marketing resource allocation: calculating the right number of sales reps
DESCRIPTION
How much should I spend on marketing? How many sales reps do I need? Where should I deploy those resources? Full of graphs and data, this analysis demonstrates how to answer these questions. The key? Profit margins!TRANSCRIPT
Customer Information Strategy – Professor Dominique Hanssens Case Submission #2 – November 5, 2010| Study Group #5: Justin Cohen, Doug Daly, Kevin Morra, Brent Morrison, Nancy Sagar
The Age-‐Old Question: How Many Sales Reps Do We Need? Founded in 1889, C-‐Tek has grown revenue for its grinding wheels, sandpaper and abrasives
products to more than $20 billion in 2004. The company’s organizational structure encourages
innovation and entrepreneurial spirit by giving 33 different business operations their own P&Ls,
their own distribution channels, and their own sales teams. As a result, the company reaps the
rewards of occasional product breakthroughs. Yet on the flip side, this decentralized structure
creates resource allocation challenges; with all of these separate P&Ls, it’s extremely difficult to
judge where the most promising growth investment opportunities lie.
John Sawyers, the sales manager for grinding products, has experienced this issue firsthand –
he’s been losing his battle to gain additional resources for the past five years. His division is
growing steadily, but his 14 sales offices are losing ground to the competition, meaning he is
giving up market share. He has repeatedly proposed to add to his salesforce of 52 reps, but the
company continues to deny his requests. C-‐Tek management’s response to his proposals isn’t
uncommon, since troubled units in any business typically request additional resources in order
to reverse a performance slide. It’s easy to invest in divisions that are doing well, but when
they’re struggling, it’s easy to point the finger at managers or to cut further investment until the
situation turns around. That’s why so many companies slash their marketing budgets during
downturns in the economy – they base their investments on last year’s performance rather than
focusing on the return (e.g. profit) they can generate through various investment levels. John
has found himself in this very situation; fortunately, he’s smart enough to employ a forward-‐
thinking resource allocation analysis.
Group 5 – C-‐Tek page 2
Analytical process
We used the projections developed by John’s “base team” to run a resource allocation analysis
including sales response functions for each branch -‐-‐ that is, expected revenue as a function of
staff level. The first step was to use the team’s revenue projections to “calibrate” our model and
create the sales response functions. After our first pass at the data, we discovered that we
needed to use the “expert user” logit analysis in the ME-‐XL software, since the standard analysis
produced poor response curves like the Twin Cities curve in Exhibit A. By upgrading to the logit
analysis, we generated S-‐shaped response curves that more accurately modeled the impact of
additional resources (sales reps) on total revenue.
Once we calibrated the model by creating those city-‐by-‐city response curves, we ran the
resource allocation analysis to answer these questions:
1. If C-‐Tek continues to constrain John’s staffing level, can he increase his expected net
margins by shifting sales reps among his offices?
2. If John can optimize his staffing resources, what is the optimal (unconstrained) staffing
level and resource allocation among his branches to achieve the optimal level of profits
for the business?
Question 1: Reallocation of his current 52 reps
With a gross margin of 35%, C-‐Tek predicts about $28.7 M in net margin (revenue minus the cost
of the sales force) over the next year. The good news is that John can increase net margins to
$34.2 M by reallocating staff among his 14 branches as shown in Table 1. The reallocation
results in an additional $5.4M in gross profit, a 19% increase over the current sales force
allocation.
Group 5 – C-‐Tek page 3
Table 1: Expenses and Profits for Constrained Sales Force by Gross Margin %
To achieve these results for the case of the 35% gross margin, John will need to shift sales reps
among the different offices as shown below:
This graph shows that John must eliminate three of his sales offices altogether – San Francisco,
Philadelphia, and High Point – and move those sales reps into more lucrative cities (Cleveland,
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Optimal vs current headcount at C-‐Tek branches while maintaining overall staff levels
Current
Optimal
Gross Margin % Cost ($000)Gross Margins
($000)Net Margins
($000)20% 7,645.31$ 23,337.63$ 15,692.32$ 25% 7,644.83$ 29,568.64$ 21,923.81$ 30% 7,644.89$ 34,855.04$ 27,210.15$ 35% 7,645.03$ 41,829.65$ 34,184.62$ 40% 7,644.98$ 46,556.82$ 38,911.83$ 45% 7,644.92$ 52,248.65$ 44,603.73$
Group 5 – C-‐Tek page 4
Atlanta, Seattle, Los Angeles, Boston, Nashville, and Dallas). Such a shift could be quite
challenging for a company like C-‐Tek; their sales reps are likely mid-‐to-‐senior level, have roots in
their various cities, and strong backgrounds in the industry and product lines. A San Francisco-‐
based rep may not be interested in moving to Cleveland, so the company will need to determine
how to best serve customers in each market (can reps work virtually and travel for meetings, or
do they need to be physically located in each city?). If reps must relocate but are unwilling to do
so, the company may face a recruiting challenge to replace their expertise, or they may need to
increase base salaries/commission rates and incur non-‐trivial moving expenses to hang on to
sales stars.
In addition, to fully maximize profit, the analysis produced fractional headcounts at many
branches; C-‐Tek needs to decide whether it is practical for one salesperson to cover multiple
areas or if the staffing levels should be rounded up or down. The company faces additional
other decisions regarding how much of a change in staffing the company can endure without
breaking all current relationships with customers. As these practical issues are addressed, the
projected income would reduce somewhat, but these early stage results are promising, with
total net margin by branch shown below:
$-‐
$2,000
$4,000
$6,000
$8,000
$10,000
$12,000
$14,000
$16,000
Optimal vs current net margins at C-‐Tek branches while maintaining overall staff levels
Optimal
Current
Group 5 – C-‐Tek page 5
Unconstrained Case: Optimal Staff Levels and Allocation
For the unconstrained case, every branch sees an increase in staff, which allows the company to
maintain relationships with existing customers while avoiding the relocation challenges and
expenses. The new optimal staff level by gross margin is 97 FTEs at a 35% gross margin as
shown below:
Table 2: Gross & Net Margins w/ Unconstrained Sales Force by Gross Margin %
Even with a minimal gross margin of 20%, the optimal staff level is 83 heads -‐-‐ an increase of
over 50% from today’s level. The new staff is allocated across the 14 branches as shown below:
Gross Margin %Salesforce
size Gross Margins Net Margins20% 83.0 29,304.76$ 17,108.60$ 25% 89.2 37,664.72$ 24,552.21$ 30% 93.6 45,915.72$ 32,151.52$ 35% 97.2 54,130.79$ 39,848.20$ 40% 100.1 62,324.69$ 47,612.63$ 45% 102.6 70,509.00$ 55,427.19$
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# of salespeople
Optimal vs current headcount at C-‐Tek branches with unconstrained staff levels
Current
Optimal
Group 5 – C-‐Tek page 6
Based on this analysis, adding more staff will increase net margins by over $5M versus just
reallocating the sales force. Further, it is often easier for sake of continuity with customers and
employee morale to add staff than to shift or remove staff. However, adding staff poses
additional risk as the company is committing itself to additional SG&A cost. There is also a
question as to how many new people a branch can absorb and still function smoothly (for
example, do they need more support personnel as well?) and whether such a recommendation is
based on an overly optimistic scenario. Therefore, we did a sensitivity analysis on the expected
net margin as a function of total sales people over a range of gross margin levels.
As shown in the graph, there is a point of diminishing returns where additional staff leads to a
lower net margin. However, even for very low margins the optimal headcount is over 80.
Further, considering the flatness of the curves, the staff level can be within 5-‐10 FTEs versus the
optimal level and still reap very nearly all of the potential benefits. With this in mind, we
estimate the relative benefit of different staff levels on overall net margin:
$0.00
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0 20 40 60 80 100 120
Total net m
argin ($00
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Salesforce Headcount
Higher gross margins demand a larger salesforce
45% Gross margin
40% Gross margin
35% Gross margin
30% Gross margin
25% Gross margin
20% Gross margin
Optimal Headcount
Group 5 – C-‐Tek page 7
This chart shows the change in net margin for different staff levels versus the optimal
reallocation of the existing 52 member sales force. As shown in the graph, most of the benefit
to the company happens with a staff level between 80 and 100 people.
Breakthrough Technology
C-‐Tek is blessed with an entrepreneurial culture and history of innovation, and the product
development team believes their next new technology could increase the company’s profit
margin to 40% and increase the total market size by 20-‐25%. With such a dramatic potential
growth opportunity available, the company needs to have adequate sales staff ready to
capitalize.
With a 40% profit margin, increasing staff to 100 FTEs is the most profitable option assuming no
growth in market size (see graph at top of page). As this technology increases market size, a
greater increase in staff would ensure the company capitalizes on this new market opportunity
-‐$2,000.00
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Change in Net M
argin ($00
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Gross margin (%)
Raising headcount improves net margins
52 heads
60 heads
80 heads
100 heads
120 heads
Group 5 – C-‐Tek page 8
before imitators fill in the gap. However, there are three reasons we can’t make a
recommendation today about the specific additional headcount needed:
1. Growth drivers: If their market size calculation is based on total revenue for the product
line, is a large proportion of that growth being driven by price increases or purchase
volume increases from existing customers? If so, the current sales staff may be able to
capture most of the existing revenue with little incremental effort, meaning that the
need for additional headcount growth may be negligible. But if growth will be driven by
a new customer segment or purchases from new decision-‐making units, C-‐Tek will need
to increase headcount to capture that revenue. Without knowing the level of effort
required to generate various revenue scenarios in the calibration model, we can’t project
total or city headcount with any degree of accuracy.
2. Adoption rate: Over what timeframe will the innovation be adopted? Without knowing
this, we cannot know when or how quickly the market will reach the expanded state. We
would need to know more about the diffusion rate before staffing up to capture it.
3. Timing & sales process: Finally, we need to know exactly when this innovation will be
ready to launch and what the length of its sales process may look like so that we can hire
reps at the appropriate time. For example, C-‐Tek may decide that reps need to start
scheduling initial meetings with prospects using prototype products before the new
product even launches.
We do, however, recommend that C-‐Tek hire us to run this analysis after the innovation has
been released and the team has enough adoption and driver knowledge to provide estimates for
new response functions. At that time, we can run the analysis and tell them how many
additional sales reps they may need (and over what time horizon) to fully capitalize on the
opportunity.
Group 5 – C-‐Tek page 9
Final Recommendations
C-‐Tek is clearly understaffed in even the most pessimistic of future projections. A simple
reallocation of existing staff (the “constrained” model) may improve net margins by 19%
provided the re-‐shuffling does not lead to burned out staff, difficult relocations, rehiring, and
abandoned customers. Further, at this existing staff level, C-‐Tek wouldn’t have the sales
resources to support the breakthrough technology that is apparently just around the corner.
More importantly, this reallocation solution does not properly address C-‐Tek’s key issue: sales
resources produce future profit, and staffing should not be calculated purely on cost measures or
past performance. Instead, C-‐Tek must invest in resources to maximize future profit. In
economic terms, the goal should be to staff at the point where the marginal revenue for a
salesperson equals the marginal cost of that salesperson, aka the point at which marginal profit
equals zero. This exercise produces the headcount for that point and tells C-‐Tek how many reps
to hire to based on future profit margins.
This dramatic increase in staffing has its own challenges. For example, recruiting and training
the new staff could take significant time given the specialized expertise John’s team may
require. More importantly, this projection tool does not take into account how the competition
will respond. It is quite likely that a surge in selling effort by C-‐Tek will be met by a similar surge
across the industry, thus leading to more sales staff pursuing ever smaller opportunities. To
illustrate this point, note the projected sales as a function of headcount for optimally allocated
staff and a 35% margin shown below:
Group 5 – C-‐Tek page 10
The baseline sales estimate is $103.9M, so to think a major player like C-‐Tek can double its sales
force and increase sales by $50M without significant competitive response is overly optimistic.
So, since the current staff of 52 is woefully inadequate, and since ramping to 100 appears wildly
optimistic right now, we recommend an intermediate headcount of 80. This level is at or near
the peaks of the sensitivity analysis curves on page 6; it requires $3M less to staff than the 100
FTE level, and it gives C-‐Tek additional staff to exploit the breakthrough technology when it
arises. We also do not recommend asking reps to allocate their time to multiple territories in
order to meet the fractional FTE counts generated by the software.
$110,000
$120,000
$130,000
$140,000
$150,000
$160,000
$170,000
52 60 80 100 120
Sales ($0
00)
Headcount
Higher headcount leads to increased sales
Group 5 – C-‐Tek page 11
Final Staffing Recommendation: 80 Reps
With a total staff of 80 in these offices, projected revenue is just 0.7% lower than the optimal
allocation with fractional headcount.
Efforts and outcomes / Segments
LA SF Seattle Boston Philly Cleveland Atlanta Nashville High Point Dallas Chicago Cincinatti St LouisTwin Cities
Headcount 9 5 6 6 6 7 6 5 5 6 6 5 4 4sales ($000) 12,833$ 6,358$ 13,335$ 12,802$ 7,551$ 14,552$ 10,834$ 9,956$ 5,624$ 9,466$ 13,421$ 9,941$ 6,954$ 10,225$
Efforts and outcomes / Segments
LA SF Seattle Boston Philly Cleveland Atlanta Nashville High Point Dallas Chicago Cincinatti St LouisTwin Cities
Headcount 9 5 6 6 6 7 6 5 5 6 6 5 4 4sales ($000) 12,833$ 6,358$ 13,335$ 12,802$ 7,551$ 14,552$ 10,834$ 9,956$ 5,624$ 9,466$ 13,421$ 9,941$ 6,954$ 10,225$
Group 5 – C-‐Tek page 12
Exhibit A
Sample response curve using the standard analysis versus the expert logit analysis we used.
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Effort for Twin Cities
Twin Cities response curve -‐ basic model
Calibration Data
Response Curve
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Effort for Twin Cities
Twin Cities Response Curve Using Logit Model (expert users)
Calibration Data
Response Curve