Big Data Calls for Big Strategy


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In a recent post of mine, More Data, More Problems, I talked about some of the headaches that companies are facing when it comes to managing the massive amounts of business intelligence (BI) that are coming through their doors. Each of those problems I mentioned are large issues—I won’t try to say that they aren’t—but they could have all been mitigated, maybe even avoided all together, if a solid big data strategy had been put into place before the BI started rolling in. For companies who are already facing these challenges, a strategy can help them get back on track with more focused goals and priorities.

When I say strategy, it really starts with talking. Simple. It means sitting down to have a conversation about big data that includes not only the executive board, but also IT, and also the decision makers from your other large departments. It means not only talking to the people who make the BI goals, but the people who will be using the data, and yes, the IT employees who will be managing it for your company.

How do you start those discussions? How do you move from conversations to strategy?

Decide on priorities with input from each department: How much of the budget can be routed to BI? What does that, in turn, mean for IT’s capabilities? Which technologies are your company already using that could be funneled into BI management? Which technologies are just going to clog up the works? What does the executive team want to see happen with this new investment in data? When every key member of a discussion can isolate his or her most important priority, that’s when a company can really start moving forward on a BI strategy.

Start small and look to expand larger: The best (not always easy) way to move forward with incorporating BI solutions is by targeting priorities in one key area of the business. Work out the kinks this way before starting an enterprise-wide data movement where you’ll likely become caught up and overwhelmed with all of the data.

Define what success looks like for your company: How will you know if all the funds you’re putting into BI is working? You won’t, if you haven’t given thought to what you mean to get out of it. Success will mean a different thing to each company and every data campaign. Higher margins? Better customer engagement? Targeted advertising?

Focus on BI solutions that are easily retrieved, managed, and analyzed: BI isn’t useful when it’s so sprawling that nobody even wants to start the work of analyzing it to see trends. Your initial conversations about your big data strategy should include the agents and staff who will be drawing on the BI in order to see what data will be the most relevant for them and the best ways to organize it for usage.

Figure out a way now to dump big data when it’s no longer useful and relevant for the company: Chances are, you don’t wait for the trash in your kitchen to pile up and become a problem before you think about taking it out. You take it out consistently and often (or when someone more conscientious nags you about it.) Your BI plan should also have a framework now for how often you’re going to dump the data garbage before it starts piling up. Add clear definitions for what type of data will be retained and for how long.

What other elements do you think are important for a solid data strategy?

Republished with author's permission from original post.

Dave Harper
Dave Harper, Director of Aspect Analytics National Practice, speaks nationally on industry technology trends and at many events in all vertical markets. Dave continues to serve as the technical architect on many of Aspect's large-scale analytics projects. He has more than 12 years of experience developing and implementing solutions for all types of organizations, with significant experience in creating leading-edge Microsoft Business Intelligence solutions.


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