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The Real Moneyball: The Importance of Analytics to Improve Sales Forecast Accuracy

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The term “moneyball” is best known for applying an analytical approach to evaluating players on the baseball field, as written about by Michael Lewis in his book of the same name. The concept of moneyball can also apply to the field of sales, where analytics are used to improve sales forecast accuracy.

In my role as Director of Sales Operations at Richardson Sales Performance, I manage support functions that are essential to sales force productivity. When I took on this role in 2012, my primary goal was to improve sales forecast accuracy by providing insights into performance trends, identifying gaps, and recommending ways to fill those gaps.

To do this, I had to develop meaningful reports that would highlight trends and key deals, while assisting the sales team in managing the pipeline. These reports also had to give senior management the detail and visibility needed for decision making on additional strategies and whether to become personally involved in specific opportunities.

To me, there are two key aspects of sales forecasting. One is the analytics of deals in the pipeline. I use these metrics as a pressure test to qualify the risk of the forecast. This is important because, at the end of the day, if senior leadership is making decisions about investments, incentives, or promotional programmes on the basis of information that I’m providing, I need to make sure I’m not being too conservative nor too optimistic.

The risk in going too far in one direction or another has a direct impact on the business. The leadership team could decide to cut spending when they actually have the ability to spend more, or they could promote the wrong products and solutions. If I’m too optimistic in my forecast, they might interpret that as the go-ahead to spend more or not promote when they should.

The other aspect is that analytics can give sales leadership better insight into their team. Metrics that are measured consistently and thoughtfully allow leaders to 1) see how effectively their sales reps are performing and 2) more effectively coach sales reps and see how they are managing their work.

When evaluating sales reps, it’s easy to get stuck in the trap of thinking that those who hit their goals are performing well, and those who do not hit their goals are not performing well. This isn’t necessarily true because a sales rep could hit his/her goal with one or two major deals; this doesn’t mean he/she is doing the right things to continue being successful or truly effective at the job. Those who aren’t making goal may still have won many deals and be doing well in terms of things that are important to the company, such as account management or building relationships or prospecting. In this case, analytics can provide insight into areas where sales coaching would be helpful.

What is needed to be successful in sales operations is a balance of qualitative and quantitative skills. If you are overly strong on just the quantitative side, you risk throwing metrics at people without thought behind why you’re doing the analysis, what other things might be impacting the analysis, and not telling a proper story to help them understand what’s going on. This approach can easily lead to analysis paralysis, where you overwhelm people with data, and they don’t know what to look at or what any of it means.

What sales forecasting requires is thoughtful analysis so that you can tell the right story and have the data to back it up. If you’re looking at the wrong things, or not thinking from a holistic or comprehensive standpoint, you could be telling the wrong story – and that’s a story never worth telling.

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Brief: Using Analytics to Expose Impact


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