Category Archives: Cost-to-Serve Math

94. Amazon’s $7 Per Line-Item, Wake-Up Call

AMAZON’S SMALL-DOLLAR-ITEMS: Math and Solutions

Amazon knows warehouse activity costs to the penny. Their 9th generation warehouses may have the lowest, cost-per-pick on the planet. Some stats:

  1. The “click to ship” elapsed time is 15 minutes and dropping.
  2. The average human time input for each order is one minute which includes 15 seconds to pack.
  3. The cost per pick – in the narrowest sense – is 44 cents for a human and 20 cents for a robot.

Continue reading 94. Amazon’s $7 Per Line-Item, Wake-Up Call

92. Tight Labor Market Challenges? Here Are Solutions!

A February 2017 survey by Vistage Worldwide found that 67% of small business owners report a shortage of skilled workers. To try and bridge the gap, 87% have increased recruiting and 60% have boosted wages.

The answers beg more questions

But, what company doesn’t worry about skilled worker shortages, recruiting, and wages? Continue reading 92. Tight Labor Market Challenges? Here Are Solutions!

61. Discussion Exercise: Lessons to Be Learned from Moneyball

The critically acclaimed book turned Hollywood movie, Moneyball, tells the story of the Oakland Athletics baseball team and their industry-changing approach to winning more games per payroll dollar than any other team in history. How did they do this?  By being the first team to use analytical insights in distribution to increase profit instead of traditional player valuations.

The movie has strong messages, and you might be surprised to find they can be applied to your distribution business.  Below are YouTube links to a few of the most important scenes, plus some discussion questions. Watch the clips and add your own questions to spur management team discussion that will help you go beyond tradition and into the brave new world of analytics. Continue reading 61. Discussion Exercise: Lessons to Be Learned from Moneyball

58. Ranking Sales Reps in Distribution by Their Potential to Switch to a Competitor

Many distributors resist vital changes out of vague fears that some sales reps might not like change or its compensation implications. Some fear losing their sales reps in distribution to a competitor and all their loyal customers along with them. Of course, there are many factors that will determine what will happen, including how strong your reps are, whether you can afford to lose a few customers based on the projected new sales, and how many of your customers have integrated contracts. Ranking sales reps in distribution by their loyalty and account profitability is a good place to start.   Continue reading 58. Ranking Sales Reps in Distribution by Their Potential to Switch to a Competitor

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.

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