Moneyball comes to Human Resources: Data Science Matters

While you may not be a baseball fan, you have to admit that this movie (and book) is really all about Human Resources. Billy Beane learned that by using data shrewdly he could build a high-performing team at a fraction the cost of his competitors. Isn’t this what strategic HR is all about?

I’ve had the opportunity to do a lot of reading and talk with a lot of people about “Data Science” and the use of “Big Data” in business over the last few months.  McKinsey recently published an amazing research report on the applications of BigData in business, and I urge anyone interested in this subject to read it.  The reality is that businesses today are sitting on so much data – data about employees, customers, transactions, and their business operations – that a whole new “Data Science” has emerged to turn this data into competitive advantage.

Consider a few interesting facts:

• Data Scientists are now considered one of the hottest new careers in the coming decade (a “data scientist” is someone trained to understand how to manage, analyze, and identify signals in data)
• Web leaders like Reid Hoffman (Founder of LinkedIn) and Tim O’Reilly (CEO of O’Reilly Media) now recognize that Web 3.0 is really “data as the platform.” LinkedIn’s new recruiting platform scores ten billion connections every night to bring you “people you may know” and “recommended candidates” for a given position.
• Facebook users now upload more than 6 billion photos per month and YouTube users upload more video each day than all the major networks content combined.  McKinsey estimates that healthcare organizations alone can save more than $600 billion by learning to mine the digital data in their own businesses.
• Companies like Lowes, Rogers Communications, Credit Suisse, Accenture, Eaton, and many others we talk with are creating “HR Data Scientists” (analysts) who spend their full time analyzing data about their own people, to identify what precisely makes up a high-performer, and how to best replicate this performance in the workforce.

Unfortunately, Human Resources teams are still ill prepared to take advantage of all the new data and tools available.  In our 2010 High-Impact HR research, we found that only 6% of the 1000+ HR organizations we surveyed rate themselves “excellent” at data analysis and interpretation and 56% rated themselves poor.

Let me give you some concrete examples to explain why data science is now one of the most important things you can do to improve organizational performance:

• At Lowes, the Vice-President of Talent analyzed store by store performance and correlated revenue against employee engagement scores.  He found a direct correlation to engagement, and a particularly high correlation to the in-store satisfaction with a single role:  the store sales leader.  This role, which is the store “product expert” (not a managerial role), single-handedly drives sales greater than any other individual in Lowes.  As a result of this statistical analysis, Lowes revamped its sales training and assessment program to focus  on understanding how to build stronger skills among this group.
• At Bon-Ton, the Vice-President of HR found (we documented this in our Science of Fit research) that high-performing cosmetic sales people are not necessarily the most attractive, but rather are those with particularly high levels of cognitive skills.  It turns out that cosmetic sales is a complex business – so only quick thinkers can succeed on a regular basis.  This information, developed in great detail at a competency level, led Bon-Ton to revamp its hiring process and improved cosmetic sales profit by almost 30%.
• At Credit Suisse, the HR analytics group studied the performance of all major business units and found that revenue performance was most highly correlated to managerial satisfaction, ability to make money, and employees’ perception that they have a future career in that organization.  This latter factor was a much greater contributor to revenue than ever expected – and this finding led to a series of new career programs and development planning around the company.

We are identifying these “Moneyball” applications every day.  There is a science to strategic human resources, and high-performing organizations have taken the time to analyze the “signals” they hear from their workforce to identify the strategic drivers of organizational and employee performance.