Since one of my company’s biggest products is a lead management CRM, I was intrigued by Bob’s five “danger signs” that a company’s CRM “is actually behaving as a sales prevention system:”
- Unhelpful Stage Definitions
- Give – Get Imbalance
- Poor Forecast Accuracy
- Static Sales Process
- Failure to Reflect Prospect Decision Making Process
Items 2 and 3 particularly resonated.
• Give–Get Imbalance
If data input to the CRM is not not being used to give reps feedback, it simply falls into a “black hole,” Bob states, “with no evidence it is ever subsequently used by management for any practical purpose. Sales people need to believe that the information they enter is used by management to help them improve their chances of winning.”
Bob is absolutely correct, and this is generally more of a process problem than a data problem. My experience is that companies that waste time entering a lot of data into their sales intelligence systems do so because they don’t have a specific process for defining wins and losses–so reps feel compelled to enter anything and everything they think is going to help them.
Fix the process–identify key sales staging points that align to the customer, not the seller, then configure the CRM software to make data input direct and as easy as possible. I regularly see clients go through crazy finaglings to create some “essential data view” that their CRM system would support natively—if they knew how to use the system’s report engine properly, and then aligned their processes to leverage it.
• Poor Forecast Accuracy
Here Bob points out that according to CSO Insights, sales forecast accuracy for most companies hovers right around 50%, and that “Even if the projected headline revenue number is achieved, the way in which the number is made up bears little relationship to the deal by deal forecasts, and relies on heroic selling rather than intelligent use of resources.”
Sales metrics gurus The Bridge Group have repeatedly stated that a forecast should be 90% accurate in terms of both time frame and dollar value–and in my opinion, forecasts that don’t reach that level of accuracy aren’t much better than licking your finger and sticking it into the wind.
Accurate forecasting requires a process based on how the customer buys, not on the rep’s sales process. Revenues and time frames aren’t about telling the sales manager “how close” the rep thinks the deal is to going final—it’s about what’s actually going on inside the prospect’s “box.”