Please click here for the first post in this series.
We previously introduced the concept of big data, including citing a New York Times article as an excellent primer on the subject. Of course the biggest challenge (and opportunity, mind you) of big data across any field is finding the requisite talent and raw analytical horsepower to sort through it all. While these skill sets are obviously in big demand -- the NYT article cites the McKinsey Global Institute, which projects that "the United States [will] needs 140,000 to 190,000 more workers with 'deep analytical' expertise and 1.5 million more data-literate managers, whether retrained or hired," to meet emerging demand -- another challenge is identifying those with contextual knowledge that can go beyond data crunching, adding an empathetic filter on top of what information might appear to be telling us.
I like, for example, the citation of a young political science professor at Stanford who "combined math with political science in his undergraduate and graduate studies." Now, with these skills at his disposal, "research involves the computer-automated analysis of blog postings, Congressional speeches and press releases, and news articles, looking for insights into how political ideas spread." Fascinating. But also absolutely relevant if we consider the types of leaders we're going to need to identify and promote through the fields of procurement and supply chain in the future.
The ability to know how to structure different types of information sets, synthesize the data that's presented back and constantly monitor all the background noise that may or may not be a telling hint of a broader data point or trend to probe on are combined skills that can be taught, but that largely require a base level of analytical horsepower. But more important, these are skills that we won't just require of our data analysts -- or "data mavericks" as some describe themselves, inside joke noted -- but also procurement and supply chain leadership, who will need to direct their teams to focus on certain areas and then interrogate the results (not to mention becoming more comfortable running their own analyses).
This is why I'm as concerned as any about generally declining math skills in this country, at least at the high-school level (not to mention what's required in college). After all, even though Indian BPOs and KPOs will offer much needed analytical horsepower to help solve these problems, onshore skills, expertise and most important, empathy, will be required of most everyone in the function going forward. Ask yourself: what percentage of your team has the raw analytical horsepower to converse in big data speak? And are they fluent or merely capable of stumbling through the challenge with the most basic grasp required to not make fools of themselves?