I just read a synopsis of Brad Pitt’s latest movie “Moneyball” where he plays Billy Beane the general manager of the Oakland As who builds a winning team with the lowest players’ salary budget ($41 million vs. 125 million for the New York Yankees) in all of baseball in 2002. Why did Billy do this? The Oakland As didn’t have the money to pay for big name players, so Billy needed to find a different way to field a winning team.
Beane did so by downplaying the typical statistics that baseball teams used to select their players (stolen bases, runs batted and batting average) and looked for and found, through vigorous analytics called Sabermetrics, new and better metrics (on-base percentage and slugging percentage) that he believed were better indicators of success.
Beane also discovered through his Sabermetrics, that any polished college player was worth two high school draftees whose metal hadn’t been tested over a long period of time. Well you guessed it; Billy changed the face of baseball with his Sabermetrics. Now every major league baseball team employs Sabermetrics to get an edge on their competition, all because Beane decided to look for new analytics that could help him improve his team’s performance at the lowest cost. This wouldn’t have happened if Beane hadn’t broken with baseball’s “we have always done it that way, so why change tradition”.
I think we in the healthcare supply chain can learn a big lesson from this “Moneyball” story. Traditional thinking won’t give you the breakthrough savings and operational performance you have been looking for in your supply chain operations. Only by taking the road less traveled will you be able to break with tradition to develop better ways of doing things.
For example, every hospital I know of uses inventory turn-over rates as their method of determining if their inventories are in balance. However, this number in and of itself only tells part of the story. 12 years ago at my firm, we started using the ratio of inventory value to related activity that drives inventory cost (e.g. test, procedures, clinic visits, etc.) to determine more precisely if a hospital’s inventory is in control. We did so because this new metric pinpoints if you are buying more stock than you need vs. holding more than you need.
Reagent purchasing in laboratories is a classic example of this concept in action, since labs buy their reagent in lots, not by reorder points, which skews traditional inventory- turn rate calculation. There is a big difference in these two metrics, one will tell you that an inventory is bloated, while the other will tell you what the inventory level should be based on the department’s purchasing activity. It’s just a more meaningful, accurate and actionable measurement then inventory-turns. That’s why we have broken with tradition.
Back to my point, if we in healthcare continue to use old and tired analytics and then believe they will dramatically improve our supply chain operations, we haven’t really understood what the best indicators are for our supply chain success. We need to keep experimenting, as my firm does, to uncover even better analytics that will turn our data into dollars. This can only happen if you break with tradition and then untiringly look for better ways to collect, analyze, and then interpret your data to improve your performance.
Robert T. Yokl
Chief Value Strategist
Strategic Value Analysis® in Healthcare