How to pick the right innovation metrics and stay on track

If you’re at the stage in your innovation process where you’re putting together innovation metrics, you may be struggling with the following challenges in your innovation process:

• Your innovation is stalling somewhere in your innovation funnel, but you can’t identify where or why.
• Your innovation team is not accountable and is struggling to prove its results and return on investment.
• You’re doing “innovation theatre”, where you’re going through the motions, but not actually innovating at all.
• You’re unable to get buy-in for your innovation efforts from your stakeholders.

Successful and innovative companies use innovation metrics to help understand their performance, make improvements, and track the progress of their innovation programme. However, it can be really hard to figure out the right metrics to track—particularly since innovation is so intangible and can take such a long time to work. 

At Tenity, we help financial corporates such as UBS and SIX with innovation, by enabling them to learn about, collaborate with, and invest in startups. 

Personally, I’ve worked in innovation management for decades, most recently as an innovation strategist for Credit Suisse. I now work as a Partner Innovation Lead at Tenity, so I have hands-on experience of the entire innovation lifecycle.

In this article, I explain the Key Performance Indicators (KPIs) you need to measure and show you how we track innovation at Tenity. I’ll cover:

• What are the best innovation metrics to track?
• How we help corporates measure innovation at Tenity
• How Julius Baer used learning indicators to track the success of their innovation

Note: are you a corporate interested in learning more about innovation? Reach out to us to learn more about how we can help you.

What are the best innovation metrics to track?

If you search for innovation metrics online, most results you’ll find will help you measure your business’s overall innovation performance. 

You’ll learn metrics such as the “innovation rate”, which tracks the commercial success of your newest products on the market. Or your “innovation ratio”, which measures the number of innovations compared to your entire product range. 

Of course, tracking this type of information can be useful. However, these metrics are typically a measure of how a number of new products perform post-launch. What they don’t do is give you a concrete sense of how your internal innovation process—i.e. how you innovate new products—is performing.

Instead, if you want to track the success of your innovation funnel, you want to use a set of metrics throughout your entire innovation funnel, from market exploration to ideation and through to product launch. Used in this way, the right types of innovation KPIs can help you to:

• Understand how every stage of the innovation lifecycle performs, including where ideas come from and where they tend to fail.
• Build confidence in a product through the process of innovation, from exploration to validation.
• Avoid continuing to invest in developing products that are unfeasible or won’t attract enough new customers.
• Know that your innovation teams are mobilised and accountable.
• Report your successes to your sponsors and stakeholders. 

As such, the most important KPIs for innovation are those that help make your innovation funnel more rigorous and structured. Rather than directionless “innovation theatre”, these metrics will help you develop a system that reliably produces feasible products. 

The best 3 types of metrics to use in your innovation process

The ideal innovation metrics measure 3 central characteristics of your innovation funnel, depending on the maturity of your programme:

• The number of ideas that make it through the funnel. How many problems does your innovation funnel identify? How many solution ideas does it produce? And where do these ideas typically come from—accelerators or your internal innovation team? Further, you’ll want to measure how many experiments you have performed, as well as how many product ideas get to the validation stage.
  
  
• The quality of your ideas. How many insights do you create when you perform a disruptive innovation experiment—i.e. a survey, prototyping workshop, or product test? This is an important measure of the maturity of your innovation team, plus how well they know the industry and product environment.
  
  
• The velocity with which ideas pass through the funnel. Generally, you’ll want to measure how long it takes to get you from ideation to validation, as this is an indicator of your products’ lead time. But other aspects of your velocity include the number of experiments you can perform in a certain time, plus the speed with which developers can build the products themselves.
  

Together, these considerations help you track the ideas that your innovation initiatives are producing. They’re fundamental to the way we measure the success of innovation programmes at Tenity. 

Deciding on the best innovation metrics is really context and situation-dependent. So, the easiest way to talk about them is to explain how we usually approach it at Tenity.

How we help corporates measure innovation success at Tenity

At Tenity, we support finance corporates, such as UBS, SIX, and Klaytn, to innovate through startup accelerator programmes. In any programme we run—whether it’s our own accelerators we hold twice a year, or the custom programmes we organise for corporates—we use the same methodology to measure successful innovation.

That methodology follows a four-stage process. In each stage, there are specific metrics that enable us to measure the quantity and quality of ideas, as well as the speed of the innovation process. These metrics can be broken down into key success factor questions, learning indicators, and performance metrics:

• Key success factor questions. These are the questions you need to have an answer to before you can move on to the next stage of the innovation process.
• Learning indicators are concrete milestones you need to meet in that stage to ensure you’ve followed the right process.
• Performance indicators. The speed, quality, or cost with which these indicators are met.

If at any point you don’t meet the learning indicators in each stage, you have to return to the drawing board. This allows you to not waste resources on unfeasible products. 

In this section, I talk you through each stage in our innovation process one by one and show you relevant KPIs we use at each stage.

1. Discovery: Understanding the problem space

In the early stages stage of Tenity’s innovation funnel, we help corporates understand their innovation needs and study new market trends to see how they fit. 

This always starts from the problem space, by asking the question: what problem can we solve as a corporate? The different metrics and key success factor questions we use in this stage measure the corporate’s ability to provide an answer to this question. 

Key success factor questions

The key success factor questions corporates need to answer at this stage are:

• Who is the customer for the proposed idea?
• What is the problem you are trying to solve?
• How many potential customers are suffering from this problem?
• How is the customer currently having their problem solved?

These help to build a picture of the problem state of the potential customer—including their current pain points, the limitations of their current solution, and the size of the market. 

Learning indicators

The learning indicators that corporates should measure and track include:

• Number of assumptions that you can test in the subsequent experiments
• Number of experiments. At this stage, experiments could be user interviews, surveys, focus groups, or another type of customer research.
• Number of learnings. For example, these learnings could be problem statements identified, or key insights.

As an example, at this stage I would like to see 5 user stakeholder interviews, 2 to 3 problem statements, and 2 or 3 innovation projects. This would give me an idea that a rigorous process is being followed that’s creating concrete opportunities to develop insights. 

Performance metrics

Finally, some performance metrics that corporates should track at this stage—and throughout much of the rest of the entire innovation process—include:

• Experiment efficacy.
• Number of experiments that resulted in intentional learning. It’s an important distinction from the learning indicator above, as it measures the value of those experiments.
• Experiment velocity. How many experiments were completed in a particular time frame?
• Learning velocity. How many learnings did the team obtain in a given time frame?
• Cost per learning. How much did the corporate spend to obtain that learning, in terms of recruiting costs, resources, and full-time equivalent. 

2. Exploration: Matching solutions to customer problems

In the second stage of our methodology, we help corporates create solutions to the problems they’ve identified. During accelerator programmes, this can often involve working with startups and other innovators, but it can also happen in-house.

Ultimately, this stage is about understanding the willingness of customers to adopt the solutions you’re proposing. As such, the questions and KPIs at this stage help you to gain confidence that the solutions you’re taking forward will actually satisfy your customers. 

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Key success factor questions

At this stage, you want to ensure that there’s a market out there for your product. To establish this, the key questions to ask include:

• Does the potential customer want to have a problem solved? 
• How do the customers want to have the problem solved?
• Does the customer accept the value proposition?
• Who are you competing with to solve the customer’s problem?

If you don’t receive satisfactory answers at this stage—for instance, if customers don’t accept the value proposition—then it may be that your product is not viable. While that might be disappointing, it’s important to establish this now before you build the product further.

Learning indicators

In this Exploration stage, the learning indicators are similar to the first phase. However, the types of experiments you perform and learnings you gain will differ:

• Number of experiments. Here, experiments will include ideation workshops, prototyping workshops, and user testing sessions. 
• Number of learnings. These could include the number of high priority ideas, the number of prototypes, the number of critical functions, and the number of user insights.

Corporates can set their own goals for the number of learnings and innovation activities they produce. But as an example, I would like to see 1 or 2 prototypes, as well as 5 to 6 user tests per prototype, at this stage. 

Performance metrics

Throughout this second stage, corporates typically use the same performance metrics as in the Discovery stage.

3. Viability: Establishing what customers are willing to pay for

The third stage—Viability—is when corporates validate their solution as a product that customers are willing to pay for. It’s when corporates establish how their concept can be monetized, via what sorts of revenue streams, and for how much. 

Like the previous stage, Viability adds an additional level of confidence to your product innovation investment. Not all products that you have conceptualised in previous stages will make it through to this stage—and that’s for the best. You should be carrying forward only the most promising and most viable product ideas. 

Key success factor questions

Again, this stage is about understanding whether your solution can be commercialised as a product. That means you’ll need to ask the following questions. 

• Are customers willing to pay to have their problem solved?
• If so, how do they want to pay? i.e. via what revenue stream?
• How much are customers willing to pay?
• What is the best channel to deliver the value proposition?
• Is there early evidence that you can build the solution?

Of course, if in your research you find that customers are not willing to pay for this solution, you won’t be able to take the product forward into the next stage. 

Learning indicators

The kinds of experiments you undertake and the learnings you gather will be specific to this stage. However, keeping track of the number and quality of experiments you perform is crucial:

• Number of experiments. These can be user testing sessions, advertisements, landing pages, waiting lists, or pre-sales.
• Number of learnings—for instance, the number of sign-ups, feedback received, and conversations with potential customers.

In my experience, I would like to see at least one sign-up from a business that’s interested in the product, as well as a further 1 or 2 leads at this stage. 

Performance metrics

The same performance metrics can be used in this phase as in the previous phases. 

4. Growth: Validating the scalability of the solution

In the final stage of the innovation funnel, the corporate needs to validate whether they can build and scale the solution in question. It might be the final step before product launch, but even at this stage you can find that the product won’t be commercially viable. That means that KPIs and success questions are still very relevant. 

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Key success factor questions

The questions that you’ll need to answer at this stage include:

• Can the business model (that you’ve identified in stage 3) be scaled?
• Does it make sense to scale the business model?
• Is the business model going to be ethically and legally compliant at scale?
• Can the channel of business model sustain the scale?

Learning indicators

Once more, the types of experiments and learnings are specific to this stage:

• Experiments. For example, here you can track the interest in your beta or soft launch, or your minimum viable product (MVP) experiment.
• Learnings. At this stage, it’s useful to track metrics typically associated with customer acquisition and retention—such as marketing reach, sign ups, and more. 

Performance metrics

While in other stages you’ll have used the same performance metrics, there are specific output metrics that are relevant to the Growth stage. This is due to the fact that it’s no longer just research and ideation that’s involved—but actual product development. 

These include:

• Sprint velocity, meaning the amount of work that the development team can perform in a given time
• Sprint burndown, or number of story points completed during the course of a sprint.
• Lead time, namely the period between request for delivery and actual delivery.
• Learning velocity. This will typically slow down, as the feedback loop in this phase grows in length. That’s because you’re no longer conducting direct customer interviews, for instance, but engaging leads through the acquisition funnel.
• Cost per learning. The cost of learning is expected to increase, due to increased development time.

How Julius Baer used learning indicators to track the success of their innovation

At Tenity, we follow this process in both our own accelerator events and the programmes we build for corporates such as SIX and UBS. 

For instance, we have been working with the wealth management bank, Julius Baer, for a number of years on their innovation strategy and execution. Recently, they came to us for support in establishing an accelerator programme to help them develop innovative solutions in the Web 3.0 space. 

From August to November 2023, we ran a collaboration programme with Julius Baer and startups working on problems related to Web 3.0. Its focus was on fast exploration and experimentation, to gain unique insights into solutions for problems of distribution, the metaverse, and client experience. 

Throughout this process, we followed specific milestones—including proofs of concept (POCs)—to measure success at each step of the process.

Learn more about the accelerator here: Julius Baer Global Web 3.0 Program

You can read more about the various corporates we’ve supported here:

• Isle of Man’s 12 Week Program focused on insurtech
• Klaytn’s Incubation program focused on blockchain

Make your innovation process more robust and accountable with the right innovation metrics 

The right innovation metrics and KPIs enable you to create products that are viable, evidence-based, and that solve your customers’ problems. 

The wrong ones can send you in the wrong direction chasing input metrics that don’t actually help with innovation. That’s why it’s important to track metrics that you can use throughout your innovation program, as well as afterwards. 

At Tenity, we can support your corporate’s innovation by enabling you to learn about, collaborate with, and invest in startups via our custom innovation programs.

To learn more about Tenity and how we can help you with your innovation, reach out to us.