A compensation plan can reward the coverage problem it created

A quota miss looks like a person-level result because the number is attached to a person. The number does not tell you what produced it.

Before asking whether a representative worked hard enough, ask what the plan made valuable, what opportunities were available, which accounts were covered, what mix arrived, what happened near the period boundary, and whether the sales-marketing handoff produced usable work. That is not a way to avoid accountability. It is a way to identify the object for which accountability is appropriate.

Why is a sales quota an outcome rather than a causal mechanism?

A compensation plan can reward revenue, bookings, margin, new logos, retention, or some combination of them. Each choice changes the behaviour the plan makes visible and the behaviour it leaves in the background. A quota attainment percentage compresses those choices into one result.

That compression creates a common diagnostic error. A team sees 72% attainment and immediately asks which representative missed the number. The better first question is: what had to be true for the number to be reachable, and which of those conditions did the plan actually control?

The answer is rarely contained in the payout curve alone. A plan can be reasonable against a healthy opportunity set and unreasonable against a thin territory. A lead can be present in a CRM and still be unusable because it is poorly qualified, already owned by another route, or too late for the buying window. A strong quarter can contain pulled-forward transactions that make the next quarter look weak. A miss can therefore be a plan signal, a coverage signal, a timing signal, an execution signal, or several at once.

What the sales-lead study actually measured

Sabnis, Chatterjee, Grewal, and Lilien studied how sales representatives allocate time among marketing leads, self-generated leads, and non-acquisition work. The paper mailed 2,666 surveys to representatives in four B2B firms. It received 562 responses, retained 500 after screening, and analyzed 461 observations after excluding respondents who reported no time spent following up on marketing leads. The final analysis is therefore not one number. It has a sampling path, an exclusion rule, and a defined time-allocation object.

The four firms’ compensation systems were based primarily on quota achievement, commissions, and top-line bonuses. None explicitly rewarded following up on marketing leads. That detail matters for the diagnostic question. If a firm wants a behaviour that the plan does not reward, a low follow-up number is not automatically evidence of low motivation. It may be a consequence of the trade-offs the plan leaves representatives to make.

The model separates three kinds of conditions:

• Motivation: perceived lead prequalification and managerial tracking.
• Opportunity: the volume of marketing leads available to pursue.
• Ability: representative experience and past performance.

The reported results resist a simple “add more leads” prescription. Perceived prequalification quality was positively associated with marketing-lead follow-up. Managerial tracking had a negative coefficient in the reported model. Marketing-lead volume had no statistically significant simple main effect, and its relationship with follow-up varied with experience and past performance.

The practical lesson is not that tracking is always harmful or that lead volume is irrelevant. It is that a lead count is not the same object as usable selling capacity. The time available, the perceived quality of the lead, the representative’s existing relationships, and the other work competing for attention all change what the count means.

Pay can change the timing of the result

Oyer’s fiscal-year study provides a different kind of warning. It uses 31,936 quarterly observations covering 981 manufacturing firms and fiscal years from 1985 through 1993. The paper reports that manufacturers’ sales are higher at the end of the fiscal year and lower at the beginning than in the middle. Its mechanism is that nonlinear pay can give agents an incentive to influence prices, the timing of customer purchases, and effort over the fiscal year.

This is useful evidence for a compensation diagnosis, but it is not a universal quarter-end rule. The sample is manufacturing. The design separates fiscal timing from calendar seasonality, and the paper says its evidence is consistent with incentive responses. It also says that the analysis does not establish an indisputable causal relationship or an optimal compensation plan.

That limit should travel with the finding. A period-end spike is a reason to inspect timing, price, deal stage, approval path, and subsequent realization. It is not proof that every deal was pulled forward or that every plan is defective. If the next period reverses the result, the timing hypothesis gets stronger. If the result persists with stable terms and no boundary change, a different mechanism may be more plausible.

The interface can change the meaning of the number

Compensation is also an interface design. Sales and marketing may share a revenue objective while working with different definitions of a usable opportunity, a reasonable time horizon, and a good outcome.

Malshe, Johnson, and Viio studied 42 participants in 21 sales-marketing dyads from 17 B2B firms across 10 industries. Their qualitative study found that the same interface dysfunction could be interpreted differently by sales and marketing, producing responses that sometimes reinforced the dysfunction. The pattern was bidirectional or circular rather than a clean sequence in which one function simply caused the other to fail.

Biemans, Malshe, and Johnson reviewed 73 sales-marketing interface articles published between 1990 and 2021. Their synthesis keeps structural linkages, role linkages, interactions, and perceptions separate, then groups the literature into five major themes. That is a useful scope guard for a compensation discussion. The plan is one structural linkage. It sits inside a larger system of roles, interactions, and interpretations.

If marketing is rewarded for lead volume and sales is rewarded for short-term bookings, the same lead stream can be a demand-generation success and a capacity problem at the same time. Neither function’s number settles the question. The handoff needs its own observation: qualification status, ownership, response time, buying window, and eventual disposition.

What would change the diagnosis?

The table is useful only if it changes a decision. A compensation review can therefore start with a small set of questions:

1. Could a representative with the same plan have reached the target with a different, observable opportunity set? If yes, the plan or coverage is part of the explanation.
2. Did the plan change the value of timing, discounting, or deal credit near the boundary? If yes, compare current-period bookings with later realization.
3. Did the opportunity set change in volume, qualification, ownership, or mix? If yes, attainment is not a clean period-over-period comparison.
4. Did the handoff create usable work? A qualified lead that cannot be reached in time is not the same object as a qualified lead with a live buying window.
5. Is the outcome the business actually wants the outcome the plan measures? If the plan rewards top-line bookings while the decision is about margin or retained value, the miss may be in the measurement design.

These questions do not require a perfect causal model before a manager acts. They require enough structure to avoid changing the wrong variable. A plan can be repaired. A territory can be redrawn. A handoff can be redesigned. A representative can be coached. Those are different interventions, and one quota percentage cannot choose among them.

The fair counterexample

There is a strong counterexample to this diagnosis. Suppose the plan is stable, the territory is well covered, the opportunity set is qualified, the mix is comparable, the timing is ordinary, and the customer outcome is defined. The representative still misses. In that case, execution is a credible explanation and should be investigated directly.

The framework is not a presumption that the system is guilty. It is a refusal to declare the person guilty before the system variables that define the result have been checked. The burden is not to exonerate every miss. It is to name the mechanism before prescribing the remedy.

Boundary

The evidence supports a diagnosis, not a payout rule. Sabnis et al. show that lead prequalification, managerial tracking, lead volume, experience, and past performance interact with sales-representative time allocation in a four-firm B2B setting. Oyer shows a fiscal-year revenue pattern in manufacturing and explains why nonlinear pay is a plausible mechanism while keeping causality bounded. The interface sources show why plan design sits inside a system of roles and interpretations.

None of that tells a company what its quota should be. It tells the company what to inspect before a quota miss is used as a verdict. Compensation is a measurement intervention. Treating it as a neutral scoreboard is how a plan can reward the coverage problem it created.

The handoff seam is made explicit in the funnel bottleneck nobody’s measuring. The wider measurement discipline is set out in evidence over anecdote. For multi-causal quota analysis, review how quota attainment has more than one parent.