This piece from McKinsey highlighted the inflated expectations of big data analytics – “…expectations of senior management are a real issue…but too often senior leaders’ hopes for benefits are divorced from the realities of frontline application. That leaves them ill prepared for the challenges that inevitably arise and quickly breed skepticism.”
The listicle (et tu, McKinsey?) summarized below, is somewhat related to that concern:
1. Data and analytics aren’t overhyped—but they’re oversimplified
2. Privacy concerns must be addressed—and giving consumers control can help
3. Talent challenges are stimulating innovative approaches—but more is needed
4. You need a center of excellence—and it needs to evolve
5. Two paths to spur adoption—and both require investment (automation and training)
In a fit of passion, let’s go ahead and disagree with McKinsey on a few points:
Data analytics is overhyped because expectations are outpacing delivery – that’s the very definition hype. Hype is going to build. There’s no containing it. Any attempt to tamp expectations will be met with angry accusations of obstructionism and negativity. To hype is to be human. It’s a force of nature.
Corporate leadership has yet to re-architect itself around introducing more friction into business processes unless the up-side is clearly demonstrated. And even then, it’s a toss up if a firm will re-architect the stack around a customer.
Privacy is the ultimate megatrend, its seeds planted long ago and fertilized by institutional distrust, but regulatory capture has tamped most advancements in consumer-privacy advocacy.
Real change will be driven by markets. Those aren’t quite in place yet. Last weeks market simulation, a search for a market for quantified self data management built on a soup-to-nuts opt-in-right-to-be-forgotten-radical-transparency model. The simulation failed. A convincing market segment could not be discovered. I don’t see those markets awakening anytime soon.
And, finally, the training curve will not catch up the peak of inflated expectations in time. It couldn’t possibly. It’s still September in so many quarters of the digital world.
Buried in the piece is the recommendation to strategically deploy talent to the places where they can make the most impact. That’s a factor that you, as a leader, can control.
You, as a leader, can hold an umbrella over talented people and allow them to succeed. That is also entirely within your control.
You can control the volume of investment that goes into automation. You can control the volume of investment that goes into retaining, growing, and continuously improving analytics talent.
These are three management levers you can readily pull.