144. Baseball’s Adoption of Analytics v. Distributors

Red Sox ‘02 v The Orioles ‘19  

Analytics have swept through Major League Baseball (MLB) over the past 17 years. The Oakland A’s got first analytical results. But, the Boston Red Sox were the first to go big in 2002. John Henry, the new owner, was a believer. He had gotten rich by trading commodities with his own invented analytics.   

Results through 2018? The Red Sox have won four World Series titles. MLB batting averages have dropped a needle-moving 25 points due to innovative changes. And, the unchanging Baltimore Orioles lost 115 games in 2018: 3rd worst record in history.  

But, the Orioles have awakened! Last November, they hired analytical talent away from two best-practice clubs (Astros and Cubs). Will the Orioles be able to catch up to and then innovate beyond the still-analytically-advancing rest?  

Are Distributors Adopting Analytics?

The answer depends upon the type of analytics. Most have “financial analytics” that slice, dice, and chart financial numbers for little beneficial insight. Why? Financial numbers exist (by law) to pay taxes and do asset-backed borrowing.  

Financials have (for example) nothing to do with defining, measuring, achieving, selling, getting paid for, and partnering with service value. What are your specific service metrics that are targeted at your most net-profitable customers and customer niches?

Many distributors also have “silo efficiency analytics” to minimize waste within their existing belief-system for doing business. Make sure, for example, that you get every dollar of rebates earned, and don’t underprice any SKUs that typically aren’t price-shopped.

If everyone is doing this incremental stuff, it’s adaptive, table stakes. What is your big, unique edge? What are your breakthrough analytical insights and plays for big upside results?   

Customer and SKU Profitability Analytics?

Fewer distributors have experimented with some level of customer-profitability analytics. And, less than 5% have and use SKU profitability analytics. Why?

Both capabilities require creating “cost-to-serve models”; not a typical distributor competency. Then, big, unbelievable profit and loss cross-subsidies are revealed amongst both customers and SKUs. Big insights requiring big changes for big results! But, who really wants to do big change? Didn’t MLB ignore Sabermetrics’ insights from 1971 on?

Adoption Solutions?

Waypoint Analytics’ cloud service includes cost-to-serve modeling and is quickly available. They now have transformational-change consultants who are rentable by the hour. Get help with a few small wins to break inertia and be on your own way!

Will you be the Red Sox or the Orioles?

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