Monthly Archives: January 2017

50. Analytics in Distribution, Theories, Bias Inefficiencies and Courage

Analytics Without Upside Theories Fizzle

Don’t use analytics in distribution to grind existing information finer and faster. You will get interesting, but non-actionable data. Start instead with an improvement theory. Then, build an analytical model to validate an improvement theory for your distribution. You will find insights to exploit and can track subsequent change experiments with new metrics.

Distributors, for example, have a mix of very profitable and unprofitable items, picks, orders, and customers hiding within averaged-out, aggregate financial numbers. Instead, create a cost to serve (CTS) model to expose the big profit cross-subsidies and then pursue a new metric like: make 100% of customers profitable.

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49. Breaking Out of a Commodity-Hell Mindset

Data from the past 15 years of trade association PAR reports show 90% of distributors have averaged poor pre-tax returns on total assets (ROTA). Furthermore, the same top 5% distributors average 3-4 times the returns of the bottom 90%.  Probably,  same channel, same commodities, just much better results. This is a Commodity-Hell Mindset.

But, the bottom 90% aren’t slackers. We can assume these participants are:

  • Smart, conscientious, persistent and at least somewhat ambitious. Otherwise, why would they keep filling out the PAR surveys?
  • Best Practice seekers (at least from a financial-management perspective)
  • Members of the associations that sponsor the surveys, so presumably staying channel savvy
  • Members of a buying group (if channel appropriate) to remain efficient

Continue reading 49. Breaking Out of a Commodity-Hell Mindset

48. A Catalytic Financial Survey Ratio

As I was doing prep work for a speech to the Health Industry Distributors Association (HIDA), I noticed something interesting in their Members’ Financial Survey. The survey showed a three-year trend for gross margin dollars per full-time equivalent employee (FTEE), or service value productivity per employee.

Though channels do vary, for HIDA distributors the average gross margin dollar figure per FTEE for the last three years has been about $135K/FTEE. However, in 2015 the best performer in each of three sub-groups showed 16%, 60% and 90% higher gross margin per FTEE than the average.

Imagine what your business could do if service productivity was 50% above the average. You might be able to provide premium job-pay, job security, career growth and you would have growth-capital profits to reinvest. The best stakeholders would besiege you.

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47. Insight Into the NAED 2016 PAR Report

Financial numbers alone offer scant profit improvement insights. For real improvement, you must develop a theory for how to improve service value and/or cost effectiveness and then create and capture new metrics to test your theory. This gives you the data to act on what is working. Amazon, for example, has roughly 500 proprietary metrics: 80% are related to customer value improvement.

However, the National Association of Electrical Distributors (NAED) industry overview PAR report does provide some helpful ratios. Insight into the NAED 2016 PAR report can help you understand how to improve your profit.

Continue reading 47. Insight Into the NAED 2016 PAR Report