Data Competency and Business Management – Shift Happens
Data Models by JD Hancock
Data, big data, and more data. Data is everywhere in business. I have seen a lot of questions about what is big data, what is a data scientist, and where can we find good data scientists. But, today I ask, how does business gain management competency with data? Business schools typically teach data analysis as a core subject for their MBA and Executive MBA programs. Subject names vary, but include:
- Data Analysis and Decision Making Under Uncertainty (AGSM)
- Data and Management (INSEAD)
- Data, Models, and Decisions (MIT Sloan)
- Data, Models, and Decisions (London Business School)
- Data Analysis and Decision Making (Stanford)
Now, I’m not going to suggest that one grad school course in what is ultimately foundational probability and statistics is going to set up a manager to competently deal with the ever increasing demands of data capture and data analytics (it won’t), but I do want to say, based on the course outlines I’ve seen, they are perhaps teaching only a tiny subset of what managers really need in business and are short changing industry.
Some common issues, though certainly not an exhaustive list, I see that business leaders are grappling with, in the area of data, are:
- I’ve got all this data, how does it help answer my questions?
- Is the data of good quality?
- There’s too much data, too many variables, how do I understand what I’ve got?
- How do I connect this data to other data?
- That’s a pretty chart. What does it mean? Can I trust it?
I am struggling to see how a course in probability and statistics, especially those that teach students how to perform the mechanics of conducting such analyses, is going to help managers answer those questions.
Even before the advent of “big data”, we’ve had a plethora of data analytics activities such as data mining, “fuzzy” logic, genetic alorithms, geospatial analytics, machine learning, natural language processing, querying, signal processing, and I’m sure there’s many more. Oh yeah, and statistics.
The challenge for the modern manager is perhaps the ability to call bullsh*t when presented with certain information, or to be able to reliably and confidently direct a line of enquiry within available data.
Another line of study for data lies within governance and law. What are the privacy and ethical issues surrounding the capture, use and storage of data?
Then there’s the immense field of data related technology. I don’t think it is the place of an MBA course to cover the plethora of tools available that cover the multitudes of analytics types for all manner of data types. Certainly, an MBA marketing course will not, and I think, should not, cover intricacies of Search Engine Optimisation, but at least cover the fact that it exists when covering digital marketing and the various P’s of the marketing mix.
The technology space moves way too fast for any academic setting to cover in a generalist course. But today, what doesn’t move fast?
Some years ago, the education sector released a fantastic video called, Shift Happens. Here’s the 2012 version of Shift Happens. It went viral, and many subsequent updates and other videos based on it have been released. Here’s a more recent one on YouTube. It’s also known as, “Did You Know?”
One of the main messages in it is, we are currently preparing students for jobs that we don’t even know will exist in 10 years’ time. It presents a large series of information snippets, like how the top 10 in-demand jobs in 2010 did not exist in 2004. Shift happens.
I think our business schools should be opening the eyes of our managers and future managers to the current and the possibilities, and work through how to think, analyse and solve business problems using data.
Rob Stenz at Forbes looks at how data is a core competency in a growing set of occupations. In it, he quotes the CEO of CareerBuilder, a large US jobs website, ““Occupations are evolving, and we are seeing data analysis in more job descriptions.”
I’d like to see MBA courses evolve to factor this shift.
