An inaccurate sales forecasting results in sales teams turning in poor performances because either the sales quota set is too low or too high to start with. Consequently, an organization plans poorly as it fails to reach its predicted revenue.
The demand for data-driven sales forecasting is higher now than in the past. The rise of the need for sales analytics has also surged in the last couple of years as companies scramble to analyze their customer´s buying behavior in an attempt to increase sales.
So what exactly are the problems faced when doing sales forecasting? Why does it fail?
- Poor or inadequate data on existing deals
Working with very poor information is tantamount to working with no information. The truth of the matter is that many VP of Sales or sales managers employ the “hit-in-the-dark” approach. According to many, poor information about the true state of the sales opportunities is the reason for their poor sales forecasting.
So what can one do? First, ensure that the “required fields” on CRM are established. Think about all the information you want to have that is useful in forecasting. You then have to insist that these relevant information can be inputted in every step of the process before an opportunity can move on to the next phase. Ensure that you review the quality of information being entered into the CRM system.
- No personal accountability for Sales forecasts
Very few companies today have a system to ensure that the measurement and analysis for sales forecast accuracy is in check. People who do the sales forecast have no personal accountability for the forecasts they do. The danger here is that is there is no incentive for them to improve the way they forecast sales, they will never find ways to improve it to make it as accurate and realistic as possible.
How can this be resolved? First, make sure that the people you task to do the sales forecast fully understand the code of conduct to which the company subscribes to. Next, always insist on facts. Demand from your sales people data showcasing a deal by deal basis with observable evidence of the buying behavior or intent of the prospect. Show proof at which stage the customer reached in the decision making process, calculate the likelihood of the deal closing and ask why. Always ask for concrete evidence to support the claimed forecasts. Lastly, ensure that you measure their performance on the basis of the forecasts they make and then work time after time to eliminate causes of variation.
- Inability to trace the root causes of failure to close deals
Another important factor for inaccurate sales forecast is the failure to properly understand the dynamics of the deal and thereby failure to translate it into an accurate judgment about the likelihood of the opportunity closing.
This problem is usually resolved by ensuring that the salesperson asks the right questions to the right people at the right stage of the buying process. This is more a skills training for the sales people to make sure that they can interpret answers of the prospects properly and that they have the relevant information they need to be able to close the deal.
Is it really worth it fixing these issues with sales forecasting? We contend YES. Companies who are able to resolve these fundamental issues perform 24% better than other companies in terms of achieving their sales quota figures and over 16% in sales cycle reduction according to a study conducted by the Aberdeen group.
DSPanel offers cutting edge technology platform for business analytics, planning, and visualization. DSPanel designs, builds, and operates with the end users in mind. Performance Canvas was created by DSPanel to answer the unarticulated needs of the market not addressed by previous available solutions. With Performance Canvas, information is transformed into valuable business insights for the business executives to utilize in their decision-making process. DSPanel currently has over 2500 organizations deploying their solutions.