The typical middle-market firm is awash in metrics. But metrics don’t equate to the ability to manage to important goals. For this, a 30-page dashboard isn’t the answer. Neither are no-code, low-code, and/or machine learning solutions…
In our experience deploying actionable business intelligence, we’ve found there is no substitute for appropriate conceptualization of the issues and the collective tenacity to overcome the last-mile problem. Organizations that work through these challenges can convert metrics into management tools capable of driving immense long-term value.
Background
Metrics go hand-in-hand with more data and the ever-increasing number of data manipulation and visualization (BI) tools. New tools and tech are making data mining and metric creation easier than ever. This continues to drive metric overload, a longstanding and common problem.
Some “solutions” on the market claim to be able to help. Take, for example, Amazon Lookout for Metrics, which we discuss in detail here. In short, it’s a new SaaS offering that makes machine learning-enabled anomaly detection algorithms accessible to users of Amazon Web Services and key third-party business tools. Amazon pitches the tool to consumers of metrics, essentially arguing that metrics-of-metrics can solve the metric overload problem. And it’s tempting. After all, if AI-powered tech can drive cars, surely it can make for a powerful management tool.
The bigger picture
Metrics should help managers get a handle on otherwise-overwhelming amounts of data. So if you’ve got too many metrics, you’re already not doing it right, and creating metrics-of-metrics isn’t the solution.
We have seen and believe in the huge potential of AI. In fact, we’ve helped a number of clients put it into action. But there is no algorithm — no autopilot — for management.
So many organizations overmeasure, mismeasure, fail to update, and continue to have unmet need for actionable information despite available metrics. That’s because doing metrics right is hard. Metrics alone aren’t the answer. Metrics, and the tools that display them, need to be built with purpose.
That purpose is a theory of your organization and its potential. That theory, in turn, generates questions that are answerable, with answers that are actionable:
What should output, costs, and productivity be?
What is it costing us to operate below potential?
Where are we falling short of potential and why?
What are the ROIs for potential solutions to these issues?
What’s so hard about that?
Generating a theory about what the organization is and could be requires true partnership and coordination among all involved. It requires a shared vision for how to create value – for how to get from Point A to B. And this, in turn, requires sustained participation and persistence to the bitter end. Here, communication, culture, ingenuity, and sheer willpower are bigger hurdles than technical skills.
Creating these conditions requires more than just spending money on a solution. But done right, metrics built with purpose can create immense value.