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Sales Forecasting: System Benchmarking

Sales forecasting is a challenging task for management. Sales leaders and CEO’s have a difficult time understanding why sales forecasts frequently fall short of their goals. Managers frequently have two issues: why is a company’s forecast consistently failing to capture all of the deals, and sales data coming upstream from the sales staff is overinflated and painting a rosy scenario?

Fog of Sales

The sales staff will often keep two sets of numbers, one in the CRM managers can see, and then another, private ledger – often a spreadsheet or a list in a word file, that tells the true story. This could be because bad deals that need to go into the system can be entered the system at an ideal time, to minimize compensation loss. Worse yet – some deals are even kept out of the system, a practice known as “sandbagging”, to achieve the opposite – maximum compensation over a given sales period.

Clarity Through Benchmarking

System benchmarking can help to make clear. CRM systems are increasingly able, especially with the help of outside vendors, to benchmark deals, sales margins, and historic trends. Using historic data sets, systems benchmarking tools can crunch vast numbers of data to show what types of margins, quantities, and products constituted winning deals. This means that sales leaders will have accurate numbers about the type of deal structures that are winning in their organization – something that was largely guesswork or collected at great cost in large organizations until recently.

360 View

The value of benchmarking is that it can recommend margins, quantities, and product mixes to the sales staff in real-time, as they put together a deal.Sales staff will know what limits they can go towards, how far they can cut their margin, and even historic profitability of a given particular client, as well as their ordering patterns. Given that some of these metrics are new but some are just more easily obtained, what can they tell us about forecasting?

In the same way, sales staff can be benchmarked vs other staff, or even their historic selves or the account’s typical performance. If a salesman is holding back, the numbers will show this, and the issue can be addressed directly with the salesman or be built into the sales forecast. With more leads in the system with better data about what deals should close at what margin, sales forecasting should become more accurate and allow for greater profitability.

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