Correctly sizing and structuring a sales team is a high-stakes challenge. It can significantly contribute to a company’s growth—or irreversibly hinder it.
An undersized sales force with overstretched reps, whether across the entire company or in a specific territory, can cause a business to grow less effectively than its competitors and fail to serve customers well. Conversely, if a team is too large, the costs of maintaining salaries and supporting the team can eat into profits and resources.
Sales leaders whose targets feel out of reach—or who are expanding into new markets or launching new products—should consider resizing or restructuring their sales force. This can help to bring the right amount of coverage to each customer segment and maximize returns on their salespeoples’ work. A right-sizing project includes understanding the shortcomings of a current team’s size and coverage, then identifying opportunities for increasing, reducing, or shifting resources.
Unfortunately, many companies use management’s “gut feeling” to determine the size of a sales team, or how many reps to assign to a territory. Wisdom and experience certainly come into play when right-sizing, but relying solely on the intuition of a few people is unwise when their decisions are so central to a business’s growth and profits.
Instead, leaders can use data-driven methods. We will review several frameworks, caution against common mistakes and share pointers to ensure that new hires are successful . . . because hiring poorly often costs more than hiring right the first time.
Frameworks help companies avoid “paying as they go” or staying too small
For companies in a young growth stage, or in a rapidly growing market, we caution against keeping a sales team too small or using budget as a sole basis for restructuring decisions. It is what sales consulting firm ZS Associates calls a “pay as you go strategy,” or a “budget approach”: sales force size is predicated on budget, and only as many salespeople as can be afforded at a given moment are hired. The main priority is to limit headcount costs and only grow the sales force when profits increase—sales is not seen as an investment, but as a cost center alone.
For companies in a growth environment, this puts market share at risk. It anchors a sales force to the previous year’s budget and limits growth, while competitors may invest in their own sales force earlier and capture more market share.
Research from ZS Associates supports this idea. Its studies suggest that an understaffed sales force limits both short-term and long-term revenue. They have found that
“the sales force size that maximizes companies’ three-year profits is 18 percent larger, on average, than the size that maximizes one-year profits.”
Growing a sales force may not be right for every team at every time. But these findings challenge the idea that a “pay-as-you-go strategy” is a wise choice, especially for growth startups.
Rather than making sizing decisions based on an inflexible budget, or the intuition of a few managers, companies should use frameworks and data to help them become more objective about their investments in a sales force.
The data-driven approach to right-sizing
Right-sizing frameworks take into account the needs of customers, their sales potential, and resourcing costs. They create various scenarios that balance profit and customer coverage, allowing sales leaders to choose—and test—the optimal setup.
There are several methods and models to try, but here is a broad-strokes approach:
- Segment prospects and existing customers into meaningful groups.
- Calculate the sales potential of each segment.
- Estimate the minimum sales coverage required to meet the needs of each segment (for example, in hours).
- Estimate the average selling capacity (hours) of each sales rep.
- Calculate the number of salespeople needed to meet the coverage in step #3.
- Determine the fully-loaded cost of a salesperson, and calculate the cost of the entire sales force counted in step #5.
- Estimate the expected deal size and annual revenue for each customer segment. Expert judgment and intuition can be helpful here to adjust historical deal size data if a market is changing.
- Use the costs in step #6 and the revenues in step #7 to estimate profit.
- Tinker with this formula by increasing or decreasing coverage in different customer segments, shifting resources from one to the other and observing how profits change.
- Test a scenario and monitor data over time to adjust and iterate on the model.
Two data-driven frameworks, the Return on Sales optimization method and Efficient Frontier Benchmarking, provide detailed formulas for right-sizing.
Return on Sales optimization (ROS)
ROS is a simple yet powerful calculation that optimizes profits. It compares the increase in profit that comes with each salesperson to the incremental cost of employing each of those salespeople. When the marginal profit equals the marginal cost, the total profit is maximized.
Efficient Frontier Benchmarking (EFB)
EFB is a detailed formula that helps leaders calculate the ideal size for sales teams in specific districts or regions, taking into account local salary and differences in regional market potential and performance. It uses linear regression to find the ideal resource split across an entire team. EFB needs around 10 or more distinct districts, as well as other data, to be effective.
Making right-sizing work
Before restructuring or resizing a sales team, leaders can take steps to ensure all hires are productive and stay around for the long term.
Understand where a company is in the business cycle
Is a company in a Growth stage, Maturity stage, or on a Decline? Companies in growth should be careful not to under-size their sales force (and it’s worth noting that very young startups should have a solid go-to-market and sales strategy in place before scaling up). Companies at the peak of their business cycle, on the other hand, must be sure not to overestimate market potential and hire too many salespeople, because they risk the need to fire the same salespeople soon after. This is a pricey mistake.
Reduce risk by transitioning gradually into a new sales force size and allocation
We advocate for data-driven right-sizing methods, but, of course, data is not perfect. For this reason, companies should be careful not to quickly and blindly follow a model’s recommendation to downsize or scale up all at once. Rather, they should collect data as they change their sales team structure and feed it back into the model. This can support previous calculations, or prompt leaders to shift strategy if needed.
Invest in sales support
Calculations of the total cost of a sales rep must include managers, sales technology, administrative support, coaches, and more. Sales support must also increase as a company scales up its sales team. Even the best sales hires are much more effective with the right support; this ratio can differ from industry to industry.
Invest in good hires the first time around
For many companies, right-sizing means that more hiring is around the corner. It’s imperative to learn how to hire well because an underperforming sales hire is extremely costly. Our back-of-the-envelope calculation puts the price of a poor hire at about $700k in lost cash cost, not to mention reputational damage with customers and the negative impacts on morale and team culture.
Companies should invest in a solid sales hiring process to ensure that they attract A-players from the start. Top talent will support each other and improve the entire team’s performance through a better culture and the referral of other top performing hires.
Like Goldilocks, get the sales force size just right
Right-sizing a sales force, and allocating it well across customer segments, is critical for a company’s profit potential. Sales leaders can take a more objective approach to these decisions by relying on data-driven frameworks. Data isn’t perfect, so companies can increase the accuracy of these models over time by incorporating new information as a team grows, shrinks, or shifts. With enough iterations, it will soon be just right.
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