When will KPIs become redundant?

Maybe when we start making mechanized business decisions based on a more holistic awareness of data.
18 October 2018 | 9 Shares

Will KPIs ever become redundant? Source: Shutterstock

Businesspeople of all kinds love KPIs; it’s just a fact of life.

Even when profits are down, competitors are booming and the market appears to be twisting in directions that the business can not feasibly realign itself to; if all the KPIs are in place and are being monitored diligently, then there is no major need for alarm.

Or at least, this is the way it often appears to be.

What is a KPI, anyway?

TechTarget defines Key Performance Indicators (KPIs) as business metrics used by corporate executives and other managers to track and analyze factors deemed crucial to the success of an organization.

“Effective KPIs focus on the business processes and functions that senior management sees as most important for measuring progress toward meeting strategic goals and performance targets,” details the definition.

But there’s something missing here.

The development of so-called ‘effective KPIs’ (as noted here above), surely, are ones that are truly achievable and plug backwards into the operational processes of the business and the very decisions that a firm makes in any given scenario at any given moment.

We’re missing the mechanics of the KPI argument, aren’t we?

Missing mechanics

Research from iPoint suggests that 40 percent of firms do not have formal KPIs while 55 percent only have informal measurement metrics.

Oliver Mueller, Co-Founder and CEO of iPoint BiS says that, “We live in an era where data can deliver easily trackable progress and actionable insights for decisions and improvements in real time.”

Mueller and team point to the use of graph database technologies to give firms a more textured and multi-layered approach to tracking events throughout the new digital business chains that we will all now operate with.

Graph database technology certainly offers the opportunity to widens the scope of the information curve we use to run our businesses into more dimensions, but it should not be seen as a cure-all and it could (arguably) make tying down (and performing to) KPIs more complex in some scenarios.

Automated decisions?

Should we instead be looking for tools that offer us the power to make more automated decisions? This could be the end of KPIs if the software systems used to run business operations are capable of also executing those decisions inside live running operational systems.

There are systems today that can combine a chunk of artificial intelligence (AI) with a dose of real-time business performance analytics to automatically identify and prioritize future business opportunities and risks.

The kinds of tools we are seeing coming out here are capable of making recommendations about the best course of action for any given business decision. They can, for example, help quantify the economic impact of each decision in the business so that a decision’s cost and potential revenue uplift are automatically calculated.

In fact, new-age software can ensure that all operational changes are automatically forecasted and measured using embedded algorithms, and that exceptions and anomalies are automatically flagged and prioritized by impact and relevant stakeholders are alerted proactively.

No KPIs are hurt (or indeed used) in the process.

Management backstop indicator

Actually that’s an overstatement, these types of systems don’t necessarily demand that we ignore, strip out, delete and ignore KPIs.

They can still form a sort of management backstop indicator (MBI, not a real term or acronym, but it should be) of sorts that has rather less mission criticality ascribed to it.

Data product specialist at Israel based CoolaData Amit Levi suggests that over and above KPIs, we can look to the use of behavioral analytics to adding additional colors to the picture.

“It’s about placing things into context. Instead of only monitoring the KPIs, Behavioral analytics enables us to see sequence of events, understand what happened before and after the target event, explore the user paths to really analyze causes,” writes Levi.

The way ahead, for now, is probably a ‘middle-way’ combination of all factors here that certainly adds a new degree of automation and big data AI-driven intelligence to the fold.

When we automate more successfully, in context, with mechanized business decisions based upon a more holistic awareness of data at many different levels, then we can alleviate our KPI fixation just a little.

The death of the KPI has been grossly exaggerated, for now, at least.