Practical Analytics Is More Important Than Those Industry Buzzwords
My Apologies To Data Science, Big Data, Actionable Intelligence, and Data-Driven
Everybody wants to know about machine learning, but 80% of D&A jobs still require SQL. It is just more practical. Every company wants to leverage big data, but portfolio strategy actually matters (and costs a fraction of the former to boot). Data needs to be actionable as if that is even possible when most of the company is struggling to understand why it seems to matter so much. And we all need to be data-driven… but is that any more accurate?
I am a huge fan of driven employees. I love to learn. And I am a big fan of data. But all three of those statements are far more practical concerns. You see people need to learn, long before anyone starts teaching machines. Data needs to be organized in a big way — long before it can be actionable. And being driven is a personality trait, I would rather have you well informed.
If this seems like a dance in semantics, well sorry — words matter. So do symbols (spend any time on Slack?) and in very practical ways. And metaphors (and analogies) are highly simplified and effective models that make communicating ideas easier (and cheaper).
So when I chose an upside down light bulb for the cover art, there was a meaningful reason. In a world of increasingly digital and virtual business, analytics is far more important as a work light. Analytics is often required so people can see what is actually happening in their business. They need to be informed.
Information is very practical. It shows people what is happening and allows them to put things into practice. That is far more indirect than Actionable Intelligence dictates but far more simple and direct than buzzwords like Data Science, Machine Learning, and Big Data. It also means that ideas are often indirect as well. Yes — an informed employee-base is capable of creating far more actionable ideas than any analyst. Our job is to light the way (gotta love a good analogy).
So why all the buzz about concepts like predictive and prescriptive? Is that popular visualization all wrong?
Honestly, probably. The incentive structure doesn’t lead to a lot of transparency or honesty here. It just doesn’t pay for consultants to be practical. That shouldn’t be a shocker to anyone. But consider a few important realities…
- Buzzwords sell — no one is buying practical. Just ask Volvo.
- Educating your employees is far more of a service than a product — margins never favor services. Ask any VC.
- It is very hard to measure indirect impacts (like education) but you can immediately try.
- It is conversely very easy to put a dollar amount on any tool, model or forecast… but good luck measuring it until long after the checks have cleared.
- Most companies are struggling with descriptive analytics. They are perhaps far too accepting of believing there is more valuable path — especially when others claim they will do the work…
Of course, without practical insight, informed users, and organized data — none of these buzzwords have a prayer of succeeding… but that is the built-in scapegoat for failure. You see — after the checks clear, even those peddling the buzzwords admit what really mattered. “Your expectations just weren’t practical!”
I doubt I need to write this but obviously practical expectations only come from solid and practical analytics. So embrace the boring. Invest in data structures, reports, alerts, and education. Create analytics that makes your people smarter. If you really need a buzz fix — call it augmented intelligence. That really is the future… practically speaking.
Finally, the diagram is not wrong, just misleading. The slope of the line is too steep and the x-intercept is likely in the wrong place. Likely, they just distorted each axis for impact. Is that really so wrong? It probably depends on your investment and expectations…practically speaking.
Thanks for reading!
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