Creating the One Metric That Matters for Innovation Leaders

Few things were better than ripping open a baseball card pack as a kid. You’d flip each card over and size up specific player stats: homers, RBIs, batting average, ERA, wins, saves. Those metrics told you everything you needed. Or so you thought. Nowadays, you could drown in all the acronyms of advanced metrics: wRC+, wOBA, FIP, PRV, DRA. It all can feel like a calculus exam. Thankfully, the nerds (erm, "sabermatricians") also came up with WAR: wins over replacement. In a nutshell, WAR is one number meant to express a player’s overall impact on the most important stat of all: winning baseball games. 

In enterprise innovation, cookie-cutter innovation KPIs can provide a false sense of security while ignoring the actual factors that indicate growth potential. Strategic objectives don’t just need to be measurable. They have to be measured on what matters most.

This is why it’s essential to find that key metric that helps assess your organization’s current position against its long-term goals. Innovation enterprises need to identify their One Metric That Matters (OMM), and that OMM must be tailored to their unique goals, risks, and markets.

Committing to an OMM gives organizations real-time clarity on their progress toward a goal, reducing the time spent interpreting this information from unrelated, unhelpful data. And it’s played a major part in the historic success of major organizations.

When Walmart needed to fix supply chain and inventory issues, they formalized and introduced On-Time, In-Full (OTIF) as their OMM. This metric helped them hold suppliers accountable, improved inventory management, and reduced the frequency of late deliveries by tracking the percentage of orders delivered to the correct location, in full, and within a specified timeframe. It was so successful that they implemented OTIF at Sam’s Club too, and even other companies (including Amazon and Target!) have adopted it.

When Airbnb needed a clear metric to guide their decisions, they selected an OMM too: “nights booked.” By measuring not only the number of bookings but also the total number of nights guests stayed in their accommodations, they were able to gain a clear picture of both host monetization and guest satisfaction, better reflecting the platform’s value as a two-sided marketplace.

OMMs like these provide a sense of clarity that you can’t get from other data points. When you need real-time transparency on your progress toward a specific objective and broad consensus on what it takes to get there, you need an OMM.

Enterprise innovation requires that same sort of clarity.

Enterprise Innovation Needs a Certainty-Based OMM

Enterprises relying on innovation for growth are often drowning in data but starving for certainty. And while progress-oriented metrics are crucial, they’re not helpful for revenue-focused goals. They tell you how well the vehicle is running, but they don’t tell you whether it will get you to your destination.

Innovation leaders desperately need a metric that answers the enterprise’s most pressing question:
“Will our actions today lead us to our strategic targets tomorrow?”

This is the certainty innovation enterprises desperately need, and it can’t be addressed by typical innovation KPIs. You can have 100% visibility of your NPD activities and no idea whether or not those new products will perform in the market. You can have a perfectly optimized production pipeline and still fail to move the needle toward your highest objectives.

When push comes to shove, the innovation metric that truly matters is the one that gives you certainty around your ability to hit targets and fill revenue gaps.

The Anatomy of a Predictive OMM: Three Essential Sources

To calculate this certainty, you have to stop treating innovation like a series of isolated, disconnected projects. You need to commit to a philosophy of growth innovation, which sets growth as the single most important innovation outcome, and manage every step of the innovation process accordingly.

The growth innovation philosophy treats the entire innovation portfolio as a single business case. To increase the likelihood that your entire portfolio will deliver on its potential, you need an OMM that aggregates data in a similarly comprehensive manner.

As you can see from the diagram below, a truly predictive OMM is built on a comparison of two distinct future states: your targeted future state and your projected future state.

The targeted future state is your destination. It’s made up of the strategic objectives and revenue targets your organization needs to hit.

The projected future state represents your current trajectory. This is where you’re actually headed based on your current and planned work.

Comparing Your Target Future State Against Your Projection

Contrasting these two states should provide clarity to any innovation leader. The comparison should reveal one of three scenarios:

• Surplus: Your current momentum and planned roadmap are more than enough to hit your targets. This gives you some breathing room and allows you to take bigger risks or optimize your processes for greater efficiency.
• Alignment: You are on track to hit your goals. Keep in mind that there is some inherent risk here because it only takes one failure to take you out of alignment.
• Growth gap: The most important (and probably the most common) outcome is a realization that, even if you execute your current portfolio perfectly, you will still fall short of your strategic goals. Identifying this gap early offers a strategic advantage and is much better than finding out too late.

The comparison of these two states (projected vs. target) gives innovation a sense of certainty, and brings the diagnostic clarity needed for a true enterprise innovation OMM. 

A note on scale: While these scenarios represent the broad strokes of this methodology, no two enterprises are alike. For many organizations, the OMM may actually look like a collection of similar comparisons. You might run separate projected vs. target analyses for individual product lines, specific revenue streams, or independent business units. The power of the OMM architecture is that it allows these diverse signals to be compiled into a unified picture of the organization’s growth potential.

Identifying Your Projected Future State

Your targeted future state is set by leadership, the projected future state must be calculated using three essential sources of data.

Once you have this data, you identify your projected future state by:

• Aggregating the total projected value of the projects in your active pipeline (present state) and the projects on your roadmap (planned activities). This number should reflect a perfect-world scenario in which every project finishes on time and on budget, hitting every target.
• Take that theoretical value and multiply it by your historical realization rate. If your historical data shows that you tend to only realize 70% of a project’s promised value, you should discount your projected value by 30%.

You can think of this calculation as your minimum viable OMM. Your accuracy will sharpen as your data architecture matures. Eventually you can move beyond flat averages and begin applying segmented realization rates based on project types. The more granular your data, the more high-resolution your OMM becomes.

Building a Bespoke OMM for Innovation Orgs

One thing that all enterprises have in common is that they’re unique. Each one has specific governance structures, risk tolerances, market considerations, and internal processes. The OMM necessary to provide the kind of certainty you need can’t be borrowed from another organization.

If you want to start building a predictive OMM for your organization, there are a few actions you’ll need to take:

1. Begin Aggregating Your Data

A predictive OMM is only as reliable as the data that fuels it. To move beyond lagging or subjective indicators, you need to start by centralizing your historical, current, and planned data into a single, accessible platform today. This is the raw material you’ll use to calculate your current trajectory and identify strategic gaps.
You shouldn’t wait for perfect or complete data to begin. Start with the data you have today. Capturing an exhaustive view of your current state is how you build the comprehensive historical evidence necessary to enhance tomorrow’s predictions.

2. Find Patterns in Your Data

Once you start centralizing your data, the interpretation work begins. You’ll need to start looking for patterns that you can apply to your current portfolio. This may be as simple as identifying the typical gap between past estimations and actual outcomes, but you might recognize other patterns like:

• Incremental innovations to core products consistently hit their targets, while breakthrough innovations are consistently overestimated in budget and time-to-market.
• Projects over a certain budget threshold or involving a specific number of cross-functional departments tend to stall for months at a specific stage-gate.
• Horizon 2 projects are consistently delayed or defunded whenever Horizon 1 projects are at risk.

Identifying these patterns is a learning process that helps you see the systemic behaviors impacting your portfolio. Once you identify these factors, you can stop guessing about outcomes and start building a model that reflects the way your business actually operates.

3. Test and Retest Your Hypotheses

At first, the data that goes into building your OMM will be a theory. To turn it into a valuable tool, you will need to test and re-test it against real-world outcomes. The more you compare your actual “projected future states” against what actually happened, the better you’ll be able to fine-tune your formula, shrinking the gap between your prediction and reality.

The Danger of Shortcuts

It may be tempting to skip the rigorous work of data aggregation and regular testing in favor of textbook innovation KPIs. But standard KPIs are designed for reporting, not prognosticating. They lack the institutional context and historical understanding required to accurately project your unique trajectory.

To understand why you can’t skip this step, let’s look at some of the common KPIs enterprises lean on, and why they fail to deliver the certainty a true OMM requires.

Why Other Innovation KPIs Don’t Deliver as OMMs

A lot of enterprise innovation discussion centers on metrics that are disconnected from your actual strategy. Too often, they track project progress while ignoring potential outcomes and the mathematics of actual growth. They likely demonstrate that your organization is extremely busy but fail to determine whether it’s actually succeeding.

To bridge the gap between effort and impact, we have to stop relying on KPIs that were never designed to predict future performance. For instance, consider these metrics that most enterprises lean on but fail to provide the certainty necessary to be a true OMM:

New Product Revenue

This is the ultimate example of a lagging indicator. By the time this number hits your dashboard, the decisions that created it are ancient history. So while it gives you some historical performance data, it tells you absolutely nothing about the potential impact of your current investments or planned activities.

Net Present Value (NPV)

NPV is a dangerous metric because it gives the impression of mathematical certainty. It’s a point-in-time guess based on an assumed scenario. If it were a reliable leading indicator, every project you greenlit would be a massive success. Unfortunately, it examines projects in isolation and doesn’t really account for the entire portfolio or its target future state.

Pipeline Progress

This is a critical metric that tracks activity, but not achievement. As an OMM, it leaves too many questions unanswered. Will they finish on time? Are they on budget? When you get them across the finish line, will they move the needle on your objectives?

The common thread among these KPIs is that they provide ample data to discuss in a meeting, but they don’t address the most pressing, outcome-oriented questions. To close the gap between your innovation efforts and their outcomes, you need a metric that provides clearer insight into potential outcomes.

These Traditional Metrics Don’t Give You the Certainty You Need

Certainty is a rare commodity in innovation, but it’s the only one that matters. And while we accept that certain projects will fail, we need clarity and confidence around whether our portfolio mix will deliver on its objectives. Without this predictive OMM, innovation remains a black box.

Innovation enterprises need to be able to answer the question, “Is the work we’re doing now getting us closer to where we need to be?” An OMM built for growth innovation would answer this question, offering a real-time read on the gap between the current trajectory and the ultimate goal. When a metric can tell the organization that its current portfolio has an 85% probability of meeting its five-year target, innovation becomes a much more predictable discipline.

Lay Your OMM Foundation Today So AI Can Do the Heavy Lifting Tomorrow

Everything we’ve discussed up to this point is the natural territory of artificial intelligence. The time is coming when AI will be deeply involved in increasing certainty around innovation. By beginning to do this work today, you help yourself in two ways:

You Improve Your Ability to Predict Innovation Outcomes

The better you understand your enterprise’s innovation engine, the better you get at forecasting results. As your innovation teams spend time building connections and identifying patterns in your data, they’ll not only be able to create an OMM that increases their certainty, but they’ll also recognize inefficiencies they can fix, signals they need to watch for, and specific levers they can pull to increase the likelihood of success.

You Fuel the Future AI Engine

For AI to recognize patterns in your innovation activities and make accurate predictions, it needs data. The more data you can feed it (and the better organized that data is), the better. Aggregating data today creates the information repository that AI will use in the future.

The companies that wait for these capabilities to be ready before they start organizing their data will find themselves playing catch-up. But those who start today will avoid unnecessary data debt and lay the tracks that AI’s engine will eventually run on.

If you’d like more information on how to prepare for this eventuality, check out “The Inescapable Future of AI in Innovation Management, and How to Prepare for It.”

Build Your OMM in Accolade

Accolade innovation management software provides the architectural foundation for building your OMM. It offers you the hyperconfigurability necessary to generate bespoke entities, categories, and metrics that reflect your specific business. Because Accolade is designed to handle complex data relationships, you can use it to design, test, and adjust your metrics over time.

As you build out your data, Accolade can run calculations in real time, ensuring that every portfolio decision is immediately reflected in your OMM. This data can be applied to custom reports and executive dashboards, demystifying the innovation process and making it easier for leadership to make critical portfolio decisions.

Accolade’s innovation management platform will provide the power, flexibility, and visibility necessary to create, test, and monitor the OMM that will empower data-driven, predictive growth.

Schedule an Accolade demo today.