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Evolutionary Not Revolutionary: Invest Less in New Tech, and More in Your Data Values

Many leaders have this idea in mind: They want a data revolution. That becoming data-driven is revolutionary, and it’s how we should be thinking about data strategy. 

It’s not a revolution — businesses have been managing data since the invention of paper. The Romans were great data managers. The Venetians were great data managers. Data management has been around forever, and some corporations are good at it and some bad at it.

Everyone developed some sort of data management, and a lot of history’s power was in how information was handled — communications and record-keeping.

But it wasn’t revolutionary. It was a process that evolved, slowly, over time and based on the best practices. And if we want to truly lead, we need to quell the revolutionary cries and instead help our companies evolve through that same measured, proven approach.

Evolution is rooted in maturity

All organizations need to go down a similar path of data maturity. While you can skip steps in technology, you can’t skip steps in business data maturity.

You can’t expect to be really good at predictive modeling if you’re not already good at asking basic business questions of your data.

So when we’re looking at data strategy, we need to be a little more conservative about the goals we assign to the technology layer of the data strategy and a little less laden with expectations for that technology to be the silver bullet that’s going to do the trick.

Doing the trick is so much more about how the business thinks about and uses data than it is about the specific technologies they do it with. New technologies will always “revolutionize” the marketplace. They’ll disrupt. But we must evolve our knowledge of and commitment to thoughtful, intentional and strategic analysis to truly mature the business’ operations, and results.

The problem

Oftentimes, data strategies are the responsibility of the IT department. An IT-driven strategy will always be technology-heavy. It’s called information technology, but it often feels as if the information is second fiddle to the technology. IT’s job should be building business capability and results, but it’s become synonymous with building technology.

The solution

Every data strategy has to have a steady march toward business maturity at its core — governance, performance management, comfort with and innovation of how you’re asking questions of your data. Once you start innovating, the demand then arises for more advanced technologies and more advanced data applications such as predictive modeling.

How do we measure maturity?

Maturity isn’t necessarily a measure of the age of a business. Throughout the years, various organizations have taken a deep dive into data maturity. Models exist, and for those who want to study the craft, the information is out there.

But if you’re diving into Data Maturity 101, there are a few key maturation points you can strive to hit:

  • A culture of respect for data. If you want to be a data-driven company, there has to be an appreciation — adoration even — that leads to consistently making data a part of your everyday work. Not just for IT. Not just for the “data people.” For everyone. 

In reality, no organization is perfect in this regard, so instead of full buy-in, look for a cultural tipping point — is it permanent, talked about and a value held by the majority of the team? It can be respect for research, statistics and a search for new information. It can be a commitment to measuring the business and success. And it can be overwhelming. It should be. If you don’t feel like you’re staring at a mountain and thinking, “This is going to be one hell of a climb,” then you’ve probably got a way to go before you’re ready for the cultural shift. 

Underlying all of this is data management. We need to be businesses that are ready to be engaged in the work of data management, not ones trying to force it back upon IT people to be the sole stewards of data. How will you know if you’ve established a culture of respect for data? If you’re able to implement an enterprise data management program and see it gain momentum, then you’ve hit maturation point one.

  • Management and use coming together. Once a business reaches the point where it’s asking the relevant traditional questions and asking new questions of the data, then we throw in the innovation. More complex questions that reflect an evolved use of the data. We’re able to answer the questions we know are always relevant. We’re always adding new stuff and retiring irrelevant stuff. And then, we push the use of the data further than what a traditional business intelligence tool can do. 

If you’re starting to try to do things with traditional tools that are beyond their capabilities, you’re getting ready for the next phase. But use must be permanently ingrained and fully engaged with management. That means everybody who matters around the business is involved in it — not just a select few departments. It’s not partially implemented or in a pilot. It’s widespread. Everything is going through data governance. It needs to become operational — meaning, for anyone who is a data steward or owner, it’s part of their regular job to work on both operational and project data governance work. 

And both the data and the business people involved need to use quality metadata to make decisions about the data. First, quality. Then, decisions. It takes time and it takes analysis. If you’re applying business intelligence and performance management to data quality and you’re using it, you’re likely at maturation point two.

Then what?

You’ve “made it” — you have a well-established data management program and are innovating widespread data use regularly. Your investments in these are harmonized with a data strategy that ties directly into the business strategy and results. The data capabilities you build are market differentiators. They make you better than others. 

That’s when you’ve reached the evolved state. But you’re not done. You’re never done. You should be confident your data capabilities are continuously improving and having a major impact on the success of the business. And from there? You continue to invest, question and commit, because just like growing a thriving business, there’s no quick fix. Your only choice is to evolve.

Aaron Fuller

Aaron Fuller is the principal and owner of Superior Data Strategies LLC. Located in Lansing, Michigan, Superior Data Strategies focuses on data warehousing, dimensional data marts, operational data stores,...

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