3 hacks for more accurate sales forecasting | radioinfo

3 hacks for more accurate sales forecasting

Tuesday 05 December, 2017
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Accurate sales forecasting has long proved one of the toughest challenges for b2b sales leaders. It’s often said that well over half of all forecasted deals fail to eventuate, so despite study and analysis of this crucial business management discipline, there’s still a long way to go.

As we’ve previously discussed, there’s a strong argument for running with opportunity stage/weighted pipeline forecasting model. We contend that this powerful tool not only helps predict future revenue flows, it also allows you to analyse the health of your sales operations and plays a role in growing revenue over the long-term. However, it’s success isn’t a given.

Ultimately, there’s no right or wrong, with the effectiveness of a forecasting model decided by the way it is applied and the type, circumstances and/or lifecycle stage of the business that adopts it.

Many organisations use the historical approach - a technique based on past experiences and knowledge, with businesses deriving their forecast from known revenue outcomes in corresponding prior periods. Notably, this often fails to effectively consider the current market dynamic. For others, hardcore statistical techniques such as regression analysis lead the way.

Indeed there’s countless approaches, each with their own strengths and weaknesses. We’ll save discussion of their relative merits for another day, but in the meantime, here’s three simple hacks which will serve you well.

1. Consistency & Collaboration

For any sales forecasting to deliver a realistic picture of upcoming revenue, a well documented sales process is a must. Consistency in how each member of the team defines the status of their accounts will only eventuate if this exists. 

Within this process, the team needs consistent language and agree upon and normalise the underlying criteria for each sales stage designation. Where reporting and forecasting is the output of advanced CRM systems, it is likewise essential that system usage is consistent and thorough. 

Sales reps should be encouraged to collaborate, discussing the status of their prospect pool with their peers. This will help ensure customer classification becomes ever more consistent across the group over time, with more experienced reps afforded the opportunity to guide newer peers on how to appraise and score accounts’ revenue probabilities. 

The same level of discourse should also be a mandatory part of team meetings. Hubspot/Sales Management Association research shows that companies that spend at least three hours per month talking with reps about their pipeline had an 11% revenue advantage over those that didn’t.

2. Evolve & Adapt

Whilst a standardised approach and cooperative mindset will typically drive some big early wins in sales forecasting efficacy, many organisations soon come unstuck when they take a set-and-go policy. The best forecasts are typically those that give due consideration to a broad range of factors and review their changing impact on sales outcomes on a regular basis. 

Current market dynamics, accuracy levels of reps’ previous forecasts, changes to the length of average sales cycle and weights applied to the various sales stages are among the factors that should be subject to ongoing review. Unfortunately, forecasting is rarely perfected, so constant recalibration of forecasting methodology is required as the determining factors of successful sales evolve. 

3. Question, Challenge & Hold Accountable

Many a green sales leader has come unstuck by relying too much on the disparate forecasting inputs of their reports. Whilst it is essential to rely on the sales team’s individual reports to build an aggregated forecast, the golden rule is to embrace the exercise, or more importantly the supplied forecast information, with a healthy degree of scepticism. 

Where a rep forecasts 10 deals for the month, instead of their normal five, examine activity data to see if there’s a spike that can justify such a position. Likewise, where inputs from individual sellers differs from the aggregated forecast put together by their manager, use the CRM data at your disposal to pinpoint the disconnect.

Ultimately, the best forecasts are those where reps don’t just throw out the numbers they believe their managers want to hear, but those that can be backed by empirical data. Although no one wants to see a forecast markedly short of budget, at least that picture can give the impetus for necessary evasive action that might otherwise be missed because of all-too-common sugar coating. 

Accountability is of course a key requisite for success. Where reps are a) held responsible for the information they supply and the predictions they make of the probability of winning an account and b) fully understand the negative impact poor forecasting can have on the business’ overall performance, you’ll be impressed by the accuracy improvements that flow through to the aggregated level. 

Breed a culture where reps take pride in the accuracy of their predictions and you can’t go wrong.


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