• This field is for validation purposes and should be left unchanged.
Guidance and results for the data-rich, yet information-poor.

Target Your Assumptions to Get More Out of Analytics

BriefcasePredictive analytics offers one outstanding strength: it helps to eliminate the inconsistencies in human behavior. It even helps you eliminate your own inconsistencies. You can start making decisions without any fear of unconscious bias.

For example, many employers are biased against hiring employees who have significant gaps in their resume. This is harming a huge portion of the population who lost their jobs, often through no fault of their own, at the beginning of the Great Recession. Predictive analytics has now shown that this attitude is actually costing companies money.

Carl Tsukahara of Evolv writes:

It’s now recognized that the use of predictive analytics can surface powerful conclusions from disparate data sources that can, in turn, serve as the catalyst to foster change in business culture, improve hiring and management practices, and enable more Americans to find gainful employment in fulfilling roles. In my own experience at Evolv, just one of the harmful hiring biases we’ve used predictive analytics to debunk is that “People who haven’t worked recently aren’t viable candidates.” Our technology platform looked across millions of data points on employees across our customer network to prove that the long term unemployed perform no worse than those without an extended jobless spell and have empowered our clients (including several of the companies that supported this week’s legislation) to hire those candidates using a predictive score based on this same technology. We hope this finding in particular helps that 32 percent get that interview, that call back – that chance to show employers that they too, can be great additions to a team.

Wired.com

Some 300 companies are making significant changes in response to these findings, and they are seeing a benefit. According to the above-referenced article, Xerox was one of these companies. Changing their policies in response to these findings resulted in a 20% reduction in their attrition rate, which in turn saved the company a great deal of money.

So what’s the takeaway for you, and your business? Well, you’ve already gotten the benefit of someone else’s predictive analytics project today: you know that you can hire the long-term jobless without creating any problems for your business. You might even solve some.

But you can also get a great deal more out of predictive analytics just by recognizing that you can use predictive analytics to challenge your own assumptions. You could be making other assumptions about hiring, about employee benefits, about vendors, or about any other aspect of your business. You may think those assumptions are bringing great results…but does the data support your claims?

Asking yourself these questions takes your business intelligence program to the next level. You begin by diving into the problems you know about. You know you want more sales, so you start there. Challenging your assumptions, however, will grant you a path to the problems you just aren’t aware of yet–problems that are costing you time, costing you money, and costing you your next star employee.

Data Mining Webinar

Learn How to Get Predictive Modeling
Off the Ground and Into Orbit
1 Hour Live Interactive Event

Why Train With TMA?

Determine whether TMA training is right for you, and learn why TMA is truly the best option for live classroom analytics training.