The Case for Patience in Long Sales Cycles
Sales leader Alex Thilen emphasizes the need for patience in enterprise sales cycles that stretch beyond 60 days. He warns against judging performance too early in complex hardware deals, which are often subject to unpredictable slips and closes.
For hardware sales with 6-12 month cycles, standard forecasting models often fall short. A weighted pipeline, which assigns a closing probability to each deal based on its stage, offers a more realistic forecast than simple projections. However, this method's accuracy depends heavily on disciplined CRM updates from sales reps. AI-assisted forecasting models can provide a more dynamic and accurate picture by analyzing hundreds of variables. These can include deal age, the history of the sales rep, and the level of engagement from decision-makers. For the volatile semiconductor industry, some companies use time-series models like Holt-Winters, which incorporate level, trend, and seasonality to predict revenue fluctuations. Improving pipeline visibility starts with standardizing deal stages and establishing clear, evidence-based criteria for moving a deal forward. This prevents deals from advancing prematurely and provides a more accurate view of the pipeline's health. In complex enterprise deals, this often involves mapping out all stakeholders from finance, legal, and engineering early in the process. To keep reps focused on selling, CRM automation is key. Workflows can automatically update deal stages based on triggers, assign tasks, and score leads based on engagement, reducing manual data entry. This frees up reps' time, which is crucial as research shows they often spend a significant portion of their week on non-selling activities. A "deal desk," a cross-functional group from sales, finance, and legal, can be created to manage high-value, complex deals. This centralized approach improves information sharing and removes bottlenecks, which is especially helpful when deals involve multiple stakeholders and departments. Key metrics for long sales cycles include pipeline coverage (the ratio of open pipeline to quota), sales cycle length by stage, and win rate. Tracking stage-by-stage conversion rates can highlight where deals are stalling, allowing for targeted coaching and process improvements. Revenue Operations (RevOps) aims to align sales, marketing, and customer service to create a unified revenue-generating engine. A core tenet of RevOps is establishing a single source of truth for all revenue-related data, which ensures that all departments are working with the same information. Dashboards for hardware sales should visualize leading indicators of deal health beyond just the deal stage. This can include the number of new opportunities created per month and the average monthly pipeline size to ensure consistency. For enterprise deals, tracking the number of engaged stakeholders within an account can also be a powerful leading indicator.
