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4 | 2014
The Magazine of WorldatWork©
The Art of Sales Compensation
Cost Modeling
How to Avoid Unexpected
Year-End Budget Breakers
By Christopher Nagle, The Alexander Group Inc.
©iStockphoto.com/AnnaNem
What’s worse than
overestimating plan payouts?
Underestimating.
One question that a vice president of
sales does not want to hear from the CFO
is, “How did you manage to overspend
your sales compensation budget while
only achieving your sales goal?” Unfortunately, the vice president of sales and
the CFO hold this (sometimes) prickly
conversation too late in the plan year.
There is very little anyone can do at that
time to remedy the sales compensation
budget overrun looming at the end of
the year. Likewise, underspending the
sales compensation budget has its own
implications, such as frustrated sales
personnel and embattled first-line sales
managers. Sales management needs to
correctly cost the incentive plan at the
outset of the plan year. Specifically, this
analysis needs to focus on the primary
factors that drive the estimated sales
compensation budget. To be complete,
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Those responsible for cost modeling
often overlook the cost impact of
a cost model must address all four of
these factors:
❙❙ Payout curves
❙❙ Adjusted value multipliers
❙❙ Expected performance
distributions by metric
❙❙ Open territories.
Missing the mark on any one of
these four factors can cause unanticipated variance either below or
above expected budget. A cost model
that incorporates and links all four
components will ensure costs are
fully aligned with the budget.
Payout Curves
The payout curve for each metric
describes the payout schedule
depending on dollars/units sold or
quota achieved. A series of slope
calculations construct the payout
curve by dividing payout opportunities by the performance ranges, such
as between threshold and target and
Figure 1 target and excellence. As an outcome,
for example, the payout curve may
specify a 60 percent payout of target
incentive for a 50 percent quota attainment. After constructing the payout
curve, calculate both individual and
aggregate costs based on expected
performance levels by individual.
Construct a cost model to reference
the expected performance for each
metric and then return the associated
payout for that metric based on the
payout curve. This approach provides
the flexibility to modify the payout
curve and recalculate, in real time, the
individual and aggregate costs. For
example, the cost of Payout Curve
A will be less than Payout Curve B
because it has a shallower slope. (See
Figure 1.) Modify the payout curve
multiple times to obtain real-time estimated costs. Done correctly, the model
will enable an interactive session
with the design team to view the
| Payout Curve Illustrations
Payout as a Percent of Target Incentive
360%
Payout Curve A
320%
Payout Curve B
280%
200%
160%
100%
75%
60%
0%
Source: The Alexander Group Inc.
46 | workspan april 2014
Quota Attainment
300%
actual cost impact based on various
defined payout curves.
Adjusted Value Multipliers
Those responsible for cost modeling
often overlook the cost impact of
adjusted value modifiers. Adjusted
value multipliers change the payout
value of a sale based on a factor
added or subtracted within the plan
design reflecting management’s sales
preferences. For example, management may favor one product. Instead
of having an incentive par value of $1
for each dollar of sale, the adjusted
value might be $1.20, providing a
20 percent premium for the sale of
the preferred product. Likewise, less
valuable products might have an
adjusted value of less than $1. These
adjustments can reflect strategic
intent or profitability of the product
or account. The cost model needs to
account for these adjustments.
The Adjusted Value Multiplier Index
(AVMI) adjusts financial quota attainment (up or down) based on the
different sales credit value of each
product. Use the AVMI to understand
how the adjusted value multipliers
have an impact on sales compensation payouts versus actual financial
performance. Use the AVMI to adjust
individual quota attainment based
on the adjusted value multipliers.
Figure 2 illustrates how to calculate
the AVMI. Note that each product has
a different adjusted value multiplier.
(See red cells.) Based on the adjusted
value multipliers and the expected
aggregate annual financial forecast by
product type, calculate the AVMI. If
the AVMI is more than 1.00, costs will
increase. Conversely, an AVMI that is
less than 1.00 will lower plan costs.
Management can improve the accuracy of the
cost model by applying the payout curve to the
Construct the model to allow
changes to the adjusted value multipliers (cells in red). It’s best to set the
adjusted value multipliers to keep the
AVMI within an acceptable +/- 0.05
variance of 1.0 (0.95 to 1.05).
The next step is to adjust the
expected individual quota attainment
based on the AVMI. For example,
Sales Rep 1 achieved 100 percent
attainment of his/her financial quota.
However, the 100 percent attainment
is adjusted (up in this case) based on
the previously calculated AVMI of 1.05
to 105 percent. Sales compensation
payout will be based on 105 percent,
not 100 percent quota attainment. This
will result in a higher incentive payout
increasing overall plan costs. Note:
This illustration assumes that each
individual has the same distribution
of product sales as the company. In
practice, product distribution results
will vary by salesperson. For example,
while the company’s overall AVMI is
1.05, at a territory level, it will vary
by salesperson based on the mix
of product opportunities.
The value of the AVMI and the
shape of the payout curve can have a
significant impact on cost. Knowing
the value of the AVMI and the shape
of the payout curve will allow the
cost model to better forecast actual
payouts relative to budget. In this
case, two options exist to bring these
increased estimated costs in alignment with budget: Reduce the AVMI
or lower the payout curve slope for
performance greater than 100 percent.
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workspan.
Expected Performance
Distribution
To improve the cost model further,
incorporate the next factor: expected
performance distribution for each
performance metric. There are several
ways to determine the expected
performance distribution by metric.
A typical approach is to use historical
data. This assumes historical performance will hold constant in the future.
The historical performance distribution
will highlight the shape and dispersion
of the expected performance.
Management can improve the
accuracy of the cost model by
applying the payout curve to the
expected performance distribution.
(See Figure 3 on page 48.) Assume
the metric has a bimodal distribution with a 50 percent cluster of
sales personnel below quota and the
other 50 percent of sales personnel
performing in a cluster above quota.
(See blue performance curve.) The
red payout curve represents the
current incentive formula. However,
in this scenario, nearly 50 percent of
the plan participants will not earn an
Figure 2 incentive because they are below the
threshold. This will produce incentive
payouts below budget. One approach
to correct this under payout is to
lower the threshold and reduce excellence payout levels to account for the
expected bimodal performance distribution. (See green payout curve.)
A final point on using historical
data: Typically, the historical performance will not equal 100 percent
in aggregate — it might be higher
or lower. To correct for this, index
the data to shift actual individual
performance to obtain 100 percent
aggregate attainment. For example, if
last year’s overall performance was
105 percent of quota, shift the distribution to the left by adjusting each
individual attainment level by 0.952
(100 percent ÷ 105 percent). The shape
of the curve stays constant, but is
indexed from 105 percent to establish
100 percent aggregate attainment.
If historical data are not available
(either it’s not going to be the same in
the future or there is no data because
it’s a new product), then the cost
modeler should obtain input from sales,
| Adjusted Value Multiplier Index Illustration (AVMI)
Adjusted Value
Multiplier
Forecast Percentage of
Annual Sales by Product
(Must Sum to 100%)
Adjusted Value Multiplier
Index (Weighted Average)
Product A
1.15
50%
57.5% (1.15 x 50%)
Product B
1.10
20%
22.0% (1.10 x 20%)
Product C
0.95
20%
19.0% (0.95 x 20%)
Product D
0.65
10%
6.5% (0.65 x 10%)
100%
105%
Product
Type
Total
AVMI
1.05 (105% ÷ 1)
Source: The Alexander Group Inc.
april 2014 workspan | 47
marketing and finance management on
the expected performance distribution.
Additionally, performance distribution will vary by metric. For example,
mature products will typically have a
more normal distribution with a low
standard deviation. Conversely, newly
launched products will have a much
more diverse distribution, possibly a
normal distribution, but with a high
standard deviation. Also, team metrics
will have a lower standard deviation
because the quota is a roll-up of
many data points.
Remember, anticipating a normal
distribution with a low standard deviation will yield far different cost results
from a normal distribution with a
high standard deviation or a bimodal
distribution. Thus, it is advisable to
run multiple cost scenarios based on
different performance distributions.
Open Territories
Employee turnover will temporarily
create unfilled territories. Unfilled
territories will reduce plan costs
because there is no salesperson to
receive sales credit.
The best predictor of unfilled territories is to analyze historical turnover
Figure 3 rates by sales role. Additionally, solicit
input from sales and field human
resources to understand if there are
any plan changes or economic factors
that may require adjustments to
turnover rate assumptions.
Once the turnover rate and the
estimated duration of the empty
territory are determined, calculate
the Open Territory Index (OTI).
Use OTI to adjust overall plan costs
(down) based on expected employee
turnover and open territories. Use
this calculation to determine the
OTI: (planned FTEs - employee
turnover FTEs - unfilled territories
FTE) ÷ planned FTEs.
Once the OTI is calculated, adjust
plan costs. For example, assume
aggregate plan costs are $2.8 million
based on the prior three factors
(payout curve, AVMI, quota distribution). Assume an OTI of 0.90 based on
the equation above. The final adjusted
cost — applying OTI — would be
$2.52 million ($2.8 million x 0.90).
Incorporating All Four Factors
As illustrated, getting one cost adjustment factor correct is not enough.
All four factors affect actual payouts,
| Payout Curves Modified Based on Expected
Quota Performance
600
300%
Bimodal performance distribution
Current payout curve 1
Proposed payout curve 2
250%
400
200%
300
150%
200
100%
100
50%
0
0%
0%
20%
40%
60%
80%
100%
Quota Attainment
Source: The Alexander Group Inc.
48 | workspan april 2014
120%
140%
160%
Percent of Target Incentive
# of Salespeople
500
including the payout curve, adjusted
values, quota distribution and open
territories. For example, expect the
following per variable:
❙❙ Shape of the payout curve.
High threshold and excellence
levels lower costs. Conversely,
low threshold and low excellence levels can increase costs.
❙❙ AVMI. If the AVMI is more
than 1.00, costs will increase.
Conversely, an AVMI that is less
than 1.00 will lower plan costs.
❙❙ Quota performance. Normal
distribution and low standard deviation lowers costs, while a normal
distribution with a high standard
deviation may increase costs.
❙❙ OTI. High employee turnover
and unfilled territories will
lower costs, while low employee
turnover and unfilled territories
will result in higher costs.
Thus, when building your model,
ensure you will have the ability to:
1 | Adjust the payout
curve inflection points.
2 | Change the adjusted value multipliers by product or account to
reduce or increase the AVMI.
3 | Modify the quota performance
from normal low standard
deviation to normal high standard deviation or bimodal.
4 | Increase or decrease the total
cost based on the OTI.
Incorporate all four factors in the
cost model to significantly reduce and
possibly eliminate the risk of underor overestimating plan payouts.
Christopher Nagle is vice president
and region manager at The Alexander
Group Inc. in Atlanta. He can be reached
at cnagle@alexandergroup.com.
resources plus
For more information, books and
education related to this topic, log
on to www.worldatwork.org and
use any or all of these keywords:
❙❙ Sales compensation
❙❙ “Cost modeling”
❙❙ Payout curve.