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month reviewThe ability to make ‘commit or not commit’ decisions and then to forecast accurately is a key measure of a sales manager’s effectiveness.

An executive team in most companies will judge how good a sales manager is based on their track record of delivering commitments successfully. Yet forecast accuracy is still a problem for most.

Research regularly shows that under 50% of forecasted deals close as predicted. This has been true for many years with little seemingly helping to improve this. Salespeople clearly need help to make the right choices, help to know when to pursue deals, and when to commit into the forecast.

This is an issue for sales managers who are expected to be predictable and deliver their forecast. The forecast sets expectations on what will be delivered at a point in time. In years gone by a sales orders forecast was commonly weighted (Probability x value). Whilst this may continue to be appropriate for higher volume sales environments (where you are confident of the probability %), in most b2b environments forecasts are done on a ‘commit’ basis. This is where a salesperson commits a deal into a forecast for a particular period and their judgement is used to include or not.

Managers should use their experience to challenge the ‘rolled up forecast’  from their team to improve the accuracy of a forecast. They should apply judgement to make better predictions, use data gathered to qualify the salesperson’s view and decide whether this deal is likely to close or not . But how well do they do?

Managers can’t see the wood for the trees

Our research shows this is one of the most challenging parts of a sales manager’s role. As salespeople work on so many deals there’s a risk that review conversations are spread too thinly and too much time is spent trying to get the insight. The need for good quality data cannot be understated when looking at building a reliable forecast. (link)

Whether you forecast quarterly or monthly, sales managers need enough information at their fingertips to be more productive. But where should they focus their inspection efforts?

Forecast categories

We typically see three ‘buckets’ used in a forecasting exercise:

  • Deals to definitely include – commit
  • Deals to definitely exclude –  omit
  • Deals that might happen – upside

Whilst “commit” and “omit” deals should be the more straightforward to review, it’s a fact that a high proportion of “commit” deals regularly fail to get over the line. They are as prone to ‘pipeline slippage’ as others and around a third of deals in “commit” fail to close.

“Upside” deals are even more tricky to predict. You could include some of them, part of them (weighted), assign ‘risk of not closing’ or perhaps ‘sprinkle in some over-optimism and hope’ to make it appear you are not going to miss your forecast (and then cross your fingers). Sadly, mostly these approaches fail to deliver yet managers are reluctant to say no. Salespeople (and managers) often lack the courage needed to make hard choices and walk away from an unwinnable deal. They fear that presenting a reduced pipeline makes them look bad. This is an issue too for the executive team, who miss the opportunity to challenge the level of “qualified” deals in the pipeline (v’s unqualified) in reviews.

So how do you make your forecasting choices?

Our opportunity management application (DealSheet) helps you to focus on the deals that matter. We use the data captured throughout the ongoing qualification process to illuminate your pipeline reports. Managers get detailed information for every deal and this reduces the wasted effort associated with “ringing around” for basic information (link) . Moreover, it then assigns each deals to a quadrant analysis to help managers make forecasting decisions. (In fact some of our users use this information directly as the basis of their forecast).

For most companies, there are core qualification questions that will inform decisions on bid/no-bid. There may be some specific to your business but there are also a number of common ones such as funding, timescales and delivery risk. You will probably have these defined for your business, and use these to consistently qualify your deals in your orders forecast. To improve predictability and accuracy of your forecast you need to know three core pieces of information:

  • Is the project likely to happen? (likely to buy?) Some people call this P(go) or P(happen). As over a quarter of B2B deals do not happen at all (they are eventually lost to no decision after much slippage). How confident are you that your deals are going somewhere (whether you win them or not!) and they will do so in the timescale included with your forecast?
  • Will you win the deal if it is procured? (competitive strength?) This is sometimes referred to as P(win) and is focused on your competitive position. No-one wants to work on deals where you have a poor chance of winning relative to your competitors. This is based on your fit with the buyers’ needs and your ability to differentiate.
  • Do we want to win? (should we bid?)

Under each area there are a number of questions that contribute to your assessment. We analyse this in DealSheet using a simple quadrant presentation, with each deal position in the quadrant being built automatically from the answers in the sales assessment. This helps you to decide whether to ‘commit or not commit’. The thinking behind this analysis is shown in the diagram below.

forecast Quad table

As sales managers, your decision to commit or not commit can be simplified using a similar approach, whether you use DealSheet to simplify things, or your own developed approach. By capturing detailed data against your qualification questions, coupled with an effective management review, it is possible to more accurately measure the ‘likely to buy’ and ‘competitive strength’ dimensions of each deal. This reporting can be built in to your CRM system to simplify your task. (See Salesforce Dashboard example below).

A Salesforce Dashboard showing added insight based on DealSheet data

A Salesforce Dashboard showing added insight based on DealSheet data

We hope this helps you to predict better. Good luck with your forecasting and your commit decisions. In the meantime, here’s some things for you to consider if you want to make better commit or not commit decisions.

  1. Assess each deal consistently against the qualification questions that work for your business
  2. Test for data integrity with good reviews
  3. Measure the ‘likely to buy’ and  ‘competitive strength’ scores for each deal
  4. Assign the deal to a quadrant
  5. Decide on includsion using grid above.

If you want to explore how DealSheet can help you to do this more easily and consistently, please get in touch.

 

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