Category Archives: Big Data

153. Analytics for Silos to Supply Chains

Invent Your Own Analytical Insights

Analytics software is big news.  But, your richest analytical insights are hiding under foot. To uncover these insights, get curious. Make specific observations about the good and bad activity that you know intuitively exists within your business.  Are these observations symptoms of what underlying root-causes? Write down the questions and theories that arise. Do some customer field research and quick statistical analysis to test and refine your questions and theories. Then, do small, fast, learning-forward experiments to find the golden insights.

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151. Share the Secret: “Profit” Is a Clean Word!

PROBLEM:

Many distributors do not share general financial numbers with all employees on a regular basis. So, new plays and innovation metrics (based on insights from customer and SKU net-profit analytics) can’t be pursued. Too bad! All stakeholder groups would benefit enormously. 

WHY NOT SHARE?

In many of my presentations over the years, I’ve asked roomfuls of distributor principals:

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152. Don’t Misapply: “Keep It Simple Stupid” (KISS)

“Bruce, KISS It!”

For years on the distribution speaking circuit, Polished Pleasers have advised me to: “Make your message simple, appealing, dumbed-down – with memorable sound-bites or key distributor folks won’t listen. Your advice on service-value innovation for net-profitable customers and customer niches is too complicated.  Tell them what they want to hear. (Be an edutainer!)”

Some distributors (along with my own turnarounds) have pursued what I preach for great results. Wins keep you going! But, many distributors are still not suffering enough (yet) to want to upgrade their simplistic, operating, financial beliefs.

The intent behind KISS was not to adopt simplistic notions for success. Simplistic always yields weak, commodity, follow-the-herd returns! What was KISS’s intent? How did it get distorted? What should you do about it? Read on!    

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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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