The Search for True Value from Data

or, what the trough of disillusionment really feels like

Data professionals everywhere are waking up to an inconvenient truth. Results are not meeting expectations, despite all the innovation in product and tooling around data technology.

Everyone wants answers. Everyone wants visibility into their business. Everyone wants operational efficiency. Show me a single business executive who breaks this pattern, and I’ll show you someone who won’t be long in their role.

Needing and wanting are not the same thing. Data is necessary, but not desirable. Everyone needs electricity, but everyone wants light.

In fact, electricity itself is scary to many people. It’s dangerous. And there is an entire infrastructure behind it, regulations, and a mystery at the atomic level that I don’t wrap my mind around.

But I sure do want light, which helps me see and operate.

I appreciate the introduction to the Shepard tone from Benn Stancil. Take a moment to understand it and you will see the depth of that analogy.

Compare it to running on a treadmill—lots of effort, and the runner gets stronger and healthier.

But ultimately the runner doesn’t get very far. That describes very well where the data analytics industry is right now.

The runner could improve through better treadmills, futuristic clothing, and measurement devices.

But a plan for getting from here to somewhere else, and dealing with the real risks of cars, dogs, and ice patches—that’s getting somewhere.

Business leaders know that rarely is anything as simple as flipping on a light switch. But we are constantly looking to put reliable systems in place that produce business results. That way we can focus on problems that still need manual effort or unreliable systems.

Most people understand the power and potential that data can give to a business. And so the entire industry and community launched into realizing that value. But we have a serious trough of disillusionment problem.

Data teams and professionals feel frustrated. Department heads, customers, and other stakeholders feel frustrated.

The average tenure of data executives is short. From what I have seen, they have big plans for how great they are going to manage the data.

That’s the wrong answer… no one wants data, no matter how badly they need it.

We don’t have a VP of Electricity for a reason—it’s a lower-level system that doesn’t get a seat at the table in a business.

The head of the support desk is not on the executive team, nor is the social media marketing manager.

I’ve seen many companies where CTO is an elevated title, while the VPs of engineering, product, and marketing are driving the company forward.

The same reasoning behind the CDO—super important, but the practices and focus don’t align with the results the business needs.

“For the better part of a decade, we’ve been trying to manifest a narrative about how data teams are critical pillars in modern companies”

Data is complex, and so it can turn into an endless engineering exercise.

Data is complex, so it is hard to find that one person who “gets it” and can map the technical effort to results visible and understandable to the business.

And yet business is complex, so it is hard to articulate and translate ideas from people’s heads into exactly what they expected from data teams.

The trough of disillusionment presents good news and bad news. The bad news is that it is painful and sad. Disillusionment can cause abandonment, by data professionals as well as by businesses.

The good news is this is a proven pattern. The future holds the promise of productivity and satisfaction.

“Self-serve - was it too general? It should always have been an 80/20 hybrid model”

This has always been my take and is one of the tenets of how I operate Datateer. There is a balance between tooling and process, between tech and people. And in general, the pendulum has swung far to the tooling/tech/self-service side.

Because the industry has become adept at delivering data… which our stakeholders don’t want.

To get out of the trough, more iterations are necessary. Tighter, shorter feedback loops help tremendously. Very thin slices of end-to-end delivery, and constant realignment—i.e. “is this working?” and validating (or challenging) assumptions.

In my company, we go through a mini-trough with every single customer. Expectations are high, disappointment and reality hit, and—with most—we get to a level of productivity that works and provides value.

Why does this keep happening? It’s amazing to watch the decision-making and risk-versus-reward situation. Everyone knows the potential of data, but the ROI is unclear. But it is so important that businesses continue to invest even with no guaranteed ROI.

The adventure of getting out of the trough and finding ways to ROI is thrilling. But like anything with high rewards, I accept the risk and the failure that so often can come with it.

I wouldn’t want to be involved in anything else.