Common Sense Has No Place in KPIs

“The material means of achieving ends are limited. We have been turned out of Paradise.” -Lionel Robbin

Econ 11

At the beginning of Economics 11 (“11” being Amherst’s course numbering equivalent to “101”), the professor wrote across the top of the chalkboard: “Economics is the study of the efficient allocation of scarce resources.” In the early days of financial planning & analysis (“FP&A”), when the bulk of the finance function still centered around accounting, treasury, and tax, early pioneers sometimes called the burgeoning silo Business Economics. I almost wish that name had stuck.

FP&A is really RP&A

FP&A is really resource planning & analysis, where data is gathered and analysis is performed. That analysis drives the strategy used to deploy those limited resources effectively. When the critical function of FP&A is described in this academic way, the process many organizations use to define key performance indicators (“KPIs”) feels backwards. And that is because it is.

Most articles about KPIs give snippets of very good advice:

• don’t have too many

• make them S.M.A.R.T. (Specific, Measurable, Attainable, Relevant, and establish a clear Time Frame)

• Achieve buy-in with stakeholders

• Review them often

These features for good KPIs are excellent, but they are window dressing—they contribute little to developing KPIs that drive strategic resource allocation. And, the piece of advice that is the chief offender of backwards KPI development? “Ask yourself ‘what is your desired outcome?’” It’s not the most useless question, but it’s close.

On the surface, these intuitions are reasonable. They exude common sense. But, it’s time for stakeholders to realize something: KPIs that matter aren’t determined by people — effective KPIs are revealed by data.

“Common sense is nothing more than a deposit of prejudices laid down by the mind before you reach eighteen.” (Attributed to Albert Einstein)

KPIs and Common Sense

Every company, from pre-revenue startup to behemoth market leader, has a set of KPIs they believe in. It took time and effort to establish them. Each stakeholder at the organization had an opinion about the most important KPIs, and each fought tooth and nail to add theirs to what was likely an already too-long list. For each stakeholder, their favorite KPIs could be driven by many factors. A short list:

• experience (“Sales Growth has always mattered, so we’ll continue measuring ourselves by Sales Growth”),

• philosophy (“I believe in lean startups, so burn rate is king”),

• their lens on the world (the VC is motivated by different outcomes than the Head of Sales),

• the “flavor of the month” KPI (there is a not insignificant number of “listicles” titled with some variation of: “Top X KPIs Every [Content Marketer/VC/Sales Manager/etc.] [Recommends/Needs to Know/Should Measure]”),

• industry (“we’re a SaaS company — it’s all about CAC and MRR for us”),

The KPIs you’d develop from the list above ☝🏾 tell us nothing about the company. We have no idea whether any one of those metrics is in fact a key indicator of performance for this company—how could we? Those metrics, without a careful study of the data first, are just random measurements. Any one of these metrics could be as relevant and indicative of future performance as “height of ceiling of 3rd floor” or “# of employees with J first names.” So how do we get KPIs that are meaningful? How do we get KPIs that actually have a correlation to this business’s performance? We dive head first into the data.

“Most of the world will make decisions by either guessing or using their gut. They will be either lucky or wrong.” -Suhail Doshi

Data-driven KPIs

To coax KPIs into revealing themselves, companies should start by analyzing its “biggests.” An organization’s biggest costs, biggest revenue producers, and biggest non-financial metrics (production hours, etc.) hold the answer to KPIs that fuel strategic planning that matters.
Next, identify the drivers and key assumptions behind your “biggests.” What inputs — both variables and constants — are used to calculate this metric? Once you’ve identified any one driver, keep double clicking until you get more underlying drivers. You’re on a mission to get to the root actors at play.
Of these drivers, organizations can narrow the list by a series of questions:

• Is it predictive of the line item we’re analyzing? If there are several drivers that are, ask: which provide the most impact?

• Is it under my control? How much?

• If we allow active planning and strategic decision making to be led by this metric, does that align with our culture? How well?

At this point the remaining candidates can even be run through the funnel of those common KPI development best practices. The old tips and tricks urging for “S.M.A.R.T. KPIs” and a “clear definition of your desired outcome” belong at the end of the process, not the beginning.

There are many drivers contributing to the running of a company. Thousands of inputs drive an organization towards its final output. The ones stakeholders choose as their compass is serious business. How can leadership know what is a key indicator of performance if no serious analysis of performance has occurred? Companies that use a bottom-up approach to KPI development will have gauges that are more finely tuned than companies that pledge allegiance to KPIs delivered from on high. And it is that data-centric viewpoint that gives an edge in efficiency, sustainability, and even innovation.