Category Archives: LIPA

146. Analytics’ Credibility Within Your Firm?

Science Deniers Past and Present

The “scientific method” has enabled all the fruits of modern civilization.

The Scientific Method’s steps are (modified for distributor results):

  1. Observations.
  2. Questioning.
  3. Theories/Hypotheses.
  4. (then) Gather new data.
  5. Do iterative experiments ever smarter.
  6. Uncover Strategic Insights.
  7. Sometimes nail something new and profitable. 
  8. And, Scale it.

Until 1660, when the Royal Society of England was founded, scientists who published discoveries that conflicted with the beliefs of the church or dictators could be burned at the stake. Even today – politicians, churches, economists, CEOs, etc – will undermine any (scientific) facts that get in the way of their agendas (comp plans) or belief-identities. Want to get ahead? Tell these bosses what they want to hear! 

Science-denying leaders have good audiences for their data-free opinions. Besides obedient underlings, surveys reveal that citizens are OK on everyday-science facts.  But, they often struggle with the scientific method process and statistics.

Belief Types: Finance, Sales Relationships and Family-Company Values

Every company is dominated by the voice of finance. Be financially pragmatic. Pay timely taxes. Service debt and meet lender’s ratios. Meet the payroll. Please the auditors. But, what are the blind spots of financial operating assumptions like “buy-low, sell-high, and sell-more”?    

What “observations, questioning, theories, and new analytics” should challenge financial management? Do financial numbers measure the improving effectiveness of leaders, strategy, and the culture and systems that support the strategy? How measurably great and guaranteed your “service value” is for best, most net-profitable, target customers?  

Switching to the sanctity of “relationships that reps have with their customers”. Where are the metrics by which to manage and improve the quality and win-win economic benefits of these relationships?

Family businesses also have beliefs/values. But, to paraphrase Tolstoy, “Happy family businesses are all alike; every unhappy family business is unhappy in its own way.” Have any unhappy, family beliefs to question?

Concluding Questions:

In your company, if scientific method analytics clash with data-free beliefs, what happens? Is the C-Suite open to experiments? Or, do they want “new” data that supports the status quo beliefs and compensation schemes? Big profitable gains come (unfortunately) from big changes to old ways. What will happen to your company, in fast-changing times if scientific method analytics can’t challenge dysfunctional, profit-drain beliefs? For more on scientific, big-change analytics for distributors, be in touch:  bruce@merrifield.com

145. Innovate at 32 Degrees

Needed: Profitable Growth and Digital-Commerce Re-Modeling

Studies trumpet that: 60-80% of outstanding companies’ profitable growth comes from “innovation”. Could you use some bigger profits and more agility? And, all legacy channel players need to innovate to meet the developing digital desires of millennial B2B buyers.   

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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.   

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140. Channel-Model Innovations Ahead

BIG CHANGES BY 2020+?

Big players (Amazon, Walmart, Home Depot, etc.) are combining many technologies to create the onrushing Cloud Omnichannels to which B2B brands must respond.    

Amazon’s (AMZ) “doorstep-back-to-producers” value-channel is all in the cloud. It incorporates technologies like AI, machine learning, robots, and cobots. And, AMZ has already hugely pre-invested in exploiting 5G bandwidth, instant-startup-clone brands, info-videos with watch-me reward points, last-mile-uber-metro-delivery platforms, voice commerce, drones, fintech, blockchain, etc.      

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136. SELL WIN-WIN, LOWER PRICING (?)

PRICING EFFICIENCY ISN’T PRICING EFFECTIVENESS

Practice good-pricing hygiene. Don’t underprice SKUs or customers if they will continue to (happily) buy from you at higher prices. But, consider also the positive trade-off of lower prices in exchange for larger average order-size buying. What are your general buying and selling incentives for increasing order size?

CASE STUDY ON ORDER-SIZE ECONOMIES

For 2018, a $100MM contractor-supply distributor had roughly 4000 active accounts. More facts:   

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135. Fix Your CRaP Items and Their Root Causes

AMAZON’S WAR ON CRaP

Amazon’s analytics can identity SKUs on which they Can’t Realize a Profit” (CRaP). Even with their improving, world’s best fulfillment and last-mile delivery costs, they can’t cover costs on items lower than $15 per pick/order.

AMZ’s fixes to date?  

Continue reading 135. Fix Your CRaP Items and Their Root Causes