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”) 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
jumped on our competitors’ unlucky fumbles;
heroically recovered our own fumbles; and
proactively performed extra-help, heroic acts within these
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
chain with thousands of active customers used Waypoint Analytics’ “quantum
(QPS) to first roll-out the use of Waypoint’s “5 x 5 Sales Force Dashboard”. 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
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
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,
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.
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.
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)
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.
THIS “FAIL FORWARD, FAST” EXPERIMENT?
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”
Our case study
distributor got immediate, big benefits from this new program and confirmed
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.
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.
Consulting Group, Inc., Article 4.12