Use Analytics To Solve Root Cause, Not Just Symptoms

Earlier this week I shared an article with a colleague entitled Can Analytics Helps Colleges Graduate More Students?, by Tanya Roscorla. The article presented some excellent case studies where universities are leveraging analytics to test innovations and help students identify the best path towards course completion and graduation.

While she appreciated the article, I found her response compelling (and obviously the inspiration for this post). She noted that the article stated “Colorado universities send about 20,000 people a year to community colleges because they aren’t ready for college-level math and English. But they’re losing many of these students in the process.”

Her response: “It’s interesting that people see this as a problem with colleges and universities – why are high schools graduating people who aren’t ready for college-level math and English?”

The question is appropriate and indicative of a much larger issue that I won’t discuss here – what are the roles of high schools, lower schools and parents in terms of getting kids ready for college?

But she got me to thinking…it’s great that Texas, Hawaii, Maryland are others are leveraging analytics to help students perform better once on campus…but isn’t that simply working on the symptoms of a larger problem and not really understanding or solving the root cause? And if we don’t solve the root cause, we’ll continue to mitigate the symptoms perpetually.

Let’s think about this in terms of a recent business example. A retailer reported sales at a particular store that did not meet expectations – it missed it’s annual sales target by over 20% (approximately $1M). Initial inquiries looked at the usual suspects…lack of traffic, ineffective marketing, insufficient labor, weather, etc. Sound familiar? And while each of these likely played some role in the missed forecast, after further inspection and questioning, a senior executive found the root cause – the initial forecast was flawed! It used a predictive model based on a different geographic area that was not comparable. So while the retailer could (and should) do everything it can to help improve traffic, marketing, labor, assortment, etc…the reality is that the store was meeting expectations based on the actual geography and demographics.

Both the business and education examples above cause emotions to run high – people are passionate about the topics and have vested interests in the outcome. Roscorla closes her article with this keen insight from Mark Milliron, co-founder and chief learning officer of Civitas Learning:

“One of the most important things to keep in mind when dealing with analytics and interventions is to balance out the hype and the skepticism. True analytics believers promise too much and don’t deliver enough, while skeptics fight back against innovation and change. As a result, true believers and caustic cynics hijack important conversations, which are complicated and require tough mindedness…[organizations] need to calm the caustic cynics, temper the true believers and create a space for learning analytics to move forward to the next level.”

So use analytics to identify symptoms and trends…then ask the 5 Whys (see cartoon below) and use analytics some more to get to the root cause…then make a data-driven decision to solve your problem.

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