August 19, 2017


















The Professor, Policeman, President, and Our Random (

Article 4.12

 

Fast Heroics For Random Events at Strategic Accounts

 

What are the odds behind the scenario that led to “the beer summit” for: President Obama, VP Biden, Prof. Gates of Harvard, and Sgt. Crowley of the Cambridge (MA) Police Department on July 30th, 2009? Quick damage control (a “heroic recovery”[1]) followed by creative follow up (heroic acts) by this group may yet turn a bad-luck, negative event into a positive story.

 

How many good and bad luck, long-odds stories happen every month (especially during economically turbulent times) within the top 100 biggest, best accounts that could matter for our company? If we could identify them faster than our competitors could we:

·          jumped on our competitors’ unlucky fumbles;

·          heroically recovered our own fumbles; and

·          proactively performed extra-help, heroic acts within these accounts?

How much incremental (“delta”) profit-contribution swing could we generate on a monthly basis? With these questions in mind, here is an early-warning, customer-retention, reporting system that one distribution company developed.  

 

Customer Profitability Analysis: Different Views x Five More Analytical Steps

A distribution chain with thousands of active customers used Waypoint Analytics’ “quantum profit service”[2] (QPS) to first roll-out the use of Waypoint’s “5 x 5 Sales Force Dashboard”[3]. This analytical, tracking and teaching tool quickly got the entire organization focused on “profit improvement plays” for 3 small groups of high-profit-improvement-potential accounts: “1) core, 2) super-losers and 3) target/gazelles.

 

The report also includes the five accounts within each territory (as well as branch and company-wide) that have increased or decreased the most in actual “profit before interest and taxes” (PBIT) in a month-over-month comparison. Why the big, “delta-pbit” swings in these accounts? Are there hidden, random events (fumbles) causing these abrupt swings? What analytical and action steps could any distributor take to answer these questions?  

 

In this case study, the company had initially done (step one) customer profitability ranking reports by: total company; by branch; and by sales territory. These results were then (step two) re-formatted into the 5 x 5 dashboard reports.

 

Step Three: Compare the PBIT for each account for the last:

a. Month v. the month prior on a ranked basis (the top five up and down accounts were already fed into the 5 x 5 dashboard for each operational level (rep; branch; company)

            b. Quarter v. the quarter prior on a ranked basis

            c. YTD v. the same X months in 2008 on a ranked basis

 

In each of these reports, the customers were ranked from the most positively up in delta-pbit to –at the bottom of the report – the biggest down (negative) delta-pbit. The cumulative numbers for the top and bottom 5% of accounts, both up and down, were surprisingly large. There was a lot of unseen turbulence going on in the account portfolio that was hidden by the financial numbers which averages the extremes out. The good news was that the big losses at the bottom were largely offset by the gains at the top. The bad news was that the potential opportunity stories behind the big delta-swings in these accounts were hidden by running the business with financial reporting numbers, because they were easily available.

 

By varying the number of trailing months for these delta-pbit reports, different patterns and insights emerged. The month-over-month ranking report was the most sensitive to abrupt changes in customer buying patterns. Digging deeper into the “whys” revealed that many of the “big swings” were quickly excused as: lumpy timing of order shipments and mis-billings that were reversed with credits. These accounts averaged out to no big changes in the quarter over quarter reports. A smaller group, though, still required deeper analysis to perhaps uncover random win-or-lose, account-share stories.  

 

The year-over-year reports, when summed up, revealed which sales reps were doing the best job of selling and installing more profitable (replenishment systems) relationships within their territories in general. Before stressing “delta- pbit” with the sales force, two thirds of the territories were actually losing money for the company! Within a few months of launching a “lead (super-losers) accounts into gold” program, some of the biggest PBIT gains at the top of reports were from former, big losers that were now close to break-even or even profitable.[4] And, the company was planning to experiment with a few reps on changing incentive pay to delta-pbit instead of gross margin dollars which had little-to-no correlation with actual cost-to-serve and PBIT for each account.

 

The 90%+ of the accounts in the middle were just trending along with the general economy, industry and company numbers for one or more of the following reasons:

1.      They were so small that anything they did (plus or minus twice their sales volume) wouldn’t make a delta-pbit difference big enough to get to the top or bottom of the report. Many were chronically-small, losing accounts for which the cost of the services provided exceeded the margin dollars that they generated.[5]   

2.      Many of the accounts were non-innovating, creatures of habit that kept buying the same stuff from the same suppliers on a close to profitless (for the distributor) basis.  

3.      Most customers hadn’t had a long-shot significant event that had consequences for competing suppliers.   

 

Step Four: Management then held meetings with each rep to do a drill-down analysis on the few-per-territory, big, delta-pbit swingers. Additional insights were often gathered from inside reps and purchasing people as needed. The goal was to keep asking “why” and “how” questions until either the team had a confident, total understanding for the delta swing or had (step five) specific questions and action steps for visiting each account to find out what exactly was behind the big swings.

 

ASSUMPTIONS BEHIND THIS “FAIL FORWARD, FAST” EXPERIMENT?[6]

1.      If anyone at the company had inadvertently done anything to upset a customer who  then switched business to create a big month-over-month drop, then the quicker management got out to visit the account to – listen, learn, apologize and execute a heroic recovery – the greater the odds for turning a negative into a positive. Customers often remember and value more our quick, gracious recoveries than our consistent, taken-for-granted, perfect service, because mistakes get 120% of a customer’s emotionally-charged attention rarely satisfied by a heroic recovery. 

2.      If a customer had a big, inexplicable delta positive, then the quicker the company could know the whole story behind the “lucky event”, the better and quicker it could adjust to make sure that the new business opportunity was well-served. New big demands from customers were, for example, often met with weak fill-rates or improper execution of necessary special pricing agreements.    

3.      Lessons learned from quick-investigation visits could lead to new ways to not just remedially react to lucky and unlucky account events, but to proactively improve systems, metrics and in-house education to further maximize the upside events and minimize the downside ones.

4.      At the very least, each visit should win from the customer “no-problem-but-thanks-for-your-concern” goodwill points. 

 

RESULTS/CONCLUSIONS

 

Our case study distributor got immediate, big benefits from this new program and confirmed that:

1.      Random good and bad luck scenarios do happen. If a company has enough accounts, then long-shot stories at high-leverage accounts will happen every month.

2.      Because distribution is a variable cost business, very few customers actually have the potential to generate big, delta-pbit swings. To have the entire team know who these accounts are to do both proactive, extra-hustle, “heroic acts” and super-fast, heroic recoveries makes a huge difference in year end retention/defection PBIT between competitors.

3.      “Delta-PBIT Swing Management” is a new skill/opportunity that can only be done with the right quantum profit tools, insights and change programs. Waypoint provides the total QPS solution. Check them out; request a management-team, on-line demo.
www.waypointanalytics.info

 

 

 

©Merrifield Consulting Group, Inc., Article 4.12

 

D. Bruce Merrifield, Jr.



[1] For more on the economics of “heroic recoveries” read the article at this link: http://www.merrifield.com/articles/3_5.asp

 

[2] www.waypointanalytics.info; inquire about free webinars

[3] More on 5x5 selling and report screenshots: http://www.merrifield.com/exhibits/Ex57.pdf

[4] For more on “lead to gold” transformational ideas see: http://www.merrifield.com/articles/4_10.asp;

[5] This strata of accounts needs a “wholetailing” model: see http://www.merrifield.com/articles/106commentary.asp (third topic)

[6] “Think Big, Act Small with Brilliant Mistakes” http://www.merrifield.com/articles/2_34.asp