5 steps to improve sales forecast accuracy

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Sales forecasting is the most important number for any organization. It forms the basis for all investment and spending decisions that will drive its growth. Therefore, the sales forecasting process is a key activity that cannot be dispensed with. It is imperative for businesses to make predictions based on demand, performance, and trends to stay ahead of the curve.

Additionally, the fast pace of the technology industry, which often comes with uncertainty, makes planning ahead even more important.

However, in today’s world, sales forecasting is a challenge for many companies as they fail to make accurate forecasts: less than 20% of sales organizations have a forecast accuracy of 75% or higher, according to the Miller Heiman Group . The main reason is the lack of a well-built forecasting strategy across the organization.

Fortunately, this doesn’t have to be the case, as there are certain things a company can do to get ahead of the curve and make inaccurate sales forecast results a thing of the past.

With this in mind, in the following article we will take a closer look at the source of the problem and suggest how to implement good sales forecasting practices.

Deal Management Forecasting - ES

4 barriers to effective sales forecasting
Sales forecasting practices are incredibly useful for businesses in more ways than one. Ultimately, they allow businesses to be better prepared for future events. At the cambodia telegram mobile phone number list same time, sales forecasting ensures that a business can make well-informed decisions using reliable data, rather than relying on information that may be inaccurate. But to get the best results, it is important to adopt the right strategy to avoid common mistakes that many businesses around the world continually make.

01. Incomplete, incorrect or unavailable data
One of the most common issues affecting forecast accuracy is data quality. Most organizations make decisions based on incomplete, incorrect, or unavailable data. One of the most common mistakes is not including data as a key driver of business strategy. It affects the type of forecast data that needs to be collected in business processes. If you haven't considered this, you're already working with a significant gap.

Other common issues affecting data quality can be, for example, a sales rep not having enough information about the deals in place and/or (most of the time) not entering the information into the CRM.