We’ve been researching and studying and analyzing the sales process and methodology for a long time. Back in 1999, our CRM was called MODE and consisted of three modules: FIND for marketing; TASC for sales; and CARE for after-sales support and service. TASC was an acronym for Territory, Account, Sales cycle, and Contact, and it incorporated the ASPEC technology, although it wasn’t called ASPEC then.
It was, as I said, 1999, and CRM was in its infancy, not really understood as a software tool by most businesses. We wrote a series of ten vignettes illustrating various situations where CRM would solve some business problem and published them as the TASC 10. They are still relevant today, and sixteen years later, here is Number 2 – The local weatherman puts your forecasting to shame.
“TASC provides a simple and consistent way to assess sales probability, the key ingredient in generating accurate forecasts. All salespeople have to do is answer two simple questions about the sales climate, and estimate when a buying decision will be made. Voila, bang-on forecasts no matter the weather.”
All companies rely to a greater or lesser degree on regular forecasting from their sales people. However, it is widely held that the forecasts from sales people tend to be very inaccurate. This can create problems for the entire organization.
Since the sales plan is an integral part of the overall business plan, companies need accurate forecasting in order to plan for the future. Data from the sales team’s forecast can influence major purchasing decisions, such as whether or not to buy parts for future manufacturing. Indeed, the financial health of the company is often riding on the quality of sales projections.
Forecasting is an area where sales automation should be able to help, and it some ways it does. Most sales automation platforms electronically connect everyone to a central list of opportunities the company is working on – therefore making it possible to streamline the collection of forecasts from the field on a regular basis. This capacity alone removes the burden of paper forecasts and reduces the costs associated with manually collecting and rolling up forecasts into a company-wide report.
Still, better efficiency does nothing to improve the quality of forecasts. This is where the sales methodology underlying the automation solution can make a big difference.
The first thing that is required for good forecasting is an estimate of when the sale will conclude. In other words, when will this order arrive in house, ready to be processed?
Determining the point in the future that the order will materialize is equivalent to assessing when the sales cycle will end (see ISA Bulletin #1). Selling skills are called into action here, since the sales person must probe the customer closely to determine when the order will be placed. To do this successfully, you should ask the customer directly when exactly he needs your product. This date, however, may not be the same as when the actual written purchase order will be received. Factor in any time the order could be stuck in the purchasing department before making your final prediction.
The customer may communicate their intentions in a few ways. Commonly, the customer will give an indication such as: “This machine must be in here and working before I take a vacation in November.” The sales person would then reply: “Then I need your order at the latest by the beginning of October,” thus deciding the forecast date.
The other critical issue in putting together an accurate forecast is the question of “are we going to get the sale?” This can be a very thorny issue for a Sales Manager. On one hand, it’s tempting to take the easy way out and simply ask individual sales people to predict the chances of getting the sale in terms of a percentage. However, this method fails to take into consideration the different forecasting “styles” that individual sales people may have. Ultimately, what’s submitted is more likely to reflect the personal characteristics of the sales rep – for example, whether they’re optimistic or pessimistic by nature – than the actual sales situation.
Leaving forecasts up to the subjective opinions of sales reps will confound your efforts to generate a realistic, accurate forecast. What’s needed is a method of assessing sales probability that everyone in the sales force can use in the same way. Ideally, even if two different salespeople were to evaluate the same opportunity, they would come up with the same results.
TASC uses two simple, straight-forward questions to make forecasting an objective exercise. The first question is “will this sale happen at all?”, regardless of whether you or the competition would win if it went through. In the rush to make a sale, it’s easy to forget that the sale might not happen at all. Many sales get started into normal sales cycles which do not reach a conclusion, often because of funding cuts, change in needs, or organizational politics. To further standardize the process, TASC asks the sales rep to answer “will it happen?” with three possible choices: high, medium, or low chance. The criteria for assessing a particular choice are outlined in the TASC on-line help system. Having a clear set of guidelines helps to ensure that this important question will be answered in a consistent way.
Once they’ve evaluated whether the sale will happen, the sales person is asked to assess whether “we will get it?”, supposing the sale becomes a reality. Again the sales person indicates whether there is a high, medium or low chance. The answer to this question takes into account the degree of competition surrounding the sale – and how well you can sell in the face of that competition. Again, providing only three possible answers to a simple questions makes the chance of consistency across the sales team very high.
Using the three-by-three grid shown in the Figure on page one, a single, unique probability value is extracted from the answers to the two questions. One grid axis represents the three possible answers to “will it happen?” and the other axis represents the three possible choices for “will we get it?”. TASC plots a unique point on the grid based on the sales person’s answers. For example, in the diagram shown, the probability is Low-Low. This grid is referred to as the probability matrix.
The probability matrix gives nine possible distinct answers to the probability that a sale will happen. For the purposes of forecasting, TASC reduces the nine possibilities to six possible probability percentages: 80%, 60%, 40%, 25%, 15% and 10%.
This method of forecasting is derived from questioning the sales representative about two distinctly different aspects contributing to the possibility of him winning the sale. To answer the questions he has to mentally integrate the key issues that contribute to the two fundamentals: firstly, is the sale going to happen at all (a lot don’t), and second, how confident is he in winning the sale if it goes to conclusion. Forcing this thinking process has a much greater potential of achieving accuracy and consistency in forecasting across the entire sales organization.