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Paving the Last Mile of Big Data Analytics

Alan Radding, guest blogger

(A book is the best way to build a consulting practice, ask me about ghostwriting your book.)

“The use of big data will become a key basis of competition and growth for individual firms. From the standpoint of competitiveness and the potential capture of value, all companies need to take big data seriously,” says McKinsey’s Business Technology Office, in a report titled: Big data: The next frontier for innovation, competition, and productivity.

Well into the report sits this tidbit that should be immensely interesting to Big 4 consultants:  There will be a shortage of talent necessary for organizations to take advantage of big data. By 2018, the United States alone could face a shortage of 140,000 to 190,000 people with deep analytical skills as well as 1.5 million managers and analysts with the know-how to use the analysis of big data to make effective decisions.

And much of that shortage will be found in the last mile of big data. Most consultants today are staking their big data initiatives on the technology platform, but that’s a game that will only benefit the big technology vendors.  The last mile of big data, however, addresses the specific client situation, which “is different in every case, very context sensitive—this is the last mile, the final customization of pre-built models and algorithms,” says Phani Nagarjuna, CEO of Nuevora, San Francisco, CA.  Nuevora’s proprietary Big Data Analytics & Apps Platform (nBAAP™) configures and customizes a broad set of pre-built big data analytic models and algorithms to enable a consultant to pave the last mile for its clients.

Of course, a consultant can pave the last mile of big data analytics on his or her own.  It is just a matter of researching, defining, and testing any number of models to come up with those that work consistently and deliver predictable and repeatable proven results.  The same goes for the algorithms that provide the substance behind the models. Again, there are many possible algorithms for every kind of business problem that a consulting client might want to solve.  Each algorithm needs to be tested repeatedly for every problem.

There are not that many problems today that consulting clients are turning to big data analytics to solve.  One, for example, is the challenge of predicting and reducing customer churn. Another involves identifying potential fraud.  Still others want to comb through big data to highlight opportunities to increase value from the customer relationship, either by generating more frequent sales to the customer or selling a variety of different products.

But even if the number of problems clients want to solve using big data is limited to a dozen or so, there are variations with each of those.  The churn problem, for example, might also be applied to address employee turnover, another costly problem for many companies. Each variation of the basic problem requires tweaks to the underlying models and algorithms. A one-size-fits-all big data solution rarely works well.  The problem of customer churn at an insurance company, for instance, will be considerably different than for a bank. Although at one level both provide financial services the last mile of big data for each is not the same.

That’s why paving the last mile of big data analytics is so challenging and why the big platform vendors avoid addressing it specifically. It is costly to configure and customize each big data solution for the customer’s specific problem to be solved.  But this provides a perfect opportunity for the consultant who understands the client’s problem and want to use big data analytics. By leveraging tools like those offered by Nuevora the consultant can address the client’s issue fast and without a large investment.

Nuevora provides a big data analytics platform for the consultant aiming to solve its client’s issue through the use of big data. It draws in any type of data and runs it though its big data processing, modeling and apps engines. For any given problem it selects the most appropriate model from its wide range of proven models and then applies the analytic frameworks, and data heuristics that will deliver the best results.  The results can be deployed to the client’s preferred business intelligence / reporting platforms, whether Cognos, Oracle, Tableau, or whatever else the client uses, even Excel. The Nuevora nBAAP platform handles the data, provides the models and heuristics, recalibrates on an ongoing basis for continuous improvement, and can augment the client’s data with Nuevora’s own proprietary data or outside data it pulls in.

Through such a platform consultants can become more client-centric by focusing on the desired business outcome rather than on the technology. In the process, it enables the consultant to breathe life into his or her big data plans and roadmap for the client. In effect, it provides a proven starting point for big data allowing the consultant, who knows the client’s business and needs, to configure the last mile confident that it will work.

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