Irrelevant data
While similar to the previous point, this issue carries a slightly different implication. Even if your data is accurate, outdated information gathered without real-time updates can impede accurate forecasting and projections.
This challenge often affects companies that rely on spreadsheets for sales forecasting.
Frequently, these spreadsheets are not linked to CRM tools or other data sources. Consequently, essential parameters necessary for forecasting are manually entered with significant delays.
The solution is straightforward: implement forecasting software that operates on real-time CRM data and information from B2B data provides.
Lack of stakeholder buy-in
The desire for accurate sales forecasting should be ingrained in a company’s culture.
A sales leader shouldn’t have to battle alone on this front.
I’ve observed instances where a company’s senior management doesn’t prioritize sales forecasting, deeming it unimportant due to the company’s size or other perceived priorities.
It’s never too early to invest time and resources in forecasting. Therefore, there are many different forecasting techniques that can be applied to each specific case.
Undefined Process
Sales forecasting isn’t a one-time event; it’s an ongoing process that requires time, people, data, and tools.
To ensure accuracy in forecasting, it’s crucial to establish data entry requirements, engage and motivate team members, schedule forecasting meetings and reviews, deploy appropriate tools, and continuously refine forecasting models.
Inappropriate forecasting methods
One size does not fit all. The most significant issue arises when companies try to implement forecasting models that are not suitable for their unique circumstances.
For example, you will not achieve positive results from time series forecasting if you lack sufficient historical data.
Forecasting based on the average length of the sales cycle is ineffective if your sales cycle is too short.
Similarly, forecasting by pipeline stages is impractical if your sales process is not adequately designed and lacks enough historical data to calculate probabilities for each stage.
Select the method that best fits your current situation to attain accurate forecasts.
Failure to employ forecasting software
This is a crucial aspect.
Many companies still invest a considerable amount of time preparing sales forecasts using spreadsheets.
Unfortunately, spreadsheets do not facilitate the implementation of comprehensive forecasting models, or at least not easily.
Furthermore, maintaining spreadsheets requires significant time and manual effort for data updates.
On the contrary, most popular CRM tools only offer simplified forecasting methods like weighted pipeline, lacking advanced capabilities.
Fortunately, we are witnessing the emergence of robust forecasting tools suitable for companies of all sizes and financial capabilities.
Consider utilizing specialized software that can be seamlessly integrated with your CRM or other data sources, without requiring extensive and complex implementation processes.
Final words
I’ve been engaged in sales forecasting ever since I entered the B2B sales arena. I’m an advocate for sales forecasting, emphasizing its importance for companies to achieve predictable and efficient growth.
I believe that every company, regardless of its size and sales model, should invest time in sales forecasting and explore ways to enhance forecast accuracy.