This post is part of a series focused on using a digital transformation strategy to provide the much needed context for lower-level initiatives like big data and analytics.

In the previous post, I talked about how to maximize the benefits of your move to the cloud by making it part of a larger digital transformation strategy.

In this post I will discuss how any large move into big data and analytics should also be part of a larger digital transformation strategy. It should not be a move you take lightly, but instead, should be focused and be in support of the overall strategy. It sounds obvious, but more often than not, companies are embarking on “big data” projects with no real end-game in mind.

First off, when we talk about “big data” don’t be concerned whether it’s big, small, thin, wide, structured or unstructured. Begin by asking yourself these questions: 

Is there key information that you don’t have today that could drive a key new initiative, address a major problem, realize significant savings or provide a competitive advantage?

Are you getting all the value possible from your existing data? If you’re reading this…probably not.

You can likely think of many possible answers to these questions, so the problem quickly becomes figuring out where is best to start and spend your time and energy. This is where the digital transformation context comes in. To have a major impact you have to “dream big” on the scale of digital transformation. A digital transformation strategy (aligned with the overall business goals) provides a "frame", which brings clarity to what data and information is critical for success. For example, a digital transformation strategy that focuses on manufacturing excellence probably wouldn't need much (if any) data and information around Human Resources, whereas a strategy focused on Digital Workplace would.

Without that focus and context, it’s extremely easy to get caught up in many different “big data” like projects that may seem important on their own, but in factare unlikely to have any major impact if they’re not treated as part of a larger strategic initiative. But you might get lucky. 

The one thing that is guaranteed is that if you do jump into a number of independent “big data” projects, you will spend significant time, energy and money. People will start to notice if it doesn’t have substantial impact. In essence, it breeds a lot of “the right hand doesn’t know what the left hand is doing” behavior, and that never ends well.

Now let’s assume you at least have the frame of a digital transformation strategy. Now think about what information would be critical to support your overarching strategy. As an example, let’s pretend we are in a fictional manufacturing company that has started to define a digital transformation strategy around a major evolution of our sales ecosystem. In terms of data and information, we’d need to know things like who the top customers are, what they’ve bought recently and how much revenue that has produced. This is important information, but investing in a major digital transformation effort simply based on what happened last year is risky at best, and maybe even disastrous. To really help make this initiative successful, you need to have a much better picture of what the future looks like. 

When talking big data and analytics, it means looking for significant patterns in the areas we’re selling in to, and quantifying the areas of opportunity. For example, if Sally and Bob had good numbers selling through their direct channels last year, maybe we’d just decide to invest heavily into their teams by adding middle managers and more staff. But maybe the direct channels just happen to have topped out last year and the real opportunity was to build out an online ecosystem that could be integrated into a number of key partner channels. Those are two very different paths that could yield dramatically different results. To have realized the better path would’ve required much more information and analysis around the trends in the market (e.g. general online purchasing patterns), our sales patterns (e.g. partner sales growing proportionally faster, patterns in the size of purchases), our online presence and activity (e.g. what are people really doing when visiting our website, who are they and where are they from). And the most difficult part: tying it all together to actually quantify it as an opportunity and the best path for realizing the digital transformation strategy. Doing this goes beyond traditional methods and into what has been labelled “big data”.

Even though this is just a hypothetical example, I hope the point is clear. Big data and analytics can and should play a major role in part of a digital transformation strategy. Like I said in my earlier post, Data doesn’t need to be physically “big” to be transformational.  It’s most important to tap into the data that can provide the most impactful information. Being part of an overarching digital transformation strategy will maximize that impact.

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