As I’ve been talking to business leaders over the past few months, I’ve noticed that more and more of them understand the scope of big data – it’s “volume, variety and velocity,” as Gartner would say. In addition, they’re increasingly aware of the enormous value of big data insights.

So, these days, the one remaining question on everyone’s mind seems to be: How can my company get started with a big data strategy?

For many, the process seems overwhelming. I’ve heard people say, “It’s like climbing Mt. Everest!” But, I assure you, once you break it down, you’ll see that a data strategy really is quite manageable — if you take it step-by-step.

Here’s a simple outline to illustrate my point and help guide your process. When you’re ready to develop a big data strategy you need to:

1. Chart your vision.  Identify what kind of customer experience you want to deliver. Compare this “ideal” to the current customer journey.  What needs to be changed so you can close the gaps? What business questions must be answered so you can deliver on your vision?

2. Assemble the right talent … and equip them with the right tools. Whether you decide to hire from outside or groom your own best employees, you’ll need to build a team that’s knowledgeable, skilled and gutsy. Why gutsy? Because they’ll be continually challenging the status quo. Give this team the tools required to get the job done, and make sure they have senior level support, too. Now and then, roadblocks are bound to appear, and the team will need to rely on the C-suite to help mow down the most stubborn obstacles.

3. Inventory your data and determine what’s missing. At most companies, data is fractured into various, disparate silos. Take the time to look around. Ask questions. Your marketing organization may find the customer data it needs is already being collected by customer support, R&D or some other department.

4. Consolidate and integrate your data. When you have a comprehensive, integrated view of your data, you’ll be better able to use it to inform campaigns and customer engagement strategies.

5. Test. Evolve. Expand. Start with small pilot projects – they’re relatively easy and low-risk. Just make sure to keep them focused and short-term. As you achieve results, continue to grow and evolve, but never lose sight of the vision you established in Step One.

One of the nation’s leading shoe retailers, DSW, used a data strategy to grow its customer loyalty program and inspire front-line employees. You can find out how DSW put data to work in the case study, If the Shoe Fits, Sell It!

And, of course, DSW isn’t the only company seeing results. According to research conducted by MIT Professor Erik Brynjolfsson, he found that data-driven enterprises outperform their industry peers by up to 6 percent and are as much as 26 percent more profitable.

Are you ready to get started on your data strategy? I hope the five steps above have helped convince you that it doesn’t have to be overly complex. After all, the answer to the question I asked in the title of this post is rather straightforward. How do you climb Mount Everest? By taking it one step at a time.