From Big Data to Bigger Results: Focus on Ecosystemic Conditions for Analytics ROI

Posted by Taylor Haney on Mon, Apr 8, 2013

We are officially kicking off our guest blogging series for the month of April with this exciting post from a great member. The theme this month is Big Data and there is some great content coming your way! Guest blogging is an opportunity we extend to our members and in the coming months we have some exciting topics, if you would like to contribute read our previous blog with all of the details.cesar brea resized 600

Cesar Brea is the co-founder of Force Five Partners, LLC, which works with multi-channel marketers across several industries to build their analytic capabilities through hands-on support for marketing programs and campaigns. More: www.forcefivepartners.com

Big Data, as Alicia Keys might say, is “On fi-yah!”  As I walked through Logan airport this morning, I couldn’t take ten steps or turn my head more than fifteen degrees without seeing an ad claiming its solution as the best path to enlightenment and bigger profits. Google Trends confirms the zeitgeist:

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Inevitably, we can soon expect the trend to get a little frothy. In my book, Pragmalytics, I suggest one reason is that many firms are discovering that you can’t just drop seven hundred Big Data racehorses under your hood if your transmission is more lawnmower than Lamborghini. Rather, if you want the ROI that Big Data investments promise, you need to focus on “ecosystemic conditions” for success.  In our work with a dozen clients across a number of industries in the last several years, we’ve distilled out four such conditions:

1. Strategic Alignment
2. Access to Data
3. Operational Flexibility
4. Analytic Marketer Mindset

Strategic Alignment

Put simply, if your senior sponsors don’t clearly articulate or can’t agree on problems worth solving with your Big Data capabilities, you’re not likely to have much success.  Which customers should you prioritize?  Where across the sales funnel should you focus?  What decisions have sufficiently high stakes and high uncertainty to deserve research and analysis, and which should move more quickly to be tested? Across the last five years, we’ve seen this challenge surprisingly often.  To help, we’ve developed an artifact we call the “Analytic Brief” which presents some simple questions to drive and sustain this alignment.

Access to Data

If, as vendors’ ads might have us believe, their Big Data solutions are like fighter jets, then data is jet fuel, and you’re grounded without it. We typically encounter one of two scenarios when we engage with clients. Sometimes they’re in the middle of a major data warehouse or governance project to create the perfect fueling infrastructure for any set of questions business types might want to ask.  Sometimes, they’re in the middle of a data mess, where no one knows where to find things or how to readily get what you need. (And sometimes, both conditions prevail…) One of our first efforts is to create, for ourselves if for no one else, a simple registry of the major data sources relevant to the business issues we tackle, documenting such basic things as major elements, keepers and contact information for different data sets, and information about how the data is generated that helps us understand its limitations, cleaning requirements, and necessary transformations. And then, we don’t try to clean things up any further until a pressing business opportunity that will deliver ROI for incremental efforts compels us to.

Operational Flexibility

Big Data’s not much use if you don’t have the operating infrastructure and processes to act on any insights you generate. Examples of such infrastructure include marketing automation systems such as those from Marketo or (Massachusetts’s own) ClickSquared, or digital content personalization tools such as Adobe’s CQ and Test & Target. But technology is only part of what’s needed. You also need budgeting and creative asset development processes that can keep up with ideas the Big Data machine cranks out. Ideally you work toward an integration of Big Data–based analytics and your execution capabilities, so you can automate the execution of programs based on algorithms and rules you discover and specify. Beware, however, integrating and automating execution capabilities past the point of diminishing returns.

Analytic Marketer Mindset

Everybody’s hot on “data scientists” these days. We’re even hotter on what we call the “Analytic Marketer”, someone who does a good job of combining “Mars”, “Venus”, and “Earth” mindsets and skills. “Mars” is shorthand for strong analytic skills: comfort with data, statistics, logic. “Venus” is code for creativity and communication abilities. “Earth” speaks to practicality and results orientation.  A good Analytic Marketer will always be able to find specialized support when needed, while a marketing organization composed of silo-ed, “best-of-breed” data scientists, creatives, and managers may find itself unable to reconcile perspectives and drive to action.

We’ve developed this ecosystemic condition framework further, to a simple you-know-them-when-you-see-them collection of descriptions for evaluating where your organization is on each of the four factors, so you can judge how fast and how far to push your Big Data investment. One interesting finding is that in applying it, we rarely see an organization that’s very far advanced on one factor and lagging on the rest, or vice versa.  Rather, a constraint in one area generally seems to limit what’s possible in other areas, possibly because without the ROI that flows from having all four in sync, you don’t get very far on any dimension.

What conditions are you keeping an eye on?  How do you manage and evaluate progress?  I hope to learn from your experiences soon.