Sales Motion Forecasting

The number one challenge sales leaders encounter is the ability to keep well-informed about an accurate status of the sales pipeline with insights about when, who, how, and why. Without clear visibility, even when salespeople keep their pipeline updated within the CRM system, accuracy is not ensured. With inaccurate sales metrics comes a significant risk of impacting sales and support functions, resulting in those teams being left to reconcile the alignment of how they execute and operate to get things back on track and moving forward.

Sales Motion Forecasting relies on many specific factors, including the relevance and availability of historical data, currency and accuracy of available data, the suitability of the data for tracking leading indicators of sales motion and success, alignment of sales motion health scores for targeted activities within sales stages, consistent metrics for the forecast time period, and the tracking of value realization compared to targeted goals and objectives.

Sales motion drivers, status, and results must be measured continuously from several sales function perspectives. Sales Motion Forecast metrics and measures must be relevant to each sales domain and sub-domain function across the sales lifecycle. For example, sales motion for a Sales Engineer will have a different focus than a Sales Development Rep or a Customer Success Manager. Each sales and support function needs to be aligned to the others so there is a 360-degree view of the entire sales lifecycle.

A successful Sales Motion Forecasting strategy depends on active collaboration with, by, and for every sales and support function. There must be visibility and clarity about how functional contributions are attributed to the stages of the sales lifecycle to ensure forecast accuracy. Attributions for contributions to sales motion ensure there is a standard for evaluating performance. Benchmarking sales motion and performance can inform improvement strategies while maintaining alignment across all functional areas.

A forecast with a focus only on historical metrics will not be adequate to provide leading indicators of risk, sales motion bottlenecks, unexpected changes to sales motion, insights that can be used to resolve under performance, opportunities for process improvements, and the ability to identify new best practices for workflows.

According to market research firm IDC, companies lose 20% to 30% in revenue every year due to inefficiencies. No matter which sales process is used as a foundation, an adaptation of how it will be executed is required for it to deliver the promise of performance. After all, there are unique expectations from every market, segment, region, buying organization and unique capabilities from each function, solution, and selling organization.

The development and execution of a viable Sales Pipeline Forecast requires sufficient data so that the correct relationships can be established. Throughout each sales cycle, especially over a long period of time, changes in conditions may account for a significant impact to sales motion and the forecast. Automated process mining and mapping provides process analytics, analysis, insights, and resulting intelligence that can adequately inform Sales Process Forecasting. With process intelligence, sales motion forecasting is becoming more accurate thanks to it providing leading indicators of health, status, and motion enabling visibility about changes before they impact the forecast. This allows for stakeholders to serve more as generators of ideas and innovations rather than forecast Sherpas.