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Corporate Innovation Metrics

Roberto Aiello and Luke Scheidler

As compared to standard product development projects, corporate innovation projects follow fundamentally different approaches and have different goals — they also require different metrics for tracking progress. Progress tracking of standard product development projects is a well-studied and documented problem. Many tools and processes have been developed and are available for program management, where speed of execution and predictability are the main goals. These tools do not often work well for innovation projects, and yet, there are a lack of established metrics and associated tools for tracking innovation projects.

Itron Idea Labs (IIL) is a corporate business incubator (1). Its objective is to identify and develop new businesses in emerging and high growth markets. IIL has been designed to embrace change in the energy and water industries and to address the need to innovate, resulting in industry-leading new products and services. We adopted an entrepreneurial approach with many operational characteristics common to startups, including lean startup methodologies, high speed and a variety of other tactics to accelerate innovation efficiently. The majority of our work is based on internal product development, from concept to market release.

This paper describes some of the principles and the tools we developed to track our innovation projects and introduces “risk” as our primary metric for tracking projects. It also includes some results from our experience. We believe they are applicable to both corporate and startup environments. We will be sharing our project risk tracking tool as a web app for others and encourage a discussion of its effectiveness.

Nine out of 10 Fortune 500 companies in 1955 disappeared from the list by 2016. The average tenure of a Fortune 500 company decreased from 33 years in 1965 to 18 years in 2012 — and it’s forecasted to shrink to 14 years by 2026 (2). The accelerating rate of technology development and disruptive innovation are the key drivers of this trend.

Because so many aspects of business are now deeply rooted in technology, the trend toward faster computers, larger data storage, faster networks, and smaller devices is changing the rules of business. Technology is also leading to regulatory and market changes in many industries. This is all fueling change in how new businesses affects — and threatens — incumbents.

New directions in the creation of business models are following this wave of change. We see more adoption of staff-on-demand, application of community and crowd sourcing, use of algorithms instead of human decisions, outsourced non-critical functions, and leveraged assets versus abundance of available assets.

In the last several decades, many companies have attempted to unlock the key to organic growth and, especially, disruptive innovation — but few have succeeded. We believe some of the problems relate to how innovation projects are managed and tracked. Innovation projects are different from product development projects. They are characterized by risk management rather than predictability and therefore require different tools.

A way to characterize corporate innovation is with the three horizons model (3) that describes innovation occurring on three time horizons:

Each horizon requires different focus, management, tools, and goals. Horizon 1 applies to a mature business. It’s where the company’s core expertise lies. This is characterized by well-developed products that solve well-understood problems for existing customers. These are profitable businesses in which product managers understand their customers and their needs. Due to this clarity, marketing-requirement documents can be written. Such documents most often present updates about existing products. New features are added that show incremental improvements to the products. Work in Horizon 1 is centered around the products. For example, the first aspect a product manager usually worries about when introducing a new product in a mature business is the cost of that product. That’s because the new product will solve the same problems the previous product does for an existing customer and with the same revenue model.

The case is different in Horizon 3, where a new business is characterized by unknowns.

Innovation projects fall within Horizon 3. These projects’ purpose is to search for new business models, not to execute existing business models (4). A new business is characterized by unknowns. The first two key unknowns are: who the new customers are and what problem we are solving for those customers. When a new business is created, it should solve a new problem for a customer, address needs of a new customer or utilize a new revenue model.

Each innovation project is typically run by a small cross functional multi-disciplinary team, and its goal is to achieve product market fit, not to achieve planned milestones and targets (5). The strategy is to achieve radical or disruptive innovation and new business model innovation, not incremental innovation or optimizing existing business models. The goals are to create new markets or to discover new opportunities within existing or adjacent markets — not to maximize yield from a captured market or to outperform competitors.

Given all that, it is obvious that these projects must be evaluated with different metrics from the ones utilized in Horizon 1 projects. What’s surprising is that there isn’t an accepted way to evaluate them.

Since the main objective is to determine product market fit and to validate the business model, a more appropriate evaluation can be based on metrics such risk and uncertainty, opportunity size, learning velocity, technology availability, time spent on the project, and cost. While there are numerous metrics that may be relevant when evaluating Horizon 3 businesses, tracking a wide variety of project types across multiple metrics is problematic. It can become difficult to compare the relative progress of different projects on a relatively equal, objective footing. Instead, we choose to focus on a single metric: risk.

The main purpose of a Horizon 3 project is to reduce its risk. This is a well-known fact for startup company founders and venture capitalists. We propose to use risk as a single metric, and to calculate it based on the business model’s evaluation. Risk will be tracked over time to evaluate the project’s progress.

We use the business model canvas (6) to describe the business model. Each section describes a component of the business model (Figure 2).

We further divide it in three sections (7; 8):

We separately assess risk for each section and then average the risks to a total. That total gives a metric of the project’s evaluation.

The various parameters for risk evaluation are shown in Table 1, where the column on the left shows the parameter and the one on the right describes the questions we need to answer.

Table 1. Parameters related to the business model canvas.

Each parameter in Table 1 is assigned a risk, from very high [4] to very low [0], based on the project’s current status, and the risk is estimated periodically. The values related to desirability, feasibility and viability are calculated separately as the average of the scores in that section. The total risk value is calculated as the average of the three section scores.

In addition to the typical components of the business model canvas, we have added additional parameters to each section including: Product/Market Fit, Market Size, Development, and Competition. These parameters have been added based on IIL experience with factors contributing to project risk but that are not explicitly in the business model canvas.

The desirability section has the most questions because we want to prioritize it compared to the feasibility and viability sections, and more questions make it harder to reduce the desirability risk. The desirability section is prioritized because until a specific customer and value proposition are validated — and there is an effective channel to reach those customers, the business is still high risk by definition.

It is equally important to validate all sections and to track all elements carefully over time. For instance, we have had projects fail because we were not tracking market changes and the associated changes in our planned partner network closely enough. A project can fail due to high risk in any element of the business model canvas.

Without deep knowledge of the customer and their problem, any assessment one might make regarding the feasibility or viability of the project are still just assumptions. It is easy to believe that feasibility and viability risks are being reduced by having productive partner meetings, defining product requirements, and building complicated revenue and cost models. We recommend keeping this in mind as total project risk is tracked. If the desirability assessment is not the lowest area of risk, then assessments of feasibility, viability, and total project risk should be viewed as potentially biased.

In order to objectively evaluate desirability, feasibility, and viability risks in Table 1, we use a multiple-choice questionnaire (9; 10; 11). This provides discrete examples and helps to remove some subjectivity from the risk assessment. The multiple-choice options provide the additional advantage that we can see what the next step should be to further reduce risk.

While the tool is relevant to new businesses of all types, the options were designed to be most applicable to corporate innovation. Any company using this tool to track their own projects over time may find value from customizing some elements of the questionnaire. The multiple-choice options for the customer segment and value proposition sections of the assessment tool are shown in Table 2 below. The remainder can be found in the Appendix.

Table 2. Risk quantification example: Customer Segment and Value Proposition

Results from Itron Idea Labs’ projects in 2019 are shown in Figure 3. Each project was tracked at periodic intervals. The curves are not normalized in time as the various projects started at different times. The risk reduction curves follow the expected behavior. All projects reduced their risk, some faster than others.

Figure 3. Risk tracking of projects in 2019

We started tracking projects with the first version of this tool in late 2018. We still don’t have enough experience to assign a meaning to absolute risk values, however we can draw some early observations.

Projects Galaxy, Cursus, Itron Pay, Flow, and Home Sweet Home never left the very high or high-risk zones and were all successfully killed. The projects that were killed fastest were those in which we were able quickly identify and talk to the customer that had the problem. Cursus, for instance, appeared to be a large problem from an end-customer perspective. However, when we were able to speak with the B2B business provider that had to pay to solve that end-customer problem, it turned out to be a small line item in their overall budget. We were able to kill these projects prior to ever developing an MVP.

Projects Coeus, Refresh and Prophecy are in the low-risk zone, and they are all in MVP stage. Project Diamond also entered the MVP stage despite relatively high risk. Sometimes we find that when we are having repeated customer conversations about their problem, but we don’t yet know all the requirements or the exact revenue model, building a basic MVP can help further reduce risk and push stagnant customer engagement forward.

Looking a little deeper, Figure 4 shows the risk evaluations over time for two IIL projects in 2019. Both projects have a similar overall risk profile, but the component risk scores are quite different. Project Diamond was focused on reducing the carbon intensity of electric vehicle charging using distributed ledger technology (e.g. blockchain) to track the real-time carbon intensity of the electricity used for charging. We identified a customer that was interested in the technology and wanted to pilot the solution via an emerging technologies grant program. Accordingly, the desirability risk score drops more quickly than other scores. However, the feasibility and viability scores remained higher because distributed ledgers were nascent technology in 2019 and regulations, markets, and the technology itself were all still developing. Ultimately, the project was killed even though the MVP design met the customer needs. It was based on an emerging market need and an emerging technology and was over-engineered for the value it created in current markets. We were only able to accurately assess the viability of the project and kill it because we understood the specific problems we were solving for the customer and their motivations for doing so.

Project Refresh is an example of where viability risk dropped more rapidly than feasibility. We identified multiple customers with the same problem. We talked to the teams that had the problems and had a good understanding of how much their problem was costing them. Based on customer meetings, we were able to develop a basic prototype MVP and a revenue model that looked good. We thought we were reducing both feasibility and viability risks. Upon going back to the customer with our prototype, we could not get anyone to do even a very low-cost pilot. The main factor that came into play was that the solution required institutional change for large businesses and for the ultimate decision-makers (not the teams that had the problem), it wasn’t the “hair on fire” problem it first seemed. Still, the MVP helped us identify and push the conversation up to the actual decision maker, who helped us better assess viability.

Both examples show how important it is to view all of the risk scores relative to the others. Any risk factor can cause a project to fail. That said, desirability should be the leading indicator. If we had spent more time upfront on customer development for Project Refresh and had talked to the actual decision-makers, we would have known that our viability risk assessments were artificially low.

We are expecting that a project’s evaluation will be very low risk when the business model is validated and ready to scale. As we continue to track our projects and gather data, we will explore the trends that lead to rapid risk reduction and successful projects.

Innovation projects are different from product development projects, they should be assessed based on risk rather than predictability. This paper presents a methodology to assess risk for innovation projects and provides a webapp that utilizes these methods to assess and track project risk over time. It includes an objective evaluation of the various aspects of business model development and some results from Itron Idea Labs’ experience.

In addition to recommending risk as an objective and standardized metric for tracking innovation project progress, we make the additional following recommendations for new business model development based on IIL experience:

· It is important to reduce risk across the three elements of the business model canvas — desirability, feasibility, and viability — but we recommend focusing on desirability, especially customer segment and value proposition. If one does not have deep knowledge of their customer and their problem, then many assessments one might make regarding the feasibility or viability of the project are likely to still be assumptions.

· When working in a corporate innovation environment, it is important to pay attention to project risk when determining when to transition a project to a primary business unit. If the risk level is not low enough, the business may not be ready to thrive under traditional business unit processes. In our experience the most important factors in a successful transition are: 1) How far has the MVP evolved? Is it an immediately scalable product or does it need additional development, integration, or marketing? 2) How much revenue is the business already generating?

We will continue to track our progress using the Risk Assessment Tool and draw additional insights as we gather more data. A few key themes we plan to examine include:

· Is risk an appropriate single metric for tracking innovation projects? Are more metrics needed? For what purposes?

· At what risk level is there demand from the corporation’s business line owners to transition projects to a primary business line? How fast do the businesses grow after the transition? Is this related to the risk level at which they transitioned?

· Should the desirability risk metric carry more weight than the other metrics? Do projects that have better desirability risk scores progress more rapidly or have greater success?

· At what risk level are MVPs built? Are they built specifically to reduce certain risk factors? Are there specific risk factors that MVPs are effective tools for improving?

We encourage the innovation and entrepreneurial community to use the Risk Assessment Tool and provide their own insights and feedback.

1. Aiello, Roberto. Innovation for Survival. Kindle Edition 2019.

2. Perry, Mark J. AEIdeas Blog. [Online] December 16, 2016.

3. Baghai, M, Coley, S and White, D. The Alchemy of Growth. 1999.

4. Blank, Steve. Lean Innovation Management — Making Corporate Innovation Work. [Online] June 26, 2015.

5. O’Reilly, Barry, Molesky, Joanne and Humble, Jez. Lean Enterprise, How High Performance Operations Innovate at Scale. 2014.

6. Osterwalder, Alexander and Pigneur, Yves. Business Model Generation: A Handbook for Visionaries, Game Changers, and Challengers. 2010.

7. Osterwalder, Alexander. How To Systematically Reduce The Risk & Uncertainty Of New Ideas. Strategizer Blog. [Online] December 5, 2017.

8. — . The 4 KPIs to Track In Innovation Accounting. Strategizer Blog. [Online] May 16, 2018.

9. Polovets, Leo. How to De-Risk a Startup. Coding VC. [Online] October 27, 2016.

10. Nathan, Adam. Business Model Canvas — Integrating KPIs. The Bartlett System. [Online] October 24, 2018.

11. Smith, Josh. Lower your startup risk with this template. Code Corps. [Online] November 2, 2016.

Appendix

1) Tables A-1, A-2, and A-3 provide the complete set of multiple-choice options IIL uses to assess project risk.

From Filipino White Supremacy to Black Lives Matter

Corporate Innovation Metrics

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