Editor’s note: Welcome to Throwback Thursdays! Every third Thursday of the month, we feature a classic post from the earlier days of our company, gently updated as appropriate. We still find them helpful, and we think you will, too! The original version of this post can be found here.
This is a great time for big data in business. There’s a widespread awareness of the value of big data analytics, and plenty of use cases that demonstrate its potential: understand your customer, optimize your supply chain, provide personalized app and media experiences.
No wonder that business leaders are asking their teams to look at big data. Anyone who’s read the business press on big data knows that the plan is simple—
- Get Data
Yet in the real world, there’s a big and unanswered question: what goes into step 2? That’s what data strategy is all about.
While it would be great for everyone if you could just “buy a Hadoop” and skip straight to “Profit!”, in reality there’s a lot of work involved, and 95% of it is unique to your business. How do you determine the steps of a big data project, and ensure it delivers results early?
Best practice suggests that successful companies have started with a pilot, and set out on a 2-3 year learning curve. But we think you can do better. Thanks to our years of data experience across diverse industries, we’ve arrived at the practice of data strategy.
Effective data strategy integrates a wide range of factors: the goals of the business and product teams, the capabilities and workflow of the analytics and engineering teams, and existing systems and data. Working through these, we can identify a roadmap of new capabilities, prioritized meaningfully. You get the benefit of focused scope with immediate return, but you can also build towards a long-term architecture.
Today’s business environment is digitized—look at mobile apps, 3-D printing, and IoT, as just a few examples. In other words, data today has to serve the strategic imperatives of what a business is doing. When we say strategic imperatives, we mean those things that define an organization by what they want to achieve. You could minimize what you do with data, but you would be left behind. You would be a taxi firm when Uber starts, or an old-fashioned TV network subsumed by Netflix or Amazon. A data strategy is about imbedding data-driven decision making, about being able to create data applications inside a company to help it achieve its strategic goals.
We have a quick, two question, quiz that we use when teaching strategy in person:
- Do you feel that the technology leadership (the CIO, for example) prioritizes their IT investments according to the ambitions of the business as a whole?
When we ask this, about 40% of our audience puts their hands up. That may be a good amount, but still means the majority don’t think their IT spending is supporting the ambitions of the business.
- Can you clearly say how your investments in data technology have impacted the business?
We find that maybe 10-15% of the audience raise their hands here.
If you answer no to either or both of these questions, then you need a data strategy.
We do accept that data strategy is a term that has been overloaded. Conventional data strategy is often all about looking inward at the systems you have, how to reduce risk, and how to implement governance. All valid things to do, but they don’t look to value. In fact, these well-meaning efforts can actually impede progress. It can frequently take three months to move a data set into a warehouse so it can be exploited, and three months is a long time in business.
Instead of just thinking about what you need to do to data, we think about what to do with data. For example, how can we use predictive analytics to identify our VIP customers and then generate great recommendations for them? Or, how can we use data to automate processes that take days, and turn them into hours?
There’s more to it, of course, which is why we speak on this topic at various events—look to the list at your left for more information on our upcoming presentations. In the meantime, check out these resources:
- Our Data Strategy Position Paper (complete with a checklist for creating your own strategy)
- VP of Advisory Services Scott Kurth’s fireside chat about strategy within your company
- A deeper description of our data strategy work.