Daily Archives: April 20, 2016

Trend Analysis: Mantic or Misguided

Trend Analysis, formally defined by Wikipedia as the practice of collecting information and attempting to spot a pattern, or trend, in the information is typically presented by providers of analytics packages as the miracle your organization has been looking for to power your productivity and process improvements. After all, if you can’t use the data you have to get a good sense of how you are doing, how are you going to figure out how you are doing, if you can improve, by how much, and what you should do.

This is true, provided that the trend analysis is statistically reliable, on accurate data, and comparable to a meaningful benchmark. But this is not always the case, and when the trend analysis is poorly implemented or applied to poor data, definitely not the case. In fact, if the trend analysis is not accurate, it will cost the organization precious time, money, and resources and result in considerably worse, instead of better, performance. And even though you don’t hear about it (as the last thing a major provider of analytics solutions wants to do is scare you away from their very complicated, and extremely expensive, solution that is supposed to save you 3X to 7X its annual cost), analytic-based screw-ups happen more often than you think. And if they happen to you, you will be cursing the analytics package until it’s off the asset sheet (and beyond).

the doctor is being dead serious here. Trend Analysis (like dashboards) hide half a dozen serious dangers that can seriously hinder productivity, savings, and even innovation. Half of these are common to internal trend projections and half to external trend projections.

One of the most significant dangers of internal trend analysis is missed opportunities. If an analysis of fulfilment time analysis over the past six months indicates that the organization is likely to continue to hit its 90-day delivery guarantee by at least 3 days, the organization may think that all is fine and well, but not realize that just hitting the 90 day delivery guarantee is costing the organization money. What if the average stock-out rate is 10%, and 6% of that are stock-outs that are less than 40 days. What if the organization could change lanes and carriers and get the delivery guarantee down to 50 days? This could reduce the stock-out rate by as much as 60%, and if this stockout rate is costing the organization 10M a year, that could be a 6M savings overlooked because the trend analysis creates an all-green dashboard.

One of the most significant dangers of external trend analysis is innovation stunting. For example, the trend analysis could show that the organization’s conversion to sustainable energy is outpacing its peers by 5% and think that it is doing great. But what if it has the opportunity, due to its locale, to switch to solar or hydro at a rate that would outpace its peers by 10% and take another 20% off its annual energy bills? Without knowledge of the possible, the analyst could completely miss that innovative opportunity.

But these are only two of the six major hidden dangers that can rear their ugly heads as a result of the misapplication of trend analysis. For a detailed insight into the other four, download the doctor‘s latest white-paper (sponsored by Trade Extensions) on The Dangers of Benchmarks and Trend Analysis (registration required) today. You need to know these inside out before even considering using trend analysis (which, when improperly constructed and improperly interpreted, can be just as deadly and dangerous as a dashboard).