Category Archives: Profit Analytics

98. “Your Margin is My Opportunity” (Jeff Bezos)

AmazonBusiness, Big Data, Distribution Industry Sales, Index, Line Item Profit Analytics, LIPA, Profit Analytics, WayPoint Analytics

Why Are Your Margins Too High v AMZ’s?

Your margins must cover your channel cost structure which was built for bygone days. Most channel costs evolved (from WW2 on) to push true-new products to first-time buyers. Cold calls (requiring product-education) required both factory and distributor reps to create demand. Both sets of reps got paid roughly 5% of their respective sales. Today (70 years later), most channels still have two sets of reps costing about the same. What other elements of your push-channel costs will AMZ threaten?

2018 Legacy-Channel Challenges:                    

  1. The US consumer-society lifecycle is mature with too much global supply. Power has shifted to customers. And, AMZ owns the increasing numbers of Prime customers. Brands must go to where the eyeballs are and sell them the way they want to buy.
  2. 80%+ of distributor product sales are for equally-excellent commodities (no demos needed)
  3. 90% of sales are rebuys from experienced customers (fewer cold calls)
  4. The internet makes all product – information, availability and pricing – 24/7 available. As digital information grows, product knowledge help from local reps drop.
  5. Mark-ups for full-lines of SKUs create profit/loss cross-subsidies. Average-pick size and turns are ignored. Buy: a popular $500 piece of equipment at 20% margin and some fittings for $1 to $3 each at a 40% margin. The equipment’s $100 of gross profit covers: its activity costs; the losses on fittings; and residual company profit.
  6. Mark-ups covering bundled services are not customer-centric. Customers get an assigned rep whether they want them or not. If reps were unbundled for fees and customers got 5% rebates for buying on their own, what would happen? Without unbundling, Millennials will web-room you on the big-price, popular and most profitable items on AMZ for less. They will: check the $500 equipment price at AMZ. Sees savings of $X. Spot buy it. Then, order the little-dollar picks (net-profit losers) from the distributor.
  7. And, the Perfect Clones of most profitable items are increasing at AMZ. Clones – with great information content, reviews and prices – will steal share from top brands not there. Clones can skip channel development costs and go right to AMZ’s unlimited cyber-shelf space using Fulfillment by Amazon.
  8. Loyalty to – brands, distributors and reps – will continue to erode.

Unless What?

Factories and distributors share SKU profitability analytics to solve cross-subsidies and rethink their respective service bundles. And, factories get on AMZ to win the content management war against the clones. For more: contact me for a free, virtual, SKU analytics session.     bruce@merrifield.com

96. How to Be Strategic on Channel Rebate Management

Big Data, Cost-to-Serve Math, Distribution Strategy, Index, Profit Analytics, WayPoint Analytics

Channel partner incentives, collectively and imprecisely known as rebates, are huge, addictive, and problematic programs for distributors. One 2012 survey estimated total channel incentives in the U.S. to be $55B. That’s 80% of the reported $69B in total channel management budgets. A Silicon Valley survey reported that the typical factory respondent ran an average of 21 incentive programs annually with an estimated overpayment of 6%.

Twenty-one incentives programs annually? Sure! Cash bribes get fast attention. Competitors understand indirect price cuts and can quickly follow, tweak and escalate with their own programs. But, without effective plans for disciplining, tracking—and in some cases exiting—these initiatives, what happens? Factory list prices generally keep rising as backend channel incentive checks multiply. Continue reading 96. How to Be Strategic on Channel Rebate Management →

95. Rusty Staub and Your Unequal, Margin Dollars

Big Data, Cost-to-Serve Math, Index, Line Item Profit Analytics, LIPA, Profit Analytics, WayPoint Analytics

UNDER-VALUED RUSTY: RIP

Daniel Joseph (Rusty) Staub passed on March 29th at 73. Rusty (Le Grand Orange) played 23 years in baseball’s major leagues retiring in ‘85. His career stats: batted in 1,466 runs; averaged .276 with 292 homers and 2,716 hits; and walked a spectacular 1,255 times. With walks, his career on-base percentage (OBP) was .362. He didn’t swing at bad pitches.

Rusty, a champ admired on and off the field, did not make the Hall of Fame. Baseball beliefs back then were still blind to the value of Walks. In 2000, the same Analytical Ignorance allowed the Oakland A’s to “buy runs to win games” cheap. They snagged free agents with superficial flaws, but high OBPs. (Well told in Moneyball: both the book and movie). Continue reading 95. Rusty Staub and Your Unequal, Margin Dollars →

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

AmazonBusiness, Cost-to-Serve Math, Distribution Industry Sales, Distribution Strategy, Index, Profit Analytics, WayPoint Analytics

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 →

91. Your People Bets Are Only as Good as Your Beliefs

Big Data, Concierge Customer Service, Distribution Strategy, Index, Profit Analytics, Service Value Innovation Guidelines, WayPoint Analytics

Imagine a distributor that has 10 outside Reps making 4.5 calls per day at an all-in cost per call exceeding $100. They must believe that the costs of these rep calls are worth the benefits. So, what cluster of beliefs guides those daily bets that add up to over $4500?

What beliefs lie behind your rep call cost bets?

Here are two belief clusters that serve as poles on a continuum. Where do your beliefs fall?

We’re supply-chain value creators

  1. All our reps are certifiably excellent at knowing which are the highest net-profit potential accounts
  2. All our reps plan and proactively pitch (with team help) the best, win-win solutions to these accounts that deliver a one-stop shop array of SKUs throughout a customer’s business and are executed with perfect, basic service metrics tuned to the customer’s needs
  3. These solutions lower the total procurement cost of the customer’s replenishment process, while boosting their uptime productivity using our goods and lowering our cost-to-serve expense as a percent of sales
  4. We also take care of all (new) product knowledge needs customers may have
  5. Our goal is to secure a bigger, win-win share of spend, if not a 100% partnership
  6. When we partner with the best growing customers, they grow us
  7. Our sales (and rebates) grow faster than industry averages due to customer-centric, service-value innovations for replenishment of commodities (which now comprise 90% of our sales)

We maximize “relationship value” to get economies of sales

  1. Our “good” reps make just-in-case, regular calls to befriend customers and react to their needs (often economic concession demands)
  2. More reps secure more active accounts
  3. Our goals are to push products to more accounts to grow sales, margin dollars and rebates.
  4. With all operational costs (seemingly) fixed in the moment, incremental GP-dollars will flow increasingly to the bottom line. These profits will hopefully grow faster than sales. (But, they haven’t!)

Relationship beliefs stopped working long ago

Financial survey data shows years of low returns for 90% of distributor participants. Isn’t it time to update your beliefs and analytics to improve your odds for better returns on your rep-call bets?

Conclusions

Business is like poker. You can’t have perfect information or consistent good luck. The winners are statistically a few percent better at deciding when to fold or hold; and at winning the hands they play.

Focus your best people-talent bets on creating more value for your biggest net-profit growth potential customers. Customer/SKU profitability analytics will upgrade your beliefs and improve your betting odds.

How? Contact me for a free, desktop session.

89. Get an Outrageous ROI from Analytics

Big Data, Index, Line Item Profit Analytics, LIPA, Profit Analytics, WayPoint Analytics

Most distributors have analytics software, but few get needle-moving results. So, what’s missing?

A case study’s best practices

A recent Harvard Business Review blog reported on a company that took their analytics seriously. Here’s what they did:

  • Created a separate analytics business unit that reported to the C-suite
  • Staffed the new business unit with young, ambitious people from outside the industry
  • Charged the team with achieving at least a 10X ROI for the unit’s budget cost
  • Targeted customer-centric results for the operating companies
  • Trained the operating companies to take over and improve upon the new initiatives
  • Incented both the analytics and operating folks with the same profit increases

The first year the new unit hit 46X their budget. Now, with all the operating companies begging for the no-charge analytics help, the unit hit 106X in year two and 200X in year three. Continue reading 89. Get an Outrageous ROI from Analytics →