A few years ago, the Major League Baseball team, the Oakland Athletics utilized a new system of analytics to assess its players and prospects based on empirical statistics. This system – which was the basis for the book and later the major motion picture “Moneyball” – is the foundation upon which a new way of managing people in the workplace was built. This system is known as “People Analytics”.
Today, people analytics is widely used by human resource departments and business management to remove anything non-empirical from decision making processes involving hiring, managing and promoting within the work force. It takes such things as gut feelings, instincts, intuition and persona prejudices or bias out of the equation.
What’s left is data that can be analyzed statistically in order to make decisions based on the best possible outcomes for an individual business.
Spreading among HR Departments like Wildfire
Once upon a time, products were developed and marketed based on hunches and instincts. This made business more of an art than a science. Today, however, businesses of every size have access to analytical tools, algorithms and data packages that can be used to reverse this balance and cause business decision making to be based more on science than personal feelings or impressions.
While this type of people analytics is now becoming wildly popular, it’s actually nothing new. Since at least the 1990s, credit agencies, credit card companies, banks and other financial institutions have been using FICO scores as the primary measurement tool of an individual’s credit worthiness.
This score uses real data – such the amount of debt a person carries, how quickly they pay off their debts, how often they miss or are late on payments, and so forth – to come up with a single number. This number is essentially all most creditors need to know in order to make an accurate decision regarding that person’s credit worthiness. There’s no guessing or uncertainty. A person’s credit score is a relatively accurate representation of their ability to handle debt.
People Analytics in the Workplace
When it comes to human resources decisions, companies want to make sure they are putting the right people in the right places so that they contribute optimally to the success of the overall enterprise with maximum efficiency. Increasingly, people analytics are being used to achieve this objective.
There are essentially four levels of people analytics that companies use to assess individuals within their organizations.
Random Access Reviews –
The first level of people analytics is also the most unscientific. It also happens to be the most popular. It involves pulling together existing records on an individual and reviewing the information they contain. These can contain things such as sales reports, annual reviews, performance evaluations, work histories and other documentation.
The problem with this level of people analytics is that many of these documents include subjective information: What their supervisor thought of their performance, how much faith their manager has in their ability to grow, and so on. It is helpful in answering general questions – such as who are the best and worst performers, and how successful is an employee rewards and recognition program working – but little else.
Analysis of Existing Hard Data –
The second level of people analytics dispels with everything subjective in an employee’s record and instead focuses on any data that can be empirically measured. This data is then analyzed either manually or by use of software and computer algorithms to compile and rank performance against a standard scale. It also can be used to rank employees’ performance against others within their subset.
Predictive Modeling –
The third level of people analytics builds upon the data compiled in the previous level by using its conclusions to employ econometric strategies – such as multivariate regression – to predict future behavior and probabilities for success.
For example, human resource professionals can use predictive modeling to accurately predict whether a salesman being considered for a district manager’s position is going to be successful in that position. Predictive analysis answers “what if” questions so that hiring managers can remove nearly all the guesswork out of hiring and promoting decisions.
Multivariate Testing –
The most advanced level of people analytics employees A/B testing in which one variable is changed to see what changes it causes within a controlled environment.
For example, multivariate testing can be used to study which type of management styles result in increased productivity and which actually dis-inspires employees. When people analytics reveals this type of predictive analysis, the findings can then be applied globally throughout the organization in order to streamline efficiency and productivity.
While people analytics is now used by many companies to help streamline their human resource decision making, given its accuracy its likely to become the standard in the years to come.