The Activity Trap: Why Measuring SA Hours Is Destroying Your Technical Win Rate
Most SA orgs are measuring the wrong things. Here is what to measure instead.
A measurement problem exists in most presales organizations, resulting in higher costs for companies than is commonly recognized.
This issue originates from management rather than technology or staffing and is frequently misclassified as a process problem. It persists because companies tend to collect the wrong metrics rather than the appropriate ones.
The core problem is that most Solutions Architect (SA) organizations measure team activities rather than their outputs, which are distinct concepts.
Research Findings
McKinsey found that strong presales capabilities yield win rates of 40 to 50 percent in new business, significantly exceeding industry averages. HubSpot reports that the average B2B SaaS win rate ranges from 15 to 25 percent. This performance gap is attributable to capability and management factors rather than product or pricing differences.
The same McKinsey research demonstrated that presales activities influence revenue two to three times more than lead generation. However, most companies prioritize measuring and optimizing marketing and lead generation instead of the outputs produced by Solutions Architects.
McKinsey also found that a 10 to 20 percent improvement in win rates correlates with 4 to 12 percent topline revenue growth without increasing the number of deals in the pipeline. Although actual impact varies based on pipeline mix, deal size, and sales cycle length, the order of magnitude remains consistent across studies. Most SA leaders fail to fully exploit this leverage point due to excessive focus on tracking inputs.
Data on Factors Correlated with Win Rates
Behaviors that distinguish high-performing SA organizations from average ones relate to insight and deliberate engagement rather than mere effort.
According to Ironclad data, companies excelling at providing insights and perspectives have a 55.2 percent win rate, compared to 40.2 percent for less effective companies. Ironclad does not identify the original study underlying this figure, so it should be treated as a benchmark rather than a primary research finding. The directional implication, that insight-oriented engagement correlates with higher win rates, is consistent with patterns observed across the broader literature.
Multi-threading data corroborate this pattern. Research from Ebsta, cited in Salesmotion’s 2025 benchmark analysis, found that deals involving three or more engaged stakeholders close 2.4 times more frequently, increasing to 3.1 times for enterprise deals. Enterprise buying committees may include a dozen or more decision-makers. These figures represent observed correlations in deal outcome data rather than controlled experiments; other variables, including deal complexity and qualification quality, likely contribute to the relationship. Nevertheless, the consistent direction of findings across multiple datasets suggests that stakeholder coverage is a meaningful leading indicator.
A Solutions Architect who spends 40 hours with a single champion fails to manage the evaluation effectively, as other stakeholders form independent opinions while the SA relies on the champion to manage them. Multi-threading constitutes an output behavior. An SA must understand the buying committee, map stakeholders, and build relationships with intent. Timesheets record hours but do not reveal whether the SA identified the economic buyer.
The implication for SA leaders is clear: behaviors associated with technical wins, such as guiding evaluations, shaping success criteria, building stakeholder coverage, and compressing timelines through precision rather than effort, produce outputs rather than hours. If a management system rewards hours, it fails to incentivize the behaviors correlated with success.
Stages Where Losses Occur
A 2025 benchmark study of 847 B2B SaaS companies found that 63 percent of losses occur before the needs assessment phase, rather than during the final presentation or procurement stages.
Therefore, the most impactful improvement for most SA organizations involves enhancing the quality of early-stage technical qualification and discovery instead of increasing the volume of demos or hours logged during evaluations.
An SA team that conducts fewer, more focused discovery engagements and qualifies out earlier reliably outperforms teams that run more engagements with less precision, even though the latter may appear more productive on timesheets. The data implies that the SA who compresses early, qualifies hard, and shapes the evaluation from the first conversation is not working less — they are working on what matters. The timesheet does not capture that distinction. The win rate does.
Characteristics of Output Metrics
Output metrics for an SA organization fall into two categories, and the right metrics depend on your go-to-market model.
In a perpetual licensing model, key output metrics include win rate on technically qualified opportunities, proof-of-concept (POC) conversion rate, deal velocity from technical qualification to technical win, and expansion revenue attributable to SA involvement post-close. These metrics indicate whether the SA is advancing deals and positioning closed accounts for growth.
In consumption or usage-based models, output metrics are more nuanced. Net Annual Recurring Revenue (NARR) influenced by the SA, specifically expansion attributable to use cases designed by the SA rather than organic product growth, is a key metric. Additionally, time to the first meaningful consumption milestone reflects whether the SA effectively prepared the customer for adoption or merely transferred a signed contract. An SA who closes a consumption deal without establishing a path to expansion has not completed their role.
This distinction is important. Many SA organizations operating under consumption models continue to use metrics from the perpetual licensing era. The true NARR opportunity lies within existing accounts, which most organizations overlook because of unclear SA responsibilities after the deal closes.
The Manager Problem Nobody Talks About
Activity metrics persist in organizations not because leaders are lazy, but because measuring outputs requires a manager who genuinely understands the technical motion their SA team runs.
To evaluate an SA on win rate, first identify technically qualified deals. To assess deal velocity, identify blockers and determine whether the SA resolved them. To measure NARR influence, define SA influence in the CRM and use an attribution model to track it.
This process requires judgment, deal knowledge, and a framework with clear success criteria at each sales stage — none of which a timesheet provides. Activity metrics are a proxy for understanding, not a substitute for it.
Gartner’s research indicates that B2B buyers advance significantly in their purchase decisions before their first substantive conversation with a seller. By the time the SA becomes involved, the customer has already formed firm views. If the SA conducts demos without understanding the customer’s buying stage, success criteria, or competitor influences, they merely participate rather than manage the evaluation.
When managers rely on activity metrics for SA performance, it indicates an absence of a framework for what actually drives outcomes. They measure what is easily observable rather than what the business requires. When those same metrics are used to justify promotions, they reinforce a culture that rewards busyness over results. The metrics tracked determine which behaviors get repeated.
Managers who understand their team’s technical motion build SA organizations that scale. Those who substitute activity tracking for deal knowledge build teams that cannot explain pipeline stalls.
Practical Implications
If you are leading an SA organization and your current measurement system relies primarily on activity data, the path forward is not to rip it out overnight. Build a parallel set of output metrics while keeping current measures. Over time, demonstrate that output metrics reflect true team performance. Gradually shift the culture to reward results, not only process compliance.
The right framework metrics depend on business model, stage, and growth phase. A Series A company with ten SAs and no defined PS function uses different metrics than a Series C company running a hybrid motion across segments.
Architecting Presales is building a framework that maps the right output metrics to your SA org stage, covering both perpetual and consumption models, with CRM configuration guidance to ensure the data is actually capturable. This is part of a library of 21 frameworks built from two decades of scaling SA organizations across multiple exits.
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