die fünf Stufen bis zum autonomen Fahren. Retrieved from: https://www.bmw.com/de/automotive-life/autonomes-fahren.html [on June 28, 2022] Homepage: https://www.bmw.com/de/index.html

Bundesministerium für Umwelt, Naturschutz, nukleare Sicherheit und Verbraucherschutz (2020). Förderung der Elektromobilität. Retrieved from: https://www.bmuv.de/themen/luft-laerm-mobilitaet/verkehr/elektromobilitaet/foerderung#:~:text=F%C3%BCr%20das%20Erreichen%20der%20Klimaziele,Million%20

Ladepunkte%20zur%20Verf%C3%BCgung%20stehen[on November 09 , 2022] Homepage: https://www.bmuv.de/

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Capgemini (2021). Wie Hyperscaler die Autobranche nach vorne bringen. Retrieved from: https://www.capgemini.com/de-de/insights/research/wie-hyperscaler-die-autobranche-nach-vorne-bringen/ [on November 09, 2022] Homepage: https://www.capgemini.com/de-de/

Climate Action Tracker (2022)

[1]. Rating System Overview. Retrieved from: https://climateactiontracker.org/countries/rating-system/[on June 28, 2022] Homepage: https://climateactiontracker.org/

[2]. Country Assessment Overview. Retrieved from: https://climateactiontracker.org/countries/ [on June 28, 2022] Homepage: https://climateactiontracker.org/

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Enzian, F. (2021). MAN setzt voll auf autonome Lkw. Retrieved from: https://www.mantruckandbus.com/de/innovation/man-setzt-voll-auf-autonome-trucks.html [on July 1, 2021] Homepage: https://www.mantruckandbus.com/de/man.html

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Gomoll, W., Viehmann, S. (2022). Investitionen ohne Verbote: Warum Chinas Auto-Strategie cleverer ist als die deutsche. Retrieved from: https://www.focus.de/auto/neuheiten/mega-investitionen-statt-gruener-verbote-chinas-pragmatische-auto-strategie_id_51870161.html [on June 28, 2022] Homepage: https://www.focus.de/

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Hägler, M., Wischmeyer, N. (2022). Warum E-Autos jetzt schon oft günstiger sind als Verbrenner. Retrieved from: https://www.sueddeutsche.de/wirtschaft/e-auto-tesla-volkswagen-verbrenner-adac-1.5583505 [on June 29, 2022] Homepage: https://www.sueddeutsche.de/

Holtermann, F. (2022). Darum scheitern Tesla und Mercedes bisher am vollautonomen Fahren.  Retrieved from: https://www.handelsblatt.com/technik/autonomes-fahren-darum-scheitern-tesla-und-mercedes-bisher-am-vollautonomen-fahren/28360188.html [on June 29, 2022] Homepage: https://www.handelsblatt.com/

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Keese, S. (2018). Autonome Lkw, Digitalisierung und Elektroantrieb verändern Transportwesen und Logistik radikal. Retrieved from: https://www.rolandberger.com/de/Insights/Publications/Lkw-der-Zukunft-Herausforderung-f%C3%BCr-Transportbranche.html [on June 28, 2022] Homepage: https://www.rolandberger.com/de/go

Kugoth, J. (2022). Chinas Datengesetze behindern Entwicklung von Roboterautos. Retrieved from: https://background.tagesspiegel.de/mobilitaet/chinas-datengesetze-behindern-entwicklung-von-roboterautos [on June 29, 2022] Homepage: https://background.tagesspiegel.de/

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Liehr, C. (2022). E-Lkw: Die Ladesäulen sind der Knackpunkt. Retrieved from: https://www.dvz.de/rubriken/land/strasse/detail/news/e-lkw-die-ladesaeulen-sind-der-knackpunkt.html[on June 28, 2022] Homepage: https://www.dvz.de/

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Menzel, S. (2022). VW-Tochter MAN setzt auf reinelektrische Lkw auf der Langstrecke. Retrieved from:https://www.handelsblatt.com/unternehmen/industrie/elektromobilitaet-vw-tochter-man-setzt-auf-reinelektrische-lkw-auf-der-langstrecke/28333636.html#:~:text=Mit%20diesem%20Lkw%20sei%20eine,Batterieantriebs%2C%20auch%20bei%20schweren%20Lastwagen[on June 28, 2022] Homepage: https://www.handelsblatt.com/

Molla, R. (2021). Self-driving cars: The 21st-century trolley problem. Retrieved from:https://www.vox.com/recode/22700022/self-driving-autonomous-cars-trolley-problem-waymo-google-tesla [on June 28, 2022] Homepage: https://www.vox.com/

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Paulsen, T., Kroher, T. (2022). Förderung für Elektroautos: Hier gibt es Geld. Retrieved from: https://www.adac.de/rund-ums-fahrzeug/elektromobilitaet/kaufen/foerderung-elektroautos/ [on June 28, 2022] Homepage: https://www.adac.de/

Plank, W. (2021). Milliarden-Plan: Frankreich setzt auf Akkus und E-Autos.Retrieved from: https://www.elektroauto-news.net/2021/milliarden-plan-frankreich-setzt-auf-akkus-und-e-autos [on June 28, 2022] Homepage: https://www.elektroauto-news.net/

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The White House (2021). President Biden Announces Steps to Drive American Leadership Forward on Clean Cars and Trucks. Retrieved from: https://www.whitehouse.gov/briefing-room/statements-releases/2021/08/05/fact-sheet-president-biden-announces-steps-to-drive-american-leadership-forward-on-clean-cars-and-trucks/ [on June 28, 2022] Homepage: https://www.whitehouse.gov/

Threlfall, R., Püstow, M., Ng, Philip et al. (2020). 2020 Autonomous Vehicles Readiness Index. Retrieved from: https://assets.kpmg/content/dam/kpmg/xx/pdf/2020/07/2020-autonomous-vehicles-readiness-index.pdf [on June 27, 2022] Homepage: https://home.kpmg/de/de/home.html

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The best Change Agent is not a Change Agent

Reflecting on Change

Few words have recently been used as ambiguously and non-specifically as the word “change.” Digitalization, customer behavior, threats of disruptive startups, COVID-19 impact, ecological and social responsibility requirements – all these developments seem to push companies, their management and their employees “to change.” Especially in the last decade, which was strongly shaped by digitalization, the call for change agents has become loud. The market followed: LinkedIn now lists more than 150,000 people with the title “Change Agent” or “Change Manager”.


Our daily business at Excubate involves change either as part of an internal digital transformation endeavor within our client’s organization; or, change management is needed to enable the more externally oriented building of a new venture. Based on that experience, we have developed a well-defined view on how change works and how an “agent” can or cannot drive it.


The take-away: As soon as someone carries the title ”change agent”, advertising “change” as their main professional activity, they can hardly act as an effective change agent. Some may find this thesis provoking, so let’s get to why we believe it’s true.

Change is not achieved by teaching: The information-action fallacy

Most business people have had an epiphany during the COVID-19 crisis: Switching from personal meetings to online meetings actually is possible and even the most tech-unsavvy people eventually managed. Why? Because they were required to. Required to log into MS Teams, switch on their camera and play with the mute/unmute button. Those who did not manage were left behind.
 
In contrast: Generations of change agents have tried time and time again to explain and convince, using carrots, sticks and psychologically tuned arguments to convince people of doing things differently, just to fail most of the time.
 
One can always explain what should be done differently, providing detail on why and how. And most subjects will easily agree with that information, yet will not change their behavior. It is the actual action, after being performed and repeated, that forms a habit that will be carried out without external enforcement later.
 
The catch for change agents: If their primary job is not show and perform the very action they want their change subjects to learn (e.g. brave testing and iterating innovative, unfinished ideas with customers), they cannot credibly drive people to take this action on their own. Organizational theory is just information, not action.

A case example: Output orientation in a complex organizational environment

Excubate supported a large-scale cross-industry B2B software platform project that had undergone several reorganizations and still faced a lack of common internal understanding of project objectives and value creation goals, deliverables, and roles & responsibilities among the 100+ people working on the project. The stakeholder group was a highly diverse double-digit number of companieswith diverging, partly conflicting project objectives. Participants were unclear about their roles and involvement in creating outcomes. Too many people were involved in too many things, while staffed into roles they were not equipped to play. Quick operational alignment meetings, set up for 4 people, ballooned to 20 participants who were afraid of missing out. This gave rise to inefficiencies and political maneuvers, allowing only a limited amount of work to flow into actual value creation, i.e. development of software functionalities for an actual market need. Having started this project with a large-scale implementation of the SAFe (scaled agile) framework, supported by an Agile Expert Consultant, the leadership team quickly realized that this method-heavy, overstructured approach was not only directing too much attention of the team towards “learning and experiencing how agile works” and away from output creation, but it also confused people with the sheer  number of roles, terms, release-train-frameworks, meeting types and the lack of pragmatism.

 

Subsequently, the SAFe approach was adjusted (not to say abandoned), and the teams were reorganized multiple times, up to the point where confusion was coupled by frustration, and the call for someone to help manage this organizational change (aka a “Change Manager”) got louder.

 

The approach we took to support change in this situation was not one of a classical Change Manager. A (very) short review of the situation and complication was helpful and done via a set of interviews across the organization. Although the situation was quite clear from the beginning, this helped create buy-in as well as clarify expectations within the client team. Then, however, other than merely asking questions and helping people reflect and come up with solutions for their issues themselves (information), our change role was to become an active part of the team and leverage real experience to effectively run and work in the project (action). Taking a very sober, rational and partially controversial stance vs. how things were done, we pushed for  a different way of working (e.g. by prioritizing backlog items much more strongly based on customer value creation) to make a relevant difference. Senior members of the client team appreciated someone who voiced a clear, experience-based opinion and got their hands dirty to overcome project inertia.

 

To reduce complexity in the overall working mode and guide the client team through a simple, yet very effective results-creation path, we outlined four stepswhich we believe are generally helpful for delivering results in  any, and especially in a complex, project environment:

1: Know what you are optimizing for

In large ecosystems, stakeholders always have diverging, sometimes conflicting objectives and agendas – and rarely position them openly. If there is no common ground on the question which problems are being solved for whom, it becomes imperative to enforce transparency on each stakeholder’s objectives and identify matches and conflicts. We use the Excubate Digital Value Canvas (https://www.excubate.de/digital-value-management/) to create this transparency for each stakeholder group, as well as – and perhaps even most importantly – for future customer groups. The value creation needs of the customers are always the smallest common denominator of what different stakeholders should be optimizing for. The example below shows value creation needs of different stakeholders in a mutual large project. It is interesting to see how two players of the same kind (automotive suppliers) aim to achieve very different things.

Digital Value Canvas for different project stakeholders: Same industry, different value creation objectives 

2: Define and prioritize deliverables to create that value

Value creation requirements must be linked to specific deliverables that help achieve that value. In software development terms, these are – among others – value-creating software functionalities. In other contexts, these could be projects to run or products to build. Sound prioritization – in a functionality backlog – must, among other criteria such as development effort, adhere to the defined value creation goals and have a clear rationale to build non-value creating features. Example: Building an automated customer onboarding functionality before any substantial number of customers is interested will create less value than some analytics functionality that a customer actually needs for their daily business and would be willing to pay for.

3: Devise specific, yet simple processes to create deliverables

Delivering on the prioritized goal must follow a clear approach. The term “process” is often despised in the agile community because it is perceived as old-school, and agile enthusiasts tend to have bad memories of corporate process fanatics. That is, however, a mistake. As much as the agile way rightly avoids waterfall methodologies and detailed, rigid process maps, it still requires some logic around the major steps to create outcomes (e.g. a simple 4-step process for value-driven prioritization of a backlog) to give people some guidance and minimize chaos. Prescribing the 4-5 major processes with 4-5 major steps each will be sufficient.

4: Make sure to have the right people play the right roles

Only then, roles and responsibilities along these key processes can and must be defined, e.g. via a decision making framework such as RACI and a practical role description including a view on “when has this role done a good job.” Independent of the wealth of potential roles offered by the SAFe framework, this approach clarifies which roles (and, thus, capabilities) are actually needed to achieve the above and lays ground for staffing these roles with people that bring the right capabilities and capacities – see an example below.

Involvement of roles along key processes

If change is to have an effect, these four steps need to be taken sequentially, regardless of the starting point

While the above approach describes a certain blueprint, reality often differs and running projects may already have some elements of, say, steps 2 and 3, but nothing yet on step 1. And that’s ok. Our project example was not different. It is just important to close the gaps one by one, starting with step 1.

To achieve successful change management and get a struggling project/ organization back on track, we recommend three important behaviors for the person in charge:

1.     Start with value, end with roles: Enforce a crystal-clear view on why something should be done, what should be done, how and by whom.

2.     Take action (and don’t ride theory): Get involved & get your hands dirty; show, don’t tell how it’s done

3.     Become part of the team: Nothing builds more credibility than becoming a part of the team you want to change. It is the doing that will make you an effective change agent.

So, the best change agent is not a change agent. Not someone who has only change in mind and change on their business card, but someone who actively and effectively helps drive towards desired outcomes and achieves organizational and behavior change on the way.

 If you are interested in understanding Excubate’s viewpoint in more detail and drive some change with us, please reach out at innovate@excubate.de

4-week Excubate Digital Business Model Audit – Evaluation of Digital Business Model Scalability

Intro and results

The scaling of digital business models is complex and uncertain, and a structured approach is required to successfully implement it. Excubate’s 4-week digital business model audit enables early identification of potential scaling barriers. In addition, the derivation and recommendation of tangible action items to address identified issues are in focus. The aim is to provide a fast and pragmatic solution, to ensure digital business models are future-proof and scalable. A successful business model audit also creates a blueprint for evaluating and scaling further digital products on the client side.

 

Excubate’s 4-week digital business model audit has three major outcomes:

Audit is based on three specific goals

Timeframe & structure

The audit consists of three steps: Preparation, execution, and recommendation/future enablement:

  • Audit preparation – week 1: In a kickoff workshop, objectives and overall timeline get clarified and the status quo of the business model is discussed. Important internal materials and a stakeholder overview will be shared by the client, and first interviews will be scheduled and conducted. The initial hypothesis tree, prepared by Excubate, will be refined according to specific project team requirements and latest insights on the business model.
  • Audit execution – weeks 2 & 3: In weeks 2 and 3 all hypotheses will be substantiated by screening materials and conducting as many interviews with internal stakeholders and experts as possible. In an iterative approach hypotheses deep dives with status quos get created and assessed based on Excubate experience and derived learnings. Suggested actions are formulated, based on cross-industrial project experience, market best practices and deep dive expert interviews
  • Recommendations/Enablement – week 4: In the last week of the audit an overall interpretation of the results will be made, recommendations will be prepared, and the main findings will be presented to the company management. Focus lies on the formulation of tangible & actionable recommendations – short-term as well as strategic/long-term.

4-week timeline of digital business model audit

Requirements and potential challenges

There are a variety of requirements to keep in mind to ensure a successful digital business model audit:

 

  1. Tough timeline: Four weeks is a short time frame – audit must be conducted with discipline in a fast and pragmatic manner in order to create the desired outcomes
  2. Availability and willingness to participate: Required stakeholders, partners and experts should be involved as early as possible to make sure all required interviews can be conducted within the timeframe. Some stakeholders might need convincing to share their insights and their time – a close alignment with top management helps to create the necessary momentum and mandate.
  3. Prioritization of hypotheses: Within four weeks not all hypotheses can be analyzed in the same depth. A constant prioritization, realignment with project team and focusing of the most critical topics is crucial, to ensure the most valuable outcomes. Focus should always be on most imminent challenges / roadblocks and the most dangerous, potential scaling barriers.
  4. Setting the right tone: Key to a successful audit is to have the project team on one’s side. While audits have a negative connotation, a constant reminder that the aim is to support not to criticize is of major importance. Deep dives need to be formulated in a clear and precise way, pointing out rational observations and constructive feedback for improvement.’

How it is done: Basis for the business model audit is a hypothesis tree

Excubate uses a hypothesis-based approach (see graphic below). Starting point is the main hypothesis, which states the answer to the question: “What do we have to believe in, in order to scale a successful digital business model?”. It is then deconstructed into several subbranches, reflecting main areas of the value generation, like e.g., sufficient customer value and demand, a well-designed operating model, or an overall working software solution. Each subbranch is then expended by a set of sub-hypotheses, that can respectively be validated or falsified and that are each assessed. Each of the hypotheses’ assessments is furthermore marked with a Harvey ball, indicating the level of confidence (from low to high), based on the information base that supports the assessment.

Example hypothesis tree

For each sub-hypothesis, a deep dive on pager is then created, featuring four content blocks:

 

  1. Status quo – A rational summary of collected insights
  2. Assessment – The interpretation of status quo by Excubate, structured by “the good, the bad, the ugly”
  3. Recommended action – A collection of tangible action items to be taken to solve identified roadblocks
  4. Sources – All sources used to create the deep dive

 

Within the audit, up to 25 interviews with relevant internal (e.g., product (HW and SW), legal, sales, marketing) and external (e.g., distributors, customers, product partners) stakeholders will be conducted and a large variety of materials will be screened. Besides interviews with internal key stakeholders, the feedback of well selected experts is crucial, to enable both, an inside in and outside in view. These experts should be selected specifically for the respective business model in scope and must bring deep expertise especially in areas of identified challenges.

 

Examples for experts involved in past Excubate audits are former software corporation top executives, IoT startup CEOs, senior sales managers from successful IoT companies, software integration experts (e.g., of Microsoft or SAP) or senior software developers & code experts. Suggested actions to address identified roadblocks are then based on the vast project experience of Excubate and on researched market best-practices. Here the focus lies on pragmatic and quickly implementable actions, that can heal roadblocks short-term and ensure a smooth scaling long-term.

Here are some examples to make the hypothesis-based methodology more tangible:

In this case, the digital business model was an AI-based temperature sensor than enables production efficiency gains in high-temperature production environments. The main hypothesis is defined in a short and concise way. In our example, the main hypothesis states, that the client company offers a scalable, effective digital solution to generate significant value for their customers and for their company. For this to be true there are many other sub-hypotheses that must be validated.

Example 1: First branch: “Customers buy and scale solution because it solves critical use cases along their value chain.”

To validate the overlying hypothesis of the first branch, it must be ensured that the solution creates enough customer value to create demand which would then be a sub-hypothesis of the first branch’s hypothesis.

  1. To confirm this sub-hypothesis interviews with pilot customers and sales personnel need to be conducted, and the answers must be documented and assessed. In this example, interviews, and previous studies showed that customers understand and cherish the solution, and interviews with the sales force concluded that there were no problems so with the customers’ ability to understand the value proposition of the solution.
  2. Based on this information the assessment of Excubate was positive, based on a high confidence.
  3. There was no need for suggested action, since this area of the business model was under control and well aligned

Example 2: Third branch: “The operating model is well integrated in our company core business, efficient and effective.”

For this hypothesis to be true, sufficiently many salespeople must be activated and enabled to sell the service solution.

  1. Interviews with sales force and with the digital solution team were conducted. The identified bottom line was, that the sales team does not feel comfortable yet with the switch from selling traditional hardware products to selling IoT SaaS solutions.
  2. This often seem challenge is a make-or-break factor in the scaling of digital business models. The hypothesis was directionally falsified, with a high level of confidence.
  3. Excubate’s suggestion towards the client consisted of a variety of tangible action items. These ranged from a suggested new trainings approach and alignment with the sales force, to a rework of the overall sales process, to the creation of an end-to-end customer success approach. All action items were described on a detail level, that enabled a short-term execution.

Have we piqued your interest in our 4-week digital business model audit approach?

Contact us (jan.hartung@excubate.de), to evaluate the scalability potential of your digital business models your company.

Realizing tangible business value with AI technology

Read on to learn more about the basics of AI, Excubate’s AI player selection process, and a brief introduction to an example AI manufacturing solution.

Excecutive Summary

Companies collect huge amounts of data on all kinds of business processes. Analyzing this data and turning it into tangible business value is uncertain, complex and time-consuming. A rapidly growing number of artificial intelligence-based software solutions aim to solve this challenge by using intelligent algorithms to analyze data sets, derive insights, and automatically recommend actions. Beneficial use cases can be found along all stages of the value chain; getting started is often easier than it seems. Examples show that ROI can be achieved as early as after just one day.

What is “AI”?

Artificial intelligence (AI) is a subfield of computer science that aims to enable machines to replicate human thinking and decision making. This is often achieved with machine learning (ML) algorithms, that continuously learn from datasets. In many cases the current discussion about AI is in fact a discussion about its subfield ML.

In comparison to classical systems (hardcoded and simple rule-based), ML algorithms can learn from existing data to react to previously unknown situations. Example: AI can learn what a person looks like from several existing images and then apply that rule to new images and recognize that person. This is possible due to the ML algorithms’ ability to recognize patterns in data and derive rules and statements from it. ML can be used in situations where large quantities of complex and unstructured data must be analysed and searched for patterns. It is faster and more accurate than human analyses of the same.

 

The potential use cases for AI are numerous but have yet to be fully understood. Here are some relevant business examples:

 

  • Manufacturing process optimization achieved by sensor-controlled anomaly detection (e.g. prevention of unplanned downtimes, using machine vibration analysis)
  • Recruitment improvement by matching talent supply and demand (AI-powered analysis to assess an applicant’s previous work experience and interests and match them with the most suitable job openings)
  • Price optimization based on historic and real-time data to predict how customers are likely to react to different pricing and automatically adjust it accordingly (e.g., ML algorithms crawl the web to gather information about competitor prices and trends to adjust own prices while keeping in mind business goals)
  • Product & process development, enhanced by design suggestions, consistency checks or predicted product properties for changed parameters
  • Automatic lead identification based on similar existing customers or market data, including information on customer intent (e.g., “What will my customer buy next?”)

Realizing tangible value with AI

In many cases, companies are hesitant to introduce investment-intensive technologies – and often wait until best practices appear on the market and risks are foreseeable. However, when it comes to AI, hesitation might lead to a significant loss of opportunity. Experts go as far, as to call AI as an essential building block for the future viability of companies. Within the last two years we observed 5 major challenges, that companies are facing when implementing AI technology:

 

  1. Identification of impactful, measurable, and individually fitting use cases, including creation of transparency on their quantified benefits and risks.
  2. Knowledge about what and how data can be used, data quality, and availability of data relevant to the application area.
  3. Internal AI technology knowledge and hiring high-in-demand data science teams or training existing personnel.
  4. Complex and time-intense integration of AI solutions in legacy systems (e.g., SAP).
  5. Ambiguity of what applications are available on the product and process side, oversupply in emerging solutions, and unclarity in regards of make or buy benefits.

 

Despite these challenges, AI usage is on the rise. In a 2021 McKinsey study with over 1.800 international companies, 56% of all respondents reported AI adoption in at least one business function. Furthermore, 27% of respondents reported a minimum of 5% EBIT that is attributable to AI.

 

Today, the benefits of AI outweigh the costs in a wide range of use cases. Using the Digital Value Canvas® (read here more about the methodology) the benefits of AI usage in the example of industrial manufacturing can be mapped as followed:

Using Excubate’s Digital Value Canvas©, the potential value impact of AI usage in manufacturing can be assessed.

Based on project experience, main value drivers of AI usage in manufacturing are:

  • Core Product Sales: For example, AI-based image processing promises reliable defect detection and higher batch quality. The better addressed customer needs result in increased competitiveness and sales if market demand permits.
  • Process Speed & Quality: In general, AI is not subject to performance fluctuations and delivers constant quality and speed. For instance, process models are used to compare as-is with to-be state in real time. In case of deviations, AI systems are able to automatically search for root causes and can trigger process changes.
  • Equipment Utilization: Reduced downtime and inefficiencies through predictive maintenance leads to higher lifetime of machines, as well as higher degree of utilization, performance, and quality.
  • Technology and Data Expertise: AI adoption enables the step into industry 4.0 and data-driven solutions. The dealing with associated topics creates knowledge spill over effects and sets the foundation for further expansion towards more autonomous productions.

A way to kickstart AI usage: partner-up and find the right solution!

  • Excubate supports companies in identifying technology use cases, formulating respective strategies, and identifying the right partners. In this article we want to give a short introduction to our standardized, six-step process for strategic (AI) partner selection. It enables a fast understanding of any technology as well as an implementation kickstart.

     

    1. If not clear: clarify use case, underlying technology, and initial search scopeg., through ideation workshop, interviews with business units and stakeholders, by derivation from strategic goals etc. Additionally: creation of hypothesis tree (“What do we have to believe in for a solution to be a good fit?”) for later ranking of left solutions
    2. Research of player long-list: wide-scope research of any solution that falls into the high-level search grid; quantity over quality to ensure to not miss out on any solution
    3. Definition and application of knock-out criteria: Search for specific criteria that can be used to steam down the longlist e.g., customer focus of solution, industry experience or GDPR conformity of player, …
    4. Reduction by business stability: Defining revenue and employee amount thresholds to exclude companies with low commercial performance
    5. Reduction by challenge-solution fit: Identifying business unit challenges, matching them with the solutions of left players, and abandoning of unsuitable solutions
    6. Forced Ranking through hypothesis tree: Quantification of hypotheses and subsequent evaluation of players based on the extent to which hypotheses were fulfilled
    7. One Pager Creation for top 5 players: Presentation of top player key facts and numbers; product/solution summary

Our process results in a wide market overview and a top 5 player recommendation for each respective use case in scope. It enables our clients to directly engage best fit partners and quickly introduce value-adding solutions to the core business. We directly tackle the most common challenges companies have (as were stated above):

  • Identification of use cases: we enable our clients to identify the best fit use cases in their value chain and to ensure tangible business benefits
  • Insufficient data quality and availability: we bring clarity in all data requirements and recommend needed action; we support in communicating requirements with respective business units
  • Lack of internal knowledge: we bring transparency in the technology, its benefits, respective use cases and the overall solution market
  • Integration of AI solutions in legacy systems: we support in selecting solutions that are integrable and pragmatic; we support in defining requirements for overall integration in legacy systems
  • Oversupply in emerging solutions: we offer a clear path forward, by providing a selection of top-notch partners and recommendations for a fast and pragmatic implementation

Output example: Best-fit players mapped along client sales value chain (each coming with respective detail one pager)

Solution example: dismiss unplanned machine downtimes by analyzing vibrations

 

Rotating equipment in manufacturing environments is often subject to issues, such as bearing damage, imbalance faults, cavitations, misalignments, and gearbox faults which often aren’t detected until it’s too late.

These typical problems result in inefficiencies and downtimes which, in general, can lead up to 20% of total production costs and 10% of global production losses. In the automotive sector, for example, average costs of 2.5 million Euro accumulate from just a one-hour outage.

In a past research project, Excubate applied the described research approach and identified a company that can solve such challenges. This particular solution provides AI-powered vibration-based sensors and associated software to avoid unplanned downtime of rotating equipment. The predictive maintenance solution supports early fault detection and thus avoidance of damage, production downtime, and loss of production. Testing of this solution is possible even in just a couple of days. Through a fast sensor installation, subsequent data collection and intelligent analysis, it is possible to detect first anomalies after a couple of days. This can lead in the best case to a return on investment after the first day of solution deployment.

Have we piqued your interest?

Contact us (jan.hartung@excubate.de) to make AI-based business benefits a reality for your company. Realize a fast ROI with the right partners.

How to (really) validate a business idea with a prototype

What is prototype validation and why is it relevant?

In recent years, the pace and mode of corporate innovation activities changed a lot. More and more business ideas are realized following the lean startup approach that has become a blueprint for independent and corporate startups alike. Central to this methodology is the validation of the business idea via an early-stage prototype. Launching a new business requires a lot of resources, so early validation is key to prevent a waste of money, time and effort and to avoid building products no one wants. 

Excubate still sees many companies struggling with building and validating prototypes. Building upon or expertise from our work with corporate clients and startups, we want to share our view on what it really takes to validate a new business idea with a prototype. We are aware that this is non-exhaustive. It aims to give you a first overview of the most important aspects throughout every validation step. We also want to share some of the hard learnings we made during a multitude of prototype developments and tests – some you don’t read in textbooks. 

How to excel in validation

We understand validation as a three-step process (see figure 1). For each phase, we have outlined typical tasks (jobs-to-be-done), our view on most relevant success factors and hands-on advice for how to make it work in practice. 

Step 1: Build & Prepare

The first step entails the building of the prototype and preparation of the testing phase. In this stage, the overall prototype goal and scope needs to be defined and prioritized. Here, formulating a set of hypotheses to be tested in validation and refining them through explorative interviews with end users and market experts can be a good starting point. We use a “hypothesis tree” to structure and prioritize hypotheses to be tested. 

 

As soon as you are confident to have a common ground, the product team can start building the backlog and developing the actual prototype and the validation team can work on an appropriate test design tailored to the desired validation outcome. Then, preparation of the testing phase can start. Test users need to be acquired and the user test needs to be planned. Also, the logistics and resources for the execution need to be put in place.  

 

Although this step seems straightforward, it’s hard to master in practice, as there is often a high level of uncertainty and a lot of tasks to be run in parallel. Therefore, we see three key success factors which help you to excel in this step (see figure 2). 

Key Success Factor 1: Ambitious and clearly defined validation outcome

Often, prototypes are built and tested without a clear view on what the validation really should prove. Adding to this validation teams stay within their comfort zone and do not reach far enough. A plethora of assumptions can be tested during validation but resources are limited. For example, you might want to prove that a great user experience can be developed, that customers continuously use the product, or that the product is technically feasible. Therefore, these priorities should be defined and clear metrics need to be established that allow for objective quantification of the results. The consequence of not doing this is a validation result that is not really addressing the right aspects in the right way or missing to evaluate some important questions at all. What we often see is that a prototype validation is too focused on one aspect (technology, user frontend, customer acceptance, …) but not the comprehensive entrepreneurial perspective. When done right validation goals are also set as stretch goals, questioning the status quo and really trying to make the hypotheses fall. A good way to start is to clearly agree (internally and with external stakeholders) on a set of validation hypotheses which can also become the inspiring north star for your validation project and even excite other stakeholders.  

Ambitious and clearly defined validation outcome: How to make it work in practice

  • Expert knowledge generation: Start validation by generating more knowledge on the validation object and its context by interviewing industry or target group experts. This will give you a deeper understanding what counts most for your validation project and what you should prioritize.
  • Be bold with your validation focus/goals: Of course it is key to define realistic goals. However, as project experience shows setting ambitious goals improves your effectiveness even when not meeting them 100%. Further, stretch goals generate management attention, motivate the team and help to deeply scrutinize the whole business idea. Always set a goal, consider what is doable and than slightly adjust the goal to the upper side.
  • Hypotheses as north star: Use the stated hypotheses as the project’s north star. It is extremely important to share them with your development team and designers to use the hypotheses 

Key Success Factor 2: High-quality test user generation

As user tests have usually smaller sample sizes it is paramount to select test users that give a good representation of your target group. Wrong samples in quality and quantity might produce misleading results in the end confirming or rejecting a business idea by mistake. For example, prevent to test prototypes with a large group of ‘family and friends’ participants. Either they only participate to do you a favor and don’t like the business idea at all, or they tend to avoid giving negative feedback due to personal relationships – or even give too tough feedback because you asked them not to be too positive. Moreover, when target groups are hard to access, the process of acquiring test users is to be set up as efficiently as possible to save resources and lower bias.

High-quality test user generation: How to make it work in practice

  • Early user acquisition: Treat user acquisition as a substantial task and start early. You can use expert resources to inform yourself about the target group. This helps you when communicating with the target group, setting up the test design in a user-oriented way and might generate further channels to reach out. Go and map all your available channels and key stakeholders for acquisition. Use the ones that allow for the best cost-quality ratio. Specialized agencies allow for high-quality samples.
  • Target group selection with right incentives: Be careful how you motivate and pick your test users. Try to balance the trade-off between a large sample generated from your private network as well as incentives and a smaller sample of high-quality test users. Note that friends & family might be far off the target group or will have a bias in their ratings, so at least monitor these effects closely and ensure that they are intrinsically motivated. Financial incentives might be useful to acquire the right sample but be careful to not attract people that are only after the reward.

Key Success Factor 3: Tailored & prototype-aligned test design

  • Validation is primarily about running experiments to test hypotheses about your product, so test design is the centerpiece. A tailored test design that takes all essential variables into account will assure that the user feedback really helps to check the hypotheses and it will allow for flexibility when you need to adjust the setting. Many validation projects lack such a tailored test design for various reasons: Often design is not aligned to the validation hypotheses or there is a lack of understanding of the test users and their needs. We also regularly see that the test design is not aligned with the development of the prototype itself – foster exchange between developers & test planning to make sure that the prototype has the tech stack and features to test well within the validation setup and vice versa! When it comes to preparation of the tests, often team members which run the tests are not familiar with the test design – or the test design is lacking a plan B if something does not work as planned.

Tailored & prototype-aligned test design: How to make it work in practice

    •  Alignment with hypotheses: Ensure testing design closely reflects the hypotheses. Mapping the hypotheses with your testing design will help you not to miss an aspect. A deliberate mix of qualitative and quantitative data is often helpful to cover different aspects and triangulate findings. If feasible, try to use the test design to also frontload and generate data on hypotheses that need to be answered later (e.g., pricing).

    • Inclusion of designers: Emphasize deeply with your team and align your testing approach with your designers. Ensuring this, you achieve that the test itself does not affect the users experience negatively. Personas can be a useful tool to create a test design with your user in mind.

    • Thorough internal test preparation: Run dedicated briefing sessions with the involved team members. Make sure that everything is in place by overcommunicating towards testing team and test users alike to prevent any negative experience from the testing procedure itself. Try also to secure key resources for testing as early as possible.

    • Proactive risk management: Plan for different scenarios and have fallback solutions in place. For this purpose, conduct a decent risk analysis when planning the test design.

Step 2: Test & Document

In this phase, the validation team conducts, documents, and manages the user tests. According to our experience, even if the team is well-prepared and highly committed, the first tests often reveal fast need for adaption. Therefore, test execution bears the risk of turning into chaos. To mitigate this risk significantly, we have some practical insights (see figure 3) that help you navigate through test execution.

Success Factor 2: End-user-centered test execution

Many validation projects forego to run tests very close and oriented towards the person testing the product. When validating a business idea with a prototype, you want to mitigate misleading feedback that is not coming from the product features itself. Therefore, designing and executing the tests from an end-user perspective and ensuring they feel comfortable is even more important. It maximizes the validity of the tests and gets you the deepest insight in your users’ experience.

End-user-centered test execution: How to make it work in practice

  • User-centric test journey: Establish a high user experience also in the test journey by providing comprehensive information, fast response to questions and friendly clear guidance for the test user.
  • Strong test user guidance: Always assure that the user has the right understanding for the task and questions asked. This minimizes unwanted biases and gives your results better robustness for hypothesis validation. Also make sure to create an environment where the user is understanding the context and expectations of what you are doing.
  • Documentation of users’ additional behavior and questions: Leave room for the users’ feeling and thinking and capture it to validate your hypotheses and eventually refine the prototype. Let them take the lead and majority of the share of voice. Take notes on users’ behavior in action and only talk when necessary to capture ad-hoc follow-up questions to dig deeper.

Success Factor 3: Agile validation mode

When following the lean startup methodology for validating a highly immature solution, your project will very likely evolve differently than you planned for. Continuous planning is necessary and helps to remove the bigger obstacles. However, many issues will emerge that you need to quickly act upon. Many project teams though want to run validation in classic waterfall mode, only coming up with one simple project plan. This inhibits them to reflect their project progress and flexibly adjust single activities and milestones. Do better and use agile principles: This allows you to optimize for speed and rather fix issues on the fly, using for example the clearly assigned bug fixing capacity (as mentioned before).

Agile validation mode: How to make it work in practice

  • Continuous monitoring and adjustment of hypotheses: Check and discuss your validation hypotheses regularly within your team during test execution and evaluate if priorities have changed, new hypotheses need to be added or if the test design should be adjusted to better validate hypotheses.
  • ‘Overcommunication’ towards all stakeholders: Adapt quickly and recognize that overcommunication in all directions and emerging shifts are rather the new normal than exception. In case of needed changes during test execution, ensure you communicate transparently and proactively – not only towards the test users but also towards all other stakeholders, e.g., internal sponsors and external partners. Additionally, try to create the culture and meeting structures to allow your team to interact accordingly.
  •  

Step 3: Analyze & Decide

Wrapping-up the validation there are two essential tasks. First, test results need to be summarized and communicated towards the involved stakeholders. Second, as validation is only one step within the overall innovation process, it also includes the preparation of the post-validation phase for further developing the business idea and bringing it to the market.

The analyze & decide phase will help your validation to finalize test results and keep the momentum of your overall innovation process. For preventing your prototype from ending up on the sidelines we have two success factors that we discovered in practice (see figure 4).

Success Factor 1: Get the maximum out of your test results

To increase the chance of success for your prototype to turn into a mature product, ensure to get the maximum out of your test results. As we have often seen, prototype test results are documented in a final presentation but do not tap the full potential. Many teams do not incorporate the validation results into other key deliverables, e.g. business case and product backlog. Moreover, they do not challenge and triangulate them with other complementing analyses done upfront of prototype testing. Finally, results are often only communicated in a final management meeting without playing them back to other stakeholders.

Get the maximum out of your test results: How to make it work in practice

  • Adaption of other deliverables: Incorporate the generated insights into other deliverables like business cases and product backlog. Also compare them with other analyses from different perspectives like competitor research and market trends to have a proper sanity check.
  • Deepen pricing research: Especially for very complex and immature business ideas price indications from initial validation are often speculative. Question your pricing approach and spend effort to deepen pricing research. This means to challenge identified price points with follow-up surveys and complementing lean experiments.
  • Proactive communication of results: Communicate the gained insights to relevant stakeholders. These might be inside or outside the company. For both sharing meaningful insights will generate motivation to keep involved and support the further phases. Watch out not to lose focus and ownership getting caught in exuberant corporate processes.
  •  

Success Factor 2: Bridging to next phase

Validation is not an end, but a necessary step when bringing a successful product to the market. When your validation result are positive and critical hypotheses are validated, you want to make it to the next phase and further develop your prototype, design the business model, and scale it in the market. Despite this inevitable truth many projects are discontinued or delayed due to shirt-sleeved wrap-up of validation. By outlining the next project phase and communicating the plan towards internal stakeholders with a clear call to action, you can create the desired momentum for your product to be further developed.

Bridging to next phase: How to make it work in practice

    • Roadmap and business case: Structure the next steps in a roadmap and put a price tag behind the to-dos. This will prepare you for management discussions and increases the understanding and transparency of the due investments.
    • Partnership acquisition: If your preliminary business model needs key partners that you have already involved in the recent validation phase, try to ensure their commitment. Use the final prototype to showcase the achievement and make the business idea tangible. If possible, gather formalized buy-in by signing e.g., letters of intent.
    • Topicality check: When you are close to kick-off for the further phase, make sure that the validation results and the assumptions derived for next phase are still up to date. If you see red flags do some additional research and adapt the project setup for the next phase.

     

    This article is based on our experience in validating a multitude of business models and prototypes with our clients.

    Excubate has a battle-proven approach for successfully developing and validating your business idea with a prototype in only 12 weeks. You want to learn more about our Corporate Startup Campus? Then get in touch with us!

Watchouts when building corporate ventures

Five essential success criteria corporate startup CEOs should keep an eye on within the first 100 days

Beyond venture capital and M&A, corporate ventures have become the third pillar for incumbent corporations to innovate and grow their business with new (digital) business models.  Since 2015, Excubate has been supporting corporate clients to successfully build and scale their own startups. Drawing from this experience, we have identified five essential action areas every corporate startup CEO should bear in mind when building a new venture.

While some of those action areas are valid for any startup out there, the context a corporate  startup navigates in brings unique challenges to the table. To list some of them: Setting up the right governance model, defining the ‘organization’s spine’, making cultural fit a top hiring criterion, avoid running into the ‘building trap’, and getting your brand out there. Of course, this list is far from being exhaustive and highlights Excubate’s view on the most important topics. For each area we have identified concrete actions to take within the first 100 days of building a startup. We consolidated all of these in a “100 day plan to corporate venture building”. Learn more about the watchouts in this article.

1. Set up the right governance model

The relationship between a corporate and its startup is tricky. Best case, the corporate equips the startup with an unfair advantage to succeed in the market. Worst case, a mismanaged relationship and governance can nip the startup’s potential in the bud. Therefore, corporate startup CEOs need to define the right governance model with corporate leadership as early in the process as possible. Key areas to agree upon are oversight and responsibilities among both parties, organizational design and reporting structure, management accountability and authority, performance, and incentives. In all dimensions, it is key to come to a preferably simple model which ensures an appropriate degree of freedom for the corporate startup – and of course, to adhere to it.

 

Within the first 100 days of the startup, corporate startup CEOs should especially aim for ensuring authority on financial transactions and corresponding processes. From our experience, corporate startups should be empowered to independently conduct financial transactions (at least up to a certain amount) to speed up the acquisition of the gazillion things that need to be acquired within the first 100 days – or else CEO’s might find themselves and their team waiting for essential tools or even a coffee machine because they are stuck in corporate purchase processes.

2. Define the ‘organization’s spine’

Drawing the right boundaries isn’t only important between corporate and startup: also within the startup itself, CEOs should establish ‘guardrails’ which work as underlying principles for future development of the company. With the early leadership team, CEOs should jointly agree on company vision and objectives, the targeted organizational design, ways of working and company culture. These guardrails function as the company’s north star, providing both leadership and the team with guidance on where the company is heading towards.

 

Of course, they will be subject to change over time. But from our experience it is advisable to set up an initial version of guardrails within the first 100 days. Defining your cultural guardrails early on will help tremendously in onboarding new employees as it provides them with guidance. With rapidly growing team size, it will become increasingly difficult to align and establish a harmonious culture the longer you wait. Plus, quite frankly your team will become busy with operational tasks, focusing on getting the solution to the market. Having guardrails established by then allows for smoother processes and ensures that your team’s focus remains on creating value for customers.

3. Make cultural fit a top hiring criterion

Your hires have a tremendous effect on the company – not only in terms of direct success but also in terms of the company culture developing. They will shape the working and communication style of your future organization and influence your ability to attract and retain needed talent. For small, young companies, the cultural fit of every new employee is especially important as one single misfit can impede the entire intended organizational culture.

 

Therefore, especially for key hires within the first 100 days, make cultural fit a top hiring criterion to ensure new hires bring the ‘right’ mindset: hands-on, can-do mentality and pushing for outcomes not processes. From our experience, the proverb ‘hire slowly, fire quickly’ holds true. We recommend to initially fill positions in an interim way with freelancers rather than compromise on quality of new hires in the long run.

4. Avoid running into the ‘building trap’

Getting an MVP out as fast as possible to make valuable learnings is key for startups. One shouldn’t get stuck in analysis paralysis. However, from our experience it pays off to take the time to validate assumed customer needs and your initial solution thoroughly enough. To avoid running into the ‘building trap’, don’t ramp up product development too early. Product development needs input and costs money – chances are high you will develop features with only little value for customers just to ‘keep the machine up and running’, leading to a self-fulfilling prophecy (“the start-up won’t fly”) and/ or inevitable pivots later.

 

During the first 100 days we recommend hiring external software development firmsf needed, get additional resources on board to remain flexible with your product development, like UX researchers. Also, from our experience it’s essential to build up customer feedback structures to be able to continuously validate solution ideas already early on.

5. Get your brand out there

Especially in corporate context, a lot of startups tend to operate in stealth mode for too long and don’t disclose their ambition openly. One potential reason can be hesitance of the corporate to go to the market –or even to approach existing corporate clients– without a high gloss polished brand and still premature products. However, we have seen that doing exactly that early on is a key factor for success. From our experience, it’s essential to start talking to customers early on –even for just communicating the company vision– to get timely feedback on ideas and build up crucial relationships to potential future partners.

 

Ideally, we recommend establishing and getting your core-brand out within the first 100 days. If you find yourself struggling due to prolonged alignment with e.g., the sponsoring corporate, we suggest to either create an interim brand appearance (you can always pivot later) or to agree on a company brand and keep it separate from future solution brands.

 

From our experience as a company builder, taking these five actions early in the venture building process will save you a lot of trouble later. As mentioned, this list is far from being exhaustive. Excubate has a battle-proven approach for successfully building, launching, and scaling your new business models within 6-18 months. We’ve consolidated our learnings into the Excubate 100-day plan for corporate venture buildingwhich includes the most important deliverables, methods, tools, and watchouts to help you navigate through the first 100 days and ramp up your corporate startup with the steepest slope possible. Learn more about the Excubate venture building approach on our website.

 

Do you want to know more? Then get in touch with us!

Value Creation with Digital Products and Services: Digital Value Canvas Part 3 – Outer Ring

A new concept to map and design value creation from digital initiatives

Most, if not all established companies across all industries are currently busy developing digital products and services. However, questions regarding the actual value created with these endeavors become louder and the need for a “Return On Digital Investment” (RODI) becomes stronger.

While working with companies on their digital business models, we often experienced that these solutions are solely valued by their potential direct revenues or cost reductions. Nonetheless benefits often arise from the less tangible benefits that these digital solutions offer. Excubate’s Digital Value Canvas offers a simple framework to quantify both the direct and indirect value dimensions of digital solutions.

The framework was initially introduced in an article authored by Excubate founding partner Markus Anding. Now we will explore the individual dimensions in more detail and establish a structured approach for the assessment of digital products in the field. Over the course of three blog posts, we will cover the three rings of the Digital Value Canvas.

In this post we will address the Outer Ring: Goodwill & strategic impacts. To read about the Inner Ring or the Middle Ring, please have a look at our first and second post, respectively.

The Outer Ring covers goodwill-type, less quantifiable benefits

Previously, we have concerned ourselves with those benefits of digital products that can be more or less easily quantified. However, now we will address highly intangible benefits that too often remain underappreciated by senior staff mostly interested in numbers.

In many ways, companies struggling to monetize digital products directly should rather try to link them to less measurable goodwill impact. More specifically, digital products can contribute to fundamental elements of the business that define the long-term success of the company. Thus, discounting digital products due to a lack of directly measurable impacts falls short of reality and in this article, we will provide a structured approach for this issue.

Brand Awareness

Brands are among the most valuable intangible assets

A brand is the sum of all ideas, perceptions, and emotions, which customers associate with a specific company or product. Brands distinguish a company’s products from those of their competitors. They can be one of the most valuable intangible assets in a company’s value base. Examples for well-designed and extremely valuable brands are Google, Apple or Coca Cola. Strong brands reflect a superior value promise.

Brand awareness can be defined as the extent to which a specific brand is known on consumer/customer side. This does not only include the brand name, but also familiarity with e.g. the value promise, quality, products / services, standards or history a brand stands for. An example for high brand awareness is German manufacturer ZEISS which is globally renowned for its high-quality standards, precision, and reliability.

 

Digital products can have major impacts on a company’s brand awareness. Two examples will give an idea on how this works:

  • Pokémon Go: The Pokémon Company created its first AR based mobile game with Pokémon Go in 2016, which proved to be extremely successful. Through the introduction of the app, the company made international headlines and was on everyone’s minds. The app attracted a high number of users in a very short period of time, most of which never played a Pokémon game before. The example shows how the popularity of digital initiatives can strongly increase brand awareness. Furthermore, Nintendo (owner of the Pokémon Company) was able to use their brand’s popularity to convert a large part of the app’s new users to their console-gaming core business.
  • BayDir Platform: Bayer Crop Science’s digital customer platform BayDir is a freemium smartphone app for all operating systems (i.e. iOS, Android). It is targeted at farmers, merchants, and consultants and provides services such as specific farming advice, a personalized newsfeed, and a direct contact to sales partners. The freemium sales model supported its dissemination among various user groups. The app creates daily user touchpoints, increasing the awareness for the Bayer Crop Science brand (that most customers rarely come into contact with) steadily.

Focusing Brand Awareness equals focusing on revenue increases

For the majority of products applies: the better known a product is, the more it is consequentially bought. Furthermore, customers often do not differentiate between a brand and the products sold under its name. This leads to the conclusion, that a high brand awareness can lead to a general increase in product sales in most markets.

The importance of Brand Awareness furthermore results from its influence on other dimensions of the Digital Value Canvas. The Pokémon example above showed, how brand awareness can be converted into core product sales. Moreover, companies that enjoy high Brand Awareness, often also enjoy the consumers’ trust through the sophisticated maintaining of long-term, emotionally charged relationships, thus resulting in improved Customer Retention.

However, Brand Awareness also derives some importance from the increasing importance of e-commerce. Since online customers cannot hold or feel the products they buy, they have to rely on characteristics such as average customer ratings or, trust in the brand name. More specifically, someone looking for e.g. a new phone, will usually start their research with the brand that first comes to their mind, which leads us to our next paragraph on how to measure brand awareness.

How well do your customers know you?

After the successful introduction of a digital product, the question regarding its public reaction usually comes up. Since most new products are externally focused, it is essential to monitor what customers and main opinion makers think of it. As touched upon above, this is indirectly reflected by Brand Awareness. Most commonly, it is measured by talking to a group of target customers.

 

In practice, customers are asked what brands come to their mind when asked to think of a certain (core) product. For example, a machine manufacturer in a B2B context could ask industry experts at a relevant trade show, while a manufacturer of toiletries with a larger focus on B2C-business could ask customers of a drug store.

 

The results are aggregated and divided into three categories: Top of Mind, Unaided Recall, and Aided Recall.

 

  • Top of Mind is the first brand that a customer lists. It is often the most prominent in the media (there is no distinction between good and bad press), and it is usually considered best practice (when it is not infamous or scandal-ridden).
  • Unaided Recalls are all brands that are listed after the Top of Mind brand. They are the main competitors of the Top of Mind brand and also very present in the minds of customers. Furthermore, they are substitutes and can replace the Top of Mind brand.
  • Aided Recalls are brands that are not mentioned right away, and customers need to be remined of them with further assistance (i.e. a picture of the company logo) from the interviewer. Being in this category implies that customers most likely do not know the brand and thus do not include it in their buying decision.

 

Here, one would compare the responses of two similarly representative target groups before and after the introduction of the digital product. If it received a lot of publicity, more customers will remember its brand name without further assistance.

Nonetheless, the impacts on Brand Awareness can manifest in a multitude of ways. Other KPIs to measure Brand Awareness before and after the introduction of a digital product include but are not limited to:

 

  • Amount of website views: The number of visitors on the company website over a specific period of time.
  • Amount of search engine searches for the brand: The number of times the company has been searched for over a specific period of time.
  • Frequency of brand mentions on social media: The number of times the brand is mentioned on social media outlets such as Twitter. More sophisticated algorithms can even determine the sentiment that is indirectly expressed in the social media post.

 

The success of most companies heavily depends on their Brand Awareness, especially in consumer goods markets, but also in B2B environments. It is therefore critical to measure the extent to which your customers are familiar with your brand.

The key to Brand Awareness

In the age of increasing customer-centricity, you should make sure that your Brand Awareness reflects your ambition. Digital initiatives can help you build up a strong and positive public perception, thereby paving the road for long-term success of your business. Can you think of a digital product that not only complements your core business but also positively furthers your Brand Awareness?

Employer Branding

In times of declining supply of top talents, companies have to reinvent their image to stay attractive. The next paragraph connects digital initiatives to an improvement in Employer Branding and gives indications on how to measure it.

It may take a lot of effort for companies to be considered attractive

Employer Branding is closely related to the overall organization’s brand. However, it is narrower as it only considers the brand’s attractiveness from an (potential) employees’ point of view. More specifically, it is whether or not key stakeholders perceive the organization to be a “good place to work”.

Defining factors of stakeholders’ perception are for example the work-life balance that is fostered by the organization, the salary, the set of employee benefits (e.g. maternity leave) or the degree of autonomy that is promoted by superiors. Moreover, they include a company’s perceived innovation power, culture, or its success. In other word all positive feelings and perceptions that employees identify with their company, positively influence employer branding. It manifests in all initiatives that are intended to attract and/or retain the best talent for the organization and as such is a defining factor for the organization’s long-term success.

Digital solutions become more and more important in terms of employer branding. One example would be an AI-based match-making platform for internal mentoring between junior and senior staff. The automation and digitalization of mentoring improves the match-making process by connecting better-fitting individuals. This leads to a higher quality in mentor-mentee-relations which creates increased value outcome for both. As a result, the working environment improves, leading to a better perceived quality of life at work, and thus increased Employer Branding.

Strong employer brands include renowned companies such as e.g. Apple, Netflix or Google. While working there is not necessarily leading to a better life quality, their innovative products, top notch performance and, last but not least, digital mindset creates a huge attraction. It is therefore no surprise, that among the world’s most successful employer brands are mostly highly digital-focused companies.

Employees are among the top valuable assets of every company…

Therefore, it is almost indisputable that attracting and attaining top talent is a critical success factor that each company must pay close attention to. This is fueled by the “war for talents” which more and more forces companies to invest a lot of effort to attract skilled employees. This becomes more and more relevant in a digital world, with its “digital native” younger generations. AI, RPA, and cloud computing are merely a few of the digital trends that are bound to change the way we work, and in a wider sense, how organizations work.

In conclusion, although it is most likely still as important to attract and retain top talent as it was 20 years ago, it has become a lot harder. Accordingly, focus on Employer Branding is gaining more and more importance as the most critical response to the war for talent.

How can Employer Branding be measured?

The logical next question is therefore: How does one know if the initiatives that one’s company has set up actually improve its Employer Branding? Some KPIs give guidance on that matter and help to measure it.

The quantity of new job applications is a good indicator for a company’s attractiveness. Since not each application is necessarily a good one, one should only consider the amount of those candidates who were invited to follow-on-interviews. In order to measure the impact an initiative had, compare the number of new job applications over a certain timeframe before and after the introduction of a digital initiative. It should be considered, however, that the effects of digital initiatives do not develop right away, as the process of news about the initiative being disseminated among potential employees (i.e. everyone who is currently not working at your company) takes some time. Therefore, it is advisable to compare the month before the introduction to e.g. the fourth month afterwards. An example for such a digital initiative is the acceptance of digital job applications via platforms like e.g. LinkedIn. Especially digital natives are used to fast and digital forms of application and will often shy away from classical, lengthy processes.

The quantity of applications neglects already hired employees. To measure their satisfaction, the turnover rate is a well-known KPI. It indicates how many employees left the company and had to be replaced. In larger companies these numbers can be output from the internal HR system. Here again it is recommended to wait a certain period before comparing turnover rates bevor and after the initial implementation of a digital initiative that might improve it. An example for such could be solutions that improve the employees daily work life, e.g. by automating travel expenses, enabling canteen food preordering, the digitization of meeting room reservations, an internal employee carpool app or something simple as the introduction of Slack.

Next, as above mentioned, one could also consult employer rating platforms such as Glassdoor.com. On these platforms employees, disgruntled or happy, can rate your organization and thus express the general feelings towards it. If a digital initiative had a (positive or negative) impact on your Employer Branding, you will receive first-hand feedback through these platforms. As opposed to the turnover rate, you will receive this feedback quite immediately as employees are usually most emotional about an initiative right after its introduction. This makes employer ratings the ideal KPI to test the short-term impacts of your digital initiative.

Call to action

Are you aware of how former and current employees perceive your company? Check out now if your company has online ratings, engage an employee you have not talked with in a long time and think about what you can do to actively improve your employees work life!

Agile Culture & Organizational Learning

In today’s fast-moving world it is important for organizations to adapt to new circumstances in the timeliest manner possible. Failing to do so will result in the falling behind of the organization and in the long-term to financial problems. In the next paragraphs we will highlight in what ways digital products can help an organization to grow with new technological challenges and develop a future-proof culture that contributes to continuous organizational learning.

From software development to business project management: What is agile?

An organization with an agile culture manages projects by applying agile software development methods, Scrum and Kanban being the most prominent ones. Although originating from the fields of software development and IT, agile methodologies have become an almost universal theme in modern organizations. They are usually characterized by four main components:

  1. Iterations and incremental steps
  2. Efficient face-to-face communication in cross-functional teams
  3. Short feedback loops enabling continuous improvements
  4. A strong focus on quality and the customer/user

The flexibility of these approaches allows for quickly successive release cycles, something which is becoming more and more important even outside the domain of software development. Furthermore, the customer-centricity ensures that only what is really needed/desired by the end-user is actually realized.

Together, these factors make agile methods fundamental, almost to the degree of raw necessity, for the development of digital products. As a result, the development of digital products often goes hand in hand with improvements in Agile Culture & Organizational Learning.

It is to be noted, however, that having an Agile Culture does not mean to strictly work in cross-functional teams and follow some method religiously. Instead, the process of project management should be re-evaluated constantly to make sure that the right people are involved at the right time and the touch to (business) reality is not falling short.

A good example for the manner in which digital products impact Agile Culture & Organizational Learning is the intelligent Report Service App by the KION Group AG. In a dedicated setting called the “KION Digital Campus”, which is solely reserved for the development of digital products, cross-functional teams work together using a value-based validation process.

In this setup, agile approaches are applied by changing BU/customer experts, thereby carrying the techniques and agile mentality out into the organization. As a welcomed side-effect, by working in this mode the different functions within the firm are exposed to new technologies, thus allowing them to develop new capabilities and expertise areas.

Why adopt agile methods instead of traditional ones?

As people are getting used to the experiences they make in their private life (e.g. next day delivery on Amazon.com), more and more experiences that were traditionally exclusively available to B2C business are being demanded in a B2B context. This forces companies to focus more heavily on the customers’ point of view in order to keep up with competition. However, this also opens up various opportunities:

By getting to know their customers in a more intimate way, companies can predict certain behaviors, create more attractive products, and improve their marketing. The development of digital products offers companies a testing field to experiment with agile methods and new ways of project management. These capabilities may not influence today’s core business in a tangible way but will determine a company’s future development in success-critical ways.

In the era of next-day-delivery, daily innovation, ephemeral trends, and disloyal customers, companies also need to embrace change in order to master the volatility of their markets. Customers demand timely and flawless solutions. While agile development helps to identify and deliver on these new demands (e.g. short release cycles, daily touchpoints, strong engagement), it also needs a clear mandate within the organization to circulate and be established. The best way to introduce an organization to it, is by implementing successful lighthouse projects.

The development of digital products has proven to be a great way to enable the aforementioned. A good example is German machine manufacturer Trumpf which started its digital transformation among other things with the execution of campus-mode projects. These agile-driven lighthouse projects found a lot of approval within the organization and information about them spread fast throughout the company. Today, Trumpf executes many of its projects in campus-mode and has already built a track record of successful agile projects throughout the whole organization.

How a lighthouse project can improve Agile Culture & Organizational Learning

The effects the development and subsequent introduction of digital products can have on a company’s Agile Culture & Organizational Learning may sometimes be rather hard to grasp. After all, this value lever is located on the Outer Ring of the Digital Value Canvas. As the above example illustrates, however, the introduction of a first lighthouse project which adopts agile methods for its project management, can have large-scale effects.

A comparatively straight-forward way of measuring this impact is estimating how many non-project employees were informed in one way or another about the project and, more specifically, its agile methodology. This can manifest in a number of ways, some of which are

  • a company-wide newsletter
  • a public announcement during a shareholder meeting
  • coverage by an external media outlet
  • word of mouth between project and non-project employees
  • upwards feedback by the project team

As the word gets out about the flexibility and efficiency of agile approaches, general interest peaks and more projects will be implemented in an agile manner. For this, of course, more employees will have to be formally introduced to the methods and levers of agile methods, thus creating a new area of expertise for them and resulting in the overall organization’s learning. Practice has proven that this knowledge spillover effect has the potential to alter the way organizations operate entirely, thereby making them more flexible as well and adaptive to external challenges.

Start today, by asking the right questions!

Agile methods start with agile people! Commit yourself to asking these three questions once a day in a meeting for one week:

  • What does this mean for our customer?
  • How can we generate value from this?
  • Which internal expert or customer can give us feedback on this matter?
 

Technology & Data Expertise

In the last part of our series we covered Agile Culture & Organizational Learning as a distinct value driver for an organization. However, the segment focused heavily on concepts and methods that could be learned by and trained to employees. Now, we would like to shift the focus towards knowledge, or more specifically technology and data related. The next paragraphs will elaborate how digital products can foster and enable a higher degree of Technology & Data Expertise.

How digital products and technological/data expertise are related

Data is a collection of qualitative and/or quantitative variables and has evolved to be one of the most influential and decisive resources. From large amounts of data information (i.e. useful conclusions from data) or trends (i.e. tendencies in the data) can be derived. These derived information packages form the basis for management decisions.

Technologies are techniques and skills involved in the production of goods or the provision of services. This makes technologies essential for the delivery of the core business. Today’s digitally affine business environment enforces both new technologies and large amounts of data on organizations of all sizes and especially the development of digital products touches upon both.

A great example for a company that sustains their employees’ technology expertise is a German machine manufacturer.

To sustain and improve employee technology expertise within organizations, different approaches can be adopted. An example is a global acting German glass producer: For the purpose of training and knowledge transferring they initiated an internal TV show that is broadcast online. In this show employees are interviewed about a variety of technology topics that they have substantial knowledge of as a result of their day to day tasks (e.g. IoT, AR). Over 5,000 employees follow these interviews on a regular basis and thus learn about the company’s technological resources and innovative projects.

Another way in which digital products can improve an organization’s Technology & Data Expertise is through the development process. In our previous chapter we focused on the methodological aspects of a (software) project, however, the development of digital products bears a lot of chances for the building of internal know-how, e.g. communication tools, through for example the interaction with IT-relevant personnel e.g. architects, developers. Furthermore, modern projects are oftentimes implemented with teams located around the world so the knowledge of and proficiency of remote working tools, e.g. Miro, is enhanced.

Especially challenging times require Technology & Data Expertise

According to research, global data creation will reach 2,142 zettabytes (1 zettabyte are 1,000 terabytes) (Source: Statista Digital Economy Compass 2019). If used effectively, this incomprehensible amount of data is an almost endless source of value, but the true (economic) value of data has yet to be understood on every corporate level. Only then, this critical asset is handled in the most value-adding way. Many organizations merely collect data but fail to generate value from it through the derivation of meaningful information.

Furthermore, both technology and data are close to the core business due to the digital nature of today’s economy and technology’s necessity for the provision of core products. Therefore, enhancing Technology & Data Expertise through digital products prepares the core business for future challenges.

One major challenge the world faces at the moment is the coronavirus which has disrupted almost every aspect of business. Many organizations have sent their employees home, which results in dissonance, not only between levels of hierarchy but also teams.

To ensure a smooth resumption of all projects, technology tools can be used for project management tasks. Video conferencing, online communication channels, (cloud-based) file sharing services and a wide variety of other solutions enable effective project collaboration. All that is needed is the right expertise and experience to guide through the remote work and use the right tools for the right purpose.

How to approximate Technology & Data Expertise

Similar to Agile Culture & Organizational Learning, it is also rather difficult to quantify Technology & Data Expertise. A good approximation is again the number of people that are reached through an initiative. In the provided example above, over a third of all employees were reached through the digital service (i.e. the internal TV show), thereby furthering their understanding of the technology used in the company. For the exact quantification of this metric, technology can help: Software tools offer detailed insights regarding the content engagement e.g. the click-through-rate, or the number of impressions.

 

Are you reaching your full potential?

Ask yourself what kind of data you are generating and collecting each day. To validate whether you are actually getting the most out of it, think of three insights that you have derived from your data in the past week. If you find this difficult, you should think about what technology you could adopt to help you.

Ecological & Social Sustainability

The recent COVID-19 pandemic has shifted our focus towards the people surrounding us and how our actions influence them. Many western businesses have undergone a similar shift in recent years, more specifically one towards Ecological & Social Sustainability. This shift is also about paying more attention to the consequences that one’s actions have on others.

 

A variety of studies have shown that sustainability considerations directly impact financial performance. Consequently, increasing an organization’s Ecological & Social Sustainability enhances long-term profitability and, in this section, we will address how digital products can achieve this goal.

Sustainability is the trinity of ecological, social, and economic sustainability.

Ecological sustainability consists of stability, which is an ecosystem’s capability to return to its original state after a disturbance, and resilience, which is an ecosystem’s capability to return to ANY functional state after a disturbance. To sum it up, ecological sustainability is the preservation of an ecosystem’s biodiversity.

An example for a digital solution that improves ecological sustainability is AR remote assistance for B2B machine manufacturers. Through AR equipment, a service employee is able to guide a customer through the maintenance or simple repair of a machine without having to leave his desk. As a result, all ecological cost associated with travelling are set to zero and CO2 emissions, as well as the need for fuel are diminished.

Social sustainability has two components: The internal one is the management and maintenance of cultural diversity, gender equality and healthy practices for employees in general. In essence, the internal perspective is similar to Employer Branding as it, too, aims at creating and cultivating a “good place to work”. Furthermore, social sustainability has an external component. It is concerned with ensuring e.g. that exploitation of human or natural resources is prevented, or that no trade is conducted with dictators.

Again, digital products can have a lasting impact on a company’s social sustainability. The COVID-19 pandemic forced companies to send their employees to the home office in order to slow down the spread of the infectious virus. Simultaneously, citizens were urged to limit all social contacts to the bare minimum. As a result, feelings of isolation and disconnection set in for many employees.

To address the issues related to working from the home office, companies quickly moved to digital solutions such as videoconferencing or collaborative online tools that would allow employees to continue interacting and cooperating with each other almost as if they were located in the same room. For example, videoconferencing tools allow the transmission of body signals and language that would otherwise get lost via the phone or emails and thus create deeper, more personal communication. As a result, employees feel more included, less alone, and more comfortable in their team.

An example that shows how a company’s actions can also have a large effect on external social sustainability is American jewellery house Tiffany & Co. started the Diamond Source Initiative project, which would allow them to trace and identify all of their diamonds via blockchain technology. This has a lasting impact on the trade of so called “blood diamonds”, or unethically sourced diamonds.

Although not expressively addressed by the Digital Value Canvas, for the purpose of completeness we shall also briefly elaborate on economic sustainability. In this context, it is the practice of ensuring long-term economic growth, while simultaneously minimizing the impact of said growth on social or environmental sustainability. Essentially, it is a matter of resource efficiency, i.e. utilizing the available resources in a way that maximizes the achieved output while preventing the overexploitation of finite resources at the same time.

A good example here would be Microsoft’s Azure for the energy industry. With an arsenal of technologies such as digital twin, AI, and cloud computing, Azure transformed the energy sector to increase its economic sustainability. In Norway, for example, Azure and Hafslund Nett (Hafslund), a major power grid operator, developed the basis for a nation-wide rollout of smart metering, which effectively provides real-time information about the country’s power consumption, which in turn allows Hafslund Nett to produce only the energy that is needed.

How sustainable practices ensure long-term success

Today, more goods are produced than ever before and the production, distribution, usage, and disposal all take a heavy toll on the environment.

However gloomy this may sound; it did nudge societies around the world to act more responsibly. Nowadays, Ecological & Social Sustainability are not just buzzwords to attract media attention, but for most companies they have become an ethical and financial imperative in order to sustain profitability in the long run.

In practice, it means that for example rare resources, such as most required for the production of mobile phones and other advanced electronics, need to be recycled and reused as their supply is either very limited or hard to source (i.e. because resource occurrences in nature are not very rich).

As for social sustainability, academic research and practical experience has shown that diverse teams outperform those that are not on all dimensions. Often the most innovative ideas come from groups with many minds that are not exactly alike, either due to their cultural background, age, sexuality, gender, or other circumstances. Therefore, in order to ensure that there will be any business to be made in the future, one needs to pay close attention to Ecological & Social Sustainability.

Capturing the effects of sustainable practices

Measuring the impact that digital solutions have on Ecological & Social Sustainability is challenging but these guidelines for the quantification of the impacts resulting from sustainable practices provide an initial overview. First, one can consider the amount of CO2 emissions that are caused by the operation of the company. As highlighted in the above example, digital solutions have the potential to reduce the need to travel, and as a result reduce the amount of CO2 that is emitted.

Additionally, it is noteworthy that many countries already discuss CO2 taxes and fees for those that emit the notorious greenhouse gas in large amounts, thus in the near future, reducing emissions will also become an important cost driver. Furthermore, one could evaluate the company’s gender pay gap- a metric that mostly comes to play in the social sustainability context. Ideally, a company would exhibit a gap of zero, but in reality, this is seldom the case.

Another insightful KPI is the number of employee sick leave days per time period. The number of sick leave days can be used to draw conclusions regarding the organization’s overall employee satisfaction, more specifically if the organization facilitates a “good place to work”. On these grounds it is a suitable measure to gauge a company’s social sustainability.

Lastly, KPIs such as a company’s Corporate Social Responsibility (CSR) score can provide insights on how responsible a company is operating. Although both debated and criticized by many, research has shown that there is a significant positive relationship between a company’ CSR score and its financial performance (Mohr & Webb, 2005).

 

Time for change

Take some time to reflect the impact your company has in social and ecological terms. What changes in policies or what digital products could make a great change?

Strategic Bets

Preparing for what might happen in the future is what is generally understood by the notion of “strategy”. Following this line of thought, Strategic Bets are the opportunity to benefit commercially from a digital product or capability in the future. The following paragraphs we will highlight the strategic relevance of Strategic Bets for an organization’s future success.

Strategic bets: high ambiguity, even higher reward

Strategic Bets are bold strategic decisions that have the potential to transform the underlying organization and the industry it operates in significantly. Digital solutions that fall into the category of Strategic Bets adopt nouvelle technologies or business models that have as such not been employed within the organization before. Often the core business is disrupted in the medium to long-term, in which case the growth trajectory of the organization changes inevitably and with it the organization’s staff and processes. The former facilitates the new skills required for the adoption and implementation of the new technology, while the latter enables the smooth operation of the digital solution.

One examples of a digital product that fit this description is the development of an online sales portal for a product that traditionally relied heavily on face-to-face interaction between the customer and sales personnel, as well as personal consulting (e.g. private health insurance). Another example would be the introduction of a digital alternative to the main offering of the core business, which, if successful, inevitably leads to the cannibalization of the core business (e.g. Netflix back in 2007).

To clarify the difference between a Strategic Bet and a regular strategic project, we will outline three factors we deem decisive for the proper categorization of projects.

  1. Large value potential. What makes Strategic Bets attractive, is their potentially great payoff in the long-term. Adopting a previously industry-unrelated technology to develop a new digital product can prove unsuccessful in the end but being the first mover provides a range of competitive advantages. These materialize in the form of e.g. a high market share, less susceptibility to external disruptions, or the tapping of a new market.
  2. High degree of ambiguity. As the name already suggests, Strategic Bets inhibit an exceptionally high degree of ambiguity. Here, one must consciously differentiate between risk and ambiguity. While risk is characterized by known probabilities (the chances of winning the lottery are roughly 1 in 14 million), for ambiguity not even all possible options are known. An example would be a lottery without a previously defined range of numbers that can be picked, meaning it could be either only one to five, or one to 5,000. The same applies to Strategic Bets. There is no way of knowing if the investment will be worth it in the future.
  3. Long timeframe. The longer into the future one intends to predict possible outcomes of a situation, the harder it is to make justifiable predictions. Therefore, a decisive characteristic of Strategic Bets is their long timeframe they impact. An imminent by-product of this is the ambiguity described above.

Two examples will illustrate this understanding:

Adobe Creative Suite: From perpetual license to Creative Cloud
In 2013 Adobe replaced its highly successful Creative Suite product (market leader in image editing, photography, and graphic design software) with its cloud-based product Creative Cloud. Instead of releasing new versions of the Creative Suite and selling them for large one-off license prices, Adobe changed the business model to SaaS. This was a bold move in 2013 and the risk of changing a successful product so drastically was high. In the end, the bet paid off, making Adobe a successful early adopter of cloud products and SaaS, allowing the company to further reinforce its market leadership.

Heidelberger Druck – Printing as a Service

German printer manufacturer Heidelberger Druck drastically transformed its core business from hardware sales to an end-to-end printing as a service solution. The initial aim was to enlarge the market power by vertically and horizontally integrating at once and simultaneously strongly digitalizing the core business. This Strategic Bet backfired, leaving the German company struggling with severe cashflow problems.

A business decision of life and death

Strategic bets can strongly influence the overall chances of survival of companies. A move that seems bold today can be critically necessary in the future. An often-quoted example is Kodak’s decision in the early 2000s to not focus on its initially created digital camera. The fear of cannibalizing its core business kept Kodak from entering the digital photography market. As a result, the company went bankrupt over the course of three years due to rapidly changing, unanswered customer demands.

Strategic bets offer a chance to acquire control or even create a monopoly on critical resources, markets, or competencies. In shifting industries like the photography market mentioned above, companies that bet on change are rewarded- by remaining competitive. Strategic Bets offer companies the opportunity to practice a form of large-scale entrepreneurship, a competency that gained more and more relevance over the last years.

Most markets today are strongly shaped by uncertainty, ambiguity, and volatility. This phenomenon leaves market players with no choice but to courageously invest in strategic bets to stay competitive. Since many markets currently transform from analogue to digital, especially digital initiatives are often the basis for such bets.

How can you measure it?

The ambiguous nature Strategic Bets makes their value incredibly hard to estimate and so far, there is no established approach. Therefore, the subsequent method is merely our educated perspective on the matter. More specifically, we would like to propose a measure we label Strategic Value Potential (SVP). It is a fraction that consists of two components: The estimated value pool and the cost associated with the failure of the project. For example, if the total addressable market of a digital solution is estimated to be $100 million in 10 years, and 10% of this market can realistically be attained, the value pool would be equal to $10 million.

However, the associated costs are estimated to reach $8 million (including all costs associated with the development, the market launch, and other related cost). As we divide the value pool by the cost of failure, we arrive at a ratio of 1.25. Naturally, one would have to define how big the ratio would have to be in the context of the situation for the project to be considered a success. While this this measure is indubitably only an approximation, it does provide insights into the upsides and downsides of Strategic Bets.

 

What change are you betting on?

Conducting successful business today always means balancing exploitation and exploration. Even though your core business might currently be successful, what digital initiatives are you betting and investing on, to keep it prospering in the future?

Can you think of theoretical scenarios that will strongly influence your market? What can you do today, to set the path for reacting successfully on a variety of unpredictable changes tomorrow?

Equity Story

Last but not least, we will address the value driver Equity Story. Equity Story is a line of reasoning describing why investors should be interested in buying shares of a specific company. Building and delivering a convincing Equity Story is fundamental for raising capital in the market and in many cases digital initiatives played a substantial role in the development of a compelling Equity Story. In the following paragraphs we will highlight the relationship between digital solutions and an Equity Story, and we will elaborate how the relationship can be translated into financial parameters.

The basis of investments

As touched upon above, a company’s Equity Story is the collection of arguments of a company that is to persuade investors to invest in the company’s shares. In essence, it reflects a company’s value potential, market potential, success drivers, strategy, culture, and stability. These are communicated in the form of financial publications, press releases, the company website, or media outlets. Combined, they add up to Equity Story which is consequentially an indicator of a company’s attractiveness to potential investors.

This attractiveness is decisive for an organization’s success; no matter how mature it may be. Securing funding is as important during the early startup phase as it is during later, more established phases. In the former, a compelling Equity Story helps to attract investors which will allow the company to initiate the process of scaling. In the later, the Equity Story helps to shed some light on the inner workings of the complex organization and its values in order to retain existing investors and win new ones.

A suitable example of a digital solution that has a positive impact on a company’s Equity Story is IBM’s adoption of blockchain technology in 2017. Their “Blockchain as a Service” model had a positive impact on their already strong public presence through a number of newspaper articles and blog comments. Furthermore, by embracing blockchain technology, arguably one of the most disruptive and innovative technologies in the past decade, IBM displayed a strong determination to future-proof its product portfolio.

As another example, consider a sizable accounting firm that is publicly traded and mostly services local clients. If it were to announce the implementation of a new AI-based system to automatically identify tax benefits, it would indubitably impact multiple dimensions of the Digital Value Canvas, but it would also positively influence the firm’s Equity Story. This move towards a more digital and efficient operation improves future competitiveness and thus makes the firm more attractive to potential investors.

External capital for the scaling of operations

Equity Story is one of the most important levers for financial sustainability as it allows firms to attract investors and scale its operations beyond what would be possible without external funding. However, a good Equity Story is not only relevant for potential new investors but also for those that are already invested. It is also in their interest to create a good Equity Story as this will inevitably maximize their own shares’ value.

Thus, Equity Story is a lever that is both internally and externally focused. Furthermore, it is relevant on two different time horizons; First, and most understandably, it is relevant for the current company performance by enabling the raising of capital for the purpose of scaling operations. Second, it sends important signals regarding the future readiness of a company. If, for example, a breakthrough technology is adopted, investors will see this as a positive indication for the company’s future success and thus invest in it in the present.

In the end, most digital solutions also impact a company’s Equity Story as they are positive indications for a company’s ability to adapt to the advancing digitalization and new market trends and technologies.

 

Increase the market valuation

Although being located on the Outer Ring of the Digital Value Canvas and therefore particularly intangible, measuring the impact an Equity Story can have on a company’s performance is relatively straightforward. More specifically, a direct KPI is the market price per share. It reflects the fraction of total market value that can be assigned to one share, and thus quite directly reflects the positive impact a company’s Equity Story has on its valuations.

Furthermore, digital solutions have the potential to improve a company’s value generation process and increase profits. An increase in profitability positively influences the Equity Story and the value of the company. The increase of value generation through a digital solution can therefore serve as an additional KPI.

 

Pitch your story!

Most digital initiatives have the potential to increase your firm’s Equity Story. If you were to pitch it for your investors today, what would be your three main selling points and how is it generating value for your stakeholders?

Value Creation with Digital Products and Services: Digital Value Canvas Part 2: Middle Ring

A new concept to map and design value creation from digital initiatives

Most, if not all established companies across all industries are currently busy developing digital products and services. However, questions regarding the actual value created with these endeavors become louder and the need for a “Return On Digital Investment” (RODI) becomes stronger.

While working with companies on their digital business models, we often experienced that these solutions are solely valued by their potential direct revenues or cost reductions. Nonetheless benefits often arise from the less tangible benefits that these digital solutions offer. Excubate’s Digital Value Canvas offers a simple framework to quantify both the direct and indirect value dimensions of digital solutions.

The framework was initially introduced in an article authored by Excubate founding partner Markus Anding. Now we will explore the individual dimensions in more detail and establish a structured approach for the assessment of digital products in the field. Over the course of three blog posts, we will cover the three rings of the Digital Value Canvas.

In this post we will address the Middle Ring: indirect commercial benefits. To read about the inner ring, please have a look at our first post.

The Middle Ring covers indirect commercial benefits

Digital products have effects on multiple elements of the value chain, from customer frontend (e.g. customer satisfaction and, thus, longer or more intense use of products) down to the internal delivery processes (e.g. higher equipment utilization and, thus, lower cost). While it is easy to make assumptions regarding additional product sales or longer customer retentions, measuring the real impact of digital products is much harder to accomplish.

 

The Middle Ring concerns itself with those value creation levers that are less tangible than direct commercial benefits but can mostly be translated into economic benefits comparatively easily (e.g. higher machine utilization drives down CAPEX and production cost).

Core Product Sales: The basis for successful exploitation

The first dimension we will address is the increase of Core Product Sales. By definition, core products are those products that are closest to a company’s core competencies and thus they are usually the main source of revenue. The core product already provides the user with a range of core benefits, which is why customers purchase it in the first place. However, digital products may add additional benefits or leverage existing ones, thus complementing the core product to a certain degree and thereby making it more attractive.

 

Hence, it becomes clear that, even though a digital product may not generate direct revenue, it can still indirectly earn its keep through the advancing of Core Product Sales. One example would be the introduction of a virtual assistant that helps the user to set up a very complex core product such as a CNC machine.

Fueling the most profitable initiatives

As aforementioned, core products are the backbone of any company. The regular income generated by core product finances almost every other function within the company. This makes them essential for the long-term viability of the organization, which in turn means much of the organization is focused on the exploitation of the core product. Conversely, it is the sale of core products that finances other products and also the exploration activities of the company.

 

A famous example of recent years was Amazon’s Dash Button solution. Customers could order a Dash Button for e.g. laundry detergents. When the product was used up, customers simply pressed the button which allowed Amazon’s software to automatically reorder the product. While the proprietary devices and APIs were only the enabler, the software in the background was the digital solution. The solution led to customers’ re-ordering the same product on a regular basis via Amazon, effectively cutting out the competition such as traditional supermarkets, completely.

How can you measure a digital product’s influence on core product sales?

While the influence of digital products on the core business can have countless forms, we would like to concentrate on two tangible cases in this article. Case number one is an increase in the amount of core products sold. This phenomenon was observed in various Excubate projects over the course of 2019.

 

A suitable example is an international machine manufacturer, that enhanced its core products by building a set of digital services around them. The services included real-time machine KPI tracking, automated spare part ordering, AR based remote assistance and a customer knowledge platform. In a number of interviews, our customer’s clients indicated, that the digital services were among the main selling points.

 

Since a single machine produced by our client was worth a minimum of seven figures, a single sale facilitated by the digital services had the potential to amortize the service’s development. Deconstructing core business sales to their exact root is a complicated task and not always possible. Regular interviews with customers (pre- and post-purchase) is a valuable source of information, as is the monitoring of user journeys. Furthermore, a close collaboration between sales and digital development is of great importance.

 

The second example case is an increase in core product price points, enabled through a shift in product quality. Digital solutions in a production environment are proven to positively influence product quality. An example is the replacement of measurement processes by AI-based software. In some industries the accuracy of produced goods (e.g. machine parts) determine the price on the market.

 

When superior quality leads to e.g. better certification, a manufacturing company can realize large benefits from new, digital production processes. This does not only occur in manufacturing, but also in industries like agriculture, where the produced product’s price is strongly dependent on its quality. To identify the value of a digital solution, that has a strong influence on production quality, the core product must be analyzed before and after the solution is implemented.

 

If the digital process has an influence on product quality and thereby on product price, the enabled price increase is an indicator for the solution’s value. A digital solution that enables no direct revenues at all can therefore nonetheless lead to strong financial benefits. The questions to be asked are therefore: Does the digital solution increase my core products quality? And can this increase be translated to better price points?

Identify now opportunities to leverage your core product sales!

A product portfolio is a lot like a more or less fragile ecosystem; You may never quite know how its inhabitants relate to each other. Thus, like in a real ecosystem, look for synergies between products and evaluate the potential to leverage them effectively to drive the performance of your core business. Can your digital product increase the quality of your core product or make it more beneficial to your customer?

Employee Effectiveness

Employee effectiveness is the employees’ ability to successfully complete their tasks and achieve the intended results and goals. It is located in the middle ring of the value canvas, due to its close relation to the core business.

What is employee effectiveness and how is it different from efficiency?

Effectiveness is not to be mistaken for efficiency. An example highlights the difference: Cutting the lawn in your garden with nail scissors is effective, since the job can be done very accurately. However, using a lawnmower is as effective, but way more efficient, since the job can be done in a much shorter period of time.

In other words, effectiveness is about doing the right things, while efficiency is about doing things right. Employee efficiency is thus the ratio of input resources (i.e. employee time) and output resources (e.g. tasks completed).

Let’s have a closer look at an example in a business context. A company introduces a new software that has a machine learning algorithm filter through a large data pool of past customer information. The algorithm looks for indicators that can predict the likelihood of a repeat purchase and provides the resulting list of most likely customers to the sales department. This, in turn, allows the sales rep to focus his attention on the most profitable customers in terms of repeatedly occurring business.

By enabling the sales rep to contact the “right” customers, she becomes more effective. Simultaneously, she becomes more efficient since sales targets (e.g. x sales per day) can be reached more easily, thus illustrating the close coherency of effectiveness and efficiency.

Our experience has shown that another good example for effectiveness-improving measures is the use of list-making applications such as Trello. These applications present tasks that need to be completed in a clear and structured manner and thus provide an overview over what needs to be achieved to complete a business objective. For example, such applications are useful for HR processes.

In the era of volatile markets, effectiveness becomes a critical competency

The current economic climate forces companies to focus on improving the effectiveness of their core value chain, in order to defend their competitive advantage. To realize this companies must first ensure to set the right goals and to enable their employees to achieve them step-by-step.

After getting the effectiveness right, companies can then focus on efficiency gains. There are many ways to leverage effectiveness (and various will be covered in the following posts). Nevertheless, one resource is predestined to be the starting point for all effectiveness-related endeavors, since even small changes can lead to major gains: employees.

Employee effectiveness can be directly translated into bottom-line impacts. For that reason, many digital initiatives aim at the improvement of employee effectiveness. These improvements may take time to materialize, especially in economies that are subject to legal regulations concerning employee protection (e.g. Germany) that prevent companies from e.g. firing employees. The example described above already provided a first glimpse on how these effectiveness improvements come together.

Furthermore, to leverage the greatest results, companies need to:

  1. Give the initiatives the right amount of time – Effectiveness does not come over night, employees will take a while to accept and understand changes in processes or new tools. A well thought-through change management and an understanding of the employees’ point of view (e.g. job-to-be-done) is essential.
  1. Changes need discipline – stick with the changes, even though they might increase the workload or decrease the effectiveness in the beginning. After a while these initial kick-off challenges will cease, and one can harvest the results.
  1. Ask the right questions – the digitalization of a bad process results in a bad digital process. Take your time to analyze your process landscape, understand your employees’ struggles and daily routines, understand where small changes (e.g. the utilization of a digital tool) can leverage the greatest benefits. And last but not least: see your employees as what they are: human beings and not just numbers on an Excel sheet. A great change that you believe in from a management point of view, might not at all seem desirable for your employees.

When these critical points are addressed with the necessary thought and time, digital solutions offer many ways to leverage employee effectiveness. They offer a solution to the challenges of the VUCA world by enabling employees to successfully achieve the respective company’s goals.

Connecting effectiveness with financial KPIs rationalizes digital initiatives

Measuring and quantifying the impact of digital products targeted at improving Employee Effectiveness, heavily depends on the nature of the employee’s tasks. If, for example, the tasks involve sales or fundraising, quantitative targets are usually provided by upper management and thus effectiveness can be measured quite easily. However, if the nature of the tasks is more qualitative (e.g. support staff) and therefore more subjective, it is more challenging to measure it.

 

Nonetheless, digital solutions have the potential to increase your company’s performance by curtailing activities that are not directly related to a business goal. The question is, however, how to best quantify these improvements. One relevant KPI is the average task completion rate. It revolves around the number of tasks that are completed within a given time frame and increases if more (relevant) tasks are completed successfully.

 

To return to the software example elaborated on earlier: The algorithm enables the sales rep to close more deals without necessarily spending more time on the phone, thus the task completion rate increases. Similarly, since the employee is working more effectively and thus completes more tasks, fewer employees are required. This materializes in the form of saved employee FTEs, which means the number of employees will level out in the medium- to long-run.

 

Conversely, since the capacity of each employee is enhanced, more tasks can be completed (keeping the number of employees constant). This implies that especially for growth-oriented organizations, effectiveness-enhancing initiatives present an attractive lever to increase overall capacity.

 

On a larger scale, one could also consider the overall revenue per employee that is generated. Although many aspects factor into this KPI, it is still valuable to see the relationship of revenue and the number of employees before and after the introduction of an effectiveness-improving initiative.

What does this mean for you?

No matter if you are in the service industry or the manufacturing sector: Your staff is the key to success. Thus, if there is a way to increase their effectiveness you should always opt for this solution as it will pay off in the mid- to long-term. Next time you evaluate a digital product, keep your employees in mind.

Process Speed and Quality

Digital products can support higher efficiency and output quality, e.g. by leveraging augmented reality technology for machinery servicing, Robotic Process Automation to automate finance processes or Tableau-based reporting tools that may deliver better insights for customers while simultaneously leveraging internal efficiencies.

What is a process?

A process is a bundle of different, recurring actions, organized step-by-step to achieve a specific result or goal. Companies can be seen as collections of different processes and relating resources and decisions. The quality and speed of a company’s processes largely determine its business success. Process quality can be defined in various ways. This article relates to it as the processes’ effectiveness; in other words, their ability to successfully lead to their intended end-result. Process speed is the amount of time, an effective process takes to be completed.

Process optimization has many forms and leads to great benefits

Value creation can be seen as a long sequence of different, often simultaneously occurring processes. The higher the degree of optimization in quality and speed, the better the value chain works. Especially in the current, difficult economic climate, most companies try to optimize their value chain, to reduce cost and expand profitability, thus try to optimize their processes. Digital solutions can play a major role in these optimizations, in all steps of the value chain. Two examples will lead to a better understanding.

A classical digital approach to optimize processes, is their automation. E.g. through RPA (robotic process automation) companies can digitize their process landscape. Formerly manual processes are replaced by automated and simple to install bots. The upside is clear. Bots can work 24 hours a day, seven days a week. They demand no salary, nor do they get sick or tired. But they also have no thinking of their own. Automated processes do their job as programmed. Carefully designed and bug free programs are of critical importance. Furthermore, Excubate has made some learnings, regarding RPA (and process digitalization) implementation, e.g.:

 

  1. A bad process digitized, results in a bad digital process. Before manual processes can be digitized, a detailed assessment is required. It is strongly recommended to optimize and simplify (as far as it doesn’t decrease the quality) “on paper”, before a successful bot should be developed.
  2. Which leads us to the second point: Do not digitize everything, just because you can. Take a step back and reevaluate value versus cost.
  3. After developing a digital / automated process landscape: keep track of your bots! RPA needs clear rules, accountabilities and responsibilities within your organization. Otherwise you end up with an unclear, constantly growing, uncontrollable bot portfolio. Losing control over your bots can result in expensive problems. And it may make your company vulnerable to attacks from the outside.

Another example shows, how digital solutions can optimize processes: AR remote assistance – which means offering technical remote support, enhanced by augmented reality. Since there are many areas of application, we’d like to focus on B2B manufacturing in this article. Main use cases here are machine repair, machine set ups, inspections and maintenance. Manufacturing remote assistance software offers special low bandwidth video call connections and AR interfaces, to actively support technicians and customers from afar. AR remote assistance optimizes the technical support process in globally acting companies dramatically.

 

Several business-related benefits can be realized through its implementation. E.g. the cuts in traveling and the ability to react in real-time to machine failures, increase technical support speed extremely. The experts’ and maintenance teams’ reaction times are strongly decreased, which furthermore leads to a serious decrease in time-to-solution. Especially in manufacturing, machine downtimes can become very expensive. The reduction of downtimes therefore leads to serious financial benefits at the same time. Furthermore, the ability to conduct root cause analysis from afar and then plan spare parts ordering much earlier than before, is an example for the increased process quality AR remote assistance may lead to: without traveling on site experts can now order the required spare parts immediately. This leads to a much higher first-time-repair-rate on site and replaces expensive on-site root cause analyses.

Two simple KPIs help you start measuring process speed and quality

Process speed and quality can be measured with different KPIs. In our experience two KPIs in particular give a good impression:

 

  • Quality: % of successful process execution
    All processes follow a specific goal, a successful execution is the completion of that goal without an interruption along the way, that leads to an uncompleted task chain. Put the rate of successfully completed processes before and after an implementation of a new digital tool in relation to each other.
  • Speed: Core Process completion time
    It will be difficult to analyze the execution speed of a large process landscape. To start with it, instead focus on your core processes first (e.g. sales; production). Track the time e.g. on how long your average sales process takes – from initial lead to finalized sale. Identify where a digital solution can replace or did replace critical steps and estimate the saved cost.

Start today…

Are you aware on the different business potentials, digital solutions like AR remote assistance or RPA can offer your company? Use the Digital Value Canvas now to map the value drivers these technologies can offer. Hint: there are several!

Equipment Utilization

Efficiency gains through better employment of equipment

Next, we will cover Equipment Utilization. “Equipment” in this context includes all physical resources that are not human and thus not covered by Employee Effectiveness. This does not only include machines and tools, but also e.g. the very chairs that employees sit on or a plot of land.

“Utilization” addresses the time a piece of equipment is running productively, adding value to the organization. For example, a punching machine is considered to be running productively, whenever it is actively stamping sheet metal. For the purpose of this brief elaboration we will disregard time spent on producing faulty or substandard products, which will be discarded after production, and can thus not objectively be considered productive time.

Moreover, Equipment Utilization is not only applicable to the manufacturing sector, which heavily relies on machines, but also e.g. service sectors such as hotels, which aim at maximizing the time their rooms are generating value. This can be achieved through e.g. an algorithm that adapts the rates for rooms according to insights generated from weather reports, past data, or publicly available information.

The factor that is primarily considered when analyzing Equipment Utilization is availability. However, we would like to point out, that digital solutions potentially go beyond increasing the availability of equipment, by finding smart ways to e.g. manage the total available capacity in order to maximize value creation.

For illustrative purposes, consider a company that operates 3D printers to produce filigree replacement parts for their machines directly on the shop floor of their various manufacturing plants. This process can increase machine utilization, since spare parts can be printed directly on the shop floor when needed, reducing repair times dramatically.

A digital solution can be used to increase the printers’ utilization through the introduction of a company-wide digital marketplace for printer capacity. If one plant’s printer is accumulating more jobs than it can realistically service, an available printer at a nearby plant would be able to fill in and complete the additional jobs. This effectively increases the total time all printers are in use, thereby improving their utilization.

Scaling without additional capital expenditures

The scaling of operations always goes hand in hand with additional expenditures on property, buildings, plants, or technology. These capital expenditures are tied to assets and cannot be flexibly accessed. While this may not necessarily prove detrimental, it is still recommended to optimize Equipment Utilization since it reduces capital expenditures.

 

Although it is always beneficial to reduce capital expenditures, it is even more so when your organization intends to scale up its operation. By increasing total capacity without spending financial resources on new equipment (which would of course increase total capacity as well), capital expenditures can be kept low enabling further investments.

The factors that define Equipment Utilization

Equipment Utilization is mostly dependent on availability and capacity. The former is calculated by first subtracting planned downtime, such as maintenance or cleaning work, and breakdowns from the scheduled time of a piece of equipment. In the next step, this number is divided by the total scheduled time, thus resulting in a percentage. This percentage indicates the availability of the equipment, i.e. the time it can realistically be expected to add value.

 

However, this is merely the time the equipment is expected to add value which might not denote the actual value creation. It is conceivable that it is not running at full capacity at the moment. In order to calculate capacity, one must divide the total time the equipment is actually being used by the total available time. The result is a metric that indicates how heavily engaged the equipment is.

 

Let us return to the example given above, the 3D printer on a company’s shop floor. On an average day, production runs in three shifts each lasting eight hours or 480 minutes, thus resulting in a total scheduled time of 1,440 minutes. At the end of each shift, the 3D printers are scheduled to be cleaned, which takes roughly 20 minutes and adds up to 60 minutes per day.

 

Furthermore, the printers jam once a day, thus adding another 30 minutes of downtime. Subtracting these values from the total scheduled time leaves us with 1,350 minutes, divide this by 1,440 to arrive at an availability of 93.75%. However, as aforementioned, this does not necessarily mean that the printers are generating value 93.75% of the total time. Another factor to consider is the frequency and duration of printing jobs. On days where no spare parts are required, capacity would be running at 0%, while an overflow of printing jobs may result in the printers running at 100% capacity, with some printing jobs not being completed.

 

This overflow of printing jobs can then be flexibly re-allocated by a digital marketplace to printers with available capacity at a different nearby plant, thereby improving total capacity without the purchase of additional printers. As the example above shows, the organization was able to take on more printing jobs without necessarily increasing its overall capacity by purchasing more equipment. Instead, Equipment Utilization was optimized through a digital solution.

Keep your Equipment Utilization in mind

Start today by calculating your equipment’s utilization and think how much more value you could be creating with for example a digital capacity marketplace or another smart solution you may not even be aware of.

Customer Satisfaction & Retention

Why the customer is always right

A well-known proverb states that the customer is always right. It reveals an issue that is crucial to the success of any business: Do whatever it takes (within limits of course) to make your customers satisfied and retain them for as long as possible.

Customer Retention is the ability of an organization to maintain a customer for a specific period of time. For Service businesses this means, that customers stay on or renew their subscription or contract. For classical, product-based businesses, customer retention means that customers re-buy the respective products.

Essentially, Customer Satisfaction measures how often the customers’ expectations towards a product or service were met, or even exceeded. These expectations can be regarding quality, appearance, pricing, or, since the emergence and dissemination of e-commerce, consignment conditions such as shipping time.

Digital products potentially help improving both Customer Satisfaction and Customer Retention. For example, many websites nowadays offer its visitors the option to chat with a bot in case any questions arise. While bots cannot yet replace human interaction, they can nonetheless give quick answers to frequently asked questions, thus reducing the time visitors have to spend waiting for a solution to their query. Additionally, resources at responsible call centers are freed up since the queries can be resolved before they are even redirected to a call center employee. By quickly resolving the issue through a chat bot, the customer’s expectations of swift and effective service can be fulfilled.

Similarly, a company might employ an AI-based solution that assesses massive amounts of customer data to identify instances where customers were disappointed by a product or service to derive these customers’ current level of satisfaction. The system would then propose compensatory offers and incentives to these unsatisfied customers in order to reinstate a desirable level of satisfaction.

Customer satisfaction and retention do not only play a major role in B2C, but with growing competition, e.g. in machine manufacturing, more and more B2B players must focus their efforts on this topic. This is also one of various reasons, why most machine manufacturers are developing and launching a smart services portfolio to support their core business. These extending services consist of a large variety of useful digital solutions, e.g. real-time KPI tracking, automated alert systems to prevent machine downtimes, remote assistance software or document management systems. These solutions aim at increasing satisfaction, by supporting customers in enabling effectiveness and efficiency gains in their value chain. Furthermore, smart service portfolios serve as differentiators in the large, often substitutable offering of machines on the market, thus aim at improving customer retention.

The emerging necessity of Customer Satisfaction

Since arriving at the age of information, the general public is becoming more informed by the day, most likely even by the hour. This has important implications for any company intending to retain their customers. If, for example, one customer is particularly unhappy with a product or the service she received, she can voice these concerns to an increasingly large number of customers. Publishing a review can be done in a matter of minutes via a quick review on one of the many websites that supports a review function, such as Amazon.

 

Reaching a wide audience, the review can inhibit existing customers from re-purchasing this product or prevent potential customers from even considering it in their buying decision. The former results in high customer attrition, i.e. the loss of customers. The latter is accompanied by higher customer acquisition cost, i.e. the financial efforts that have to be undertaken in order to win new customers through e.g. a customer acquisition campaign.

 

Another factor that exacerbates this circumstance is the availability of easily accessible alternatives and substitutes for products and services. Customers are inclined to look for the best possible option, which is enabled through the availability of information such as reviews, and do not shy away from switching providers if they feel like they get a better deal elsewhere. In other words, customer loyalty is at an all-time low. Consequentially, the customer lifetime value is similarly low.

 

This means that not only is it harder and more expensive to gain new customers (i.e. high customer acquisition cost), but the existing customers become on average less profitable (i.e. low customer lifetime value). In conclusion, it becomes clear why Customer Satisfaction is more decisive today than it was before. Still, the age of information is a coin with two sides. While it introduces new challenges and problems, it also presents appropriate solutions to those in the form of digital products and services.

A measurement for your customers’ happiness

Especially in a B2C-context, unhappy customers find the need to voice their opinion through crowd-sourced review platforms. As such, they produce a good indication of how customers feel about a product or service, a lot of high-rating reviews implying customers are very satisfied with how the product performs compared to their expectations. Conversely, many low-rating reviews indicate that at least one metric along which the product is most commonly measured, does not perform very well and thus customers are left disappointed.

 

Here, one can compare the average rating before and after the introduction of the digital solution. If it contributed to Customer Satisfaction, there will be a statistically significant change in the ratings once all other factors that might have influenced the change have been accounted for. However, these customer product ratings always have to be analyzed with caution. Only customers who have an extreme opinion about a product (i.e. very positive/negative), write a review about it. The moderate middle segment tends to remain lamentable underrepresented.

 

Therefore, the Net Promoter Score (NPS) is a much more representative metric in order to determine Customer Satisfaction. It simply involves asking customers on a scale from zero to ten how likely they are to recommend the product/service to a friend/colleague. Customers are then segmented into three groups: Promoters (score 9-10), Passives (score 7-8), and Detractors (0-6).

 

The NPS is subsequently calculated by subtracting the percentage of Detractors from the percentage of Promoters. Since word of mouth advertisement is to date the most effective means of advertisement, having a high NPS is fundamental to growing sales and evaluating Customer Satisfaction. Again, one compares the NPS before and after the introduction of a digital solution in order to evaluate the impact it had.

 

In a B2B-context, however, it is often less feasible to determine a product’s NPS since the number of customers tends to be smaller than in a B2C-context. Instead, the size of the sale is significantly higher. Therefore, a better metric to determine Customer Satisfaction/Retention is monthly recurring revenue (MRR). It is the sum of all revenue streams that are likely to be generated on a continuous basis for a specific period of time.

 

Here, one would consider the trend that can be observed over a prolonged period of time. If the MRR is decreasing, it is very likely that Customer Retention is low, while it is probable that it is stable if the MRR is moving sideways. Accordingly, a positive trend of the MRR can imply that customers’ expectations are met and that they are very satisfied with the product/service they are receiving.

What are you doing to keep your customers?

In the end, Customer Satisfaction is often a very welcomed side-effect of digital solutions. Nonetheless, Customer Satisfaction and its enhancement can also be the very focal point of a digital product. In any case, keeping your customers for as long as possible is fundamental to a smoothly running business; regardless of the industry its in.

Value Creation with Digital Products and Services: Digital Value Canvas Part 1: Inner Ring

A new concept to map and design value creation from digital initiatives

Most, if not all established companies across all industries are currently busy developing digital products and services. However, questions regarding the actual value created with these endeavors become louder and the need for a “Return On Digital Investment” (RODI) becomes stronger.

While working with companies on their digital business models, we often experienced that these solutions are solely rated by their potential direct revenues or cost reductions. Nonetheless benefits often arise from the less tangible benefits that these digital solutions offer. Excubate’s Digital Value Canvas offers a simple framework to quantify both the direct and indirect value dimensions of digital solutions.

 

The framework was initially introduced in an article authored by Excubate founding partner Markus Anding. Now we will explore the individual dimensions in more detail and establish a structured approach for the assessment of digital products in the field. Over the course of three blog posts, we will cover the three rings of the Digital Value Canvas.

In this post we will address the inner ring: direct commercial benefits.

The prevalent approach to product value evaluation

The inner ring is the core of the framework and easily quantifiable, in contrast to the less tangible outer rings. Most commonly, it is the starting point of classical product value evaluation, thus new digital products are usually first measured along this dimension.

Direct, commercial benefits are based on hard facts which thus depend little on opinions. They are therefore ideal indications for the tangible value of products as they are particularly “close to the money”. Direct revenue generation can be achieved through e.g. selling digital products for a fee, while internal cost reductions are enabled through e.g. providing remote assistance to far-away customers in order to cut down travel expenses.

The apparent dilemma of modern companies

In today’s economic climate companies experience a dilemma: According to a recent study, nearly three out of four economists estimate a new recession will hit before the end of 2021. The risk of an economic downturn forces companies to focus on profitable endeavors and cost reduction. At the same time, they must innovate and build digital business models to survive in the long run (click here to read about Excubate’s study “Innovating through the Downturn”).

However, the development of digital products is cost intense. Therefore, realizing direct revenues or cost reductions seems to be the most comfortable way to pursue innovation despite the economic downturn. This is also in line with classical product strategies, which assume that successful products finance themselves in the long run. Through regular and direct cash flows, or less commonly through the streamlining of operations, products prove their value.

Clarity regarding revenue and cost saving potentials is therefore a critical success factor in the management of digital products. In our experience companies often make the mistake to evaluate the business perspective after completing the digital product’s development. Nonetheless, it is of utmost importance to initiate the business impact calculation as early as possible, ideally already in the product’s validation phase.

Easy to measure, often nonexistent?

Direct revenues are all revenues that occur from selling the digital solution itself in any form. Direct cost reductions occur when the digital solution directly replaces a formerly, more cost intensive way of doing things. Both value drivers are KPIs in themselves, simply monitored through the fully developed solution’s direct performance. Yet in early stages (i.e. before the product development is completed) these KPIs can only be estimated. This time-consuming estimation process requires internal knowledge provided by relevant BUs. Insights from use cases and theoretical market knowledge support the process.

It leads to a clear understanding of the business potentials and enables early decisions concerning the products future. It is for that reason, that an early business potential analyses is indispensable.

 

Of course, from a classical management perspective these insights are not new. Direct revenues and cost reduction directly improve a company’s operational results. Nonetheless, experience shows that the majority of digital solutions in corporates generate value beyond these well discernible dimensions.

 

It is time to have a closer and more open-minded look into digital value generation, by exploring the middle and outer ring of the Digital Value Canvas. We will address them in our next blog post.

Start today with the value evaluation of your digital solutions!

If asked today, could you state if your digital initiative provides direct commercial benefits to your organization? If the answer is “no”, you might want to read our next blog post in which we will cover more levels on which your product might be creating value for you.