The 7 Most Common Obstacles of Sales Forecasting

August 26, 2022
Diya Mathur
Diya Mathur
Diya Mathur
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The 7 Most Common Obstacles of Sales Forecasting
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The 7 Most Common Obstacles of Sales Forecasting

"I want to be able to forecast sales!"

Timeless classic. Everyone wants to do it, but it is more than just an exercise in pulling numbers out of the air. Some say that forecasting is relatively easy; others say that it's incredibly difficult... there are even a few who say it's downright impossible.

Sales forecasting is a method for identifying and preparing for potential obstacles that could cause you to fall short of your goals. The process of forecasting requires you to think about everything happening inside your business and have a good understanding of the market and competition.

So, how does one approach this challenge? What obstacles need to be overcome for forecasting to succeed? 

These obstacles can be avoided altogether or offset by careful planning and attention to detail. This article will help you to consider a few critical points in the process of building your forecast.

1. Lack of training for managers

It can be tempting to propel yourself into the numbers-heavy forecasting world, armed only with your existing knowledge. But if you're unfamiliar with how to forecast accurately, it's probably best to find someone with experience who can help you navigate the process. Good training will arm you with the essential skills and identify common pitfalls before they happen.

Allowing managers to do their forecasting without assistance is like letting drivers complete their auto maintenance—they may figure out enough to get by. Still, they'll never be able to deal with every possible situation they might come up against. A good trainer can help managers think critically about their forecasts to prepare them for every likely scenario.

2. The sales forecasting process

The biggest obstacle in creating a sales forecast is the lack of a formal process. Many companies have a sales forecasting process but aren't using it as effectively as they could be. They might not have a documented method or use one that doesn't align with their overall business goals and objectives.

When it comes to sales territory management, it is important to note that there are no universally applicable best practices for creating sales forecasts. Each company encounters its own set of challenges and opportunities in the realm of forecasting, necessitating the development of a tailored methodology that aligns with the specific circumstances of the company.

3. Lack of quantitative analysis

Many companies rely on intuition and instinct when creating their forecasts — or worse, they take last year's figures and adjust them based on how they feel this year will go. This approach can backfire because there's no data to support it, so your forecast may not be accurate!

4. Sales forecasting is often an afterthought

Businesses often start forecasting at the beginning of the year or even at the beginning of a fiscal quarter. By then, it's already too late to get an accurate picture of what's happening in the business. The best time to begin your sales forecasting is as early as possible—ideally, six months before you need the information. Integrating a sales projection calculator into this early forecasting process enhances the accuracy of strategic decision-making and provides a more comprehensive understanding of ongoing dynamics and helps you predict the projected sales.

5. Non-repeatable and non-comparable methods

Sales forecasting is a science, but it's not an exact science. Even with the most sophisticated forecasting models, too many factors can impact sales. This means you can't rely on historical data to predict future sales.

Companies' most common mistake, often using non-repeatable or non-comparable methods, can be rectified through diligent sales performance analysis projects. These projects provide a structured approach, leveraging data for more accurate and insightful forecasting.

For example, let's say you're trying to forecast how much inventory you need to order from your supplier. Using last year's data as a basis for your forecast is not a good idea because it's not relevant to this year's situation. If last year's sales were slow because of bad weather, but this year are expected to be average temperatures, using the previous year's data isn't going to help much (and might even hurt).

Instead of using historical data, use more forward-looking numbers such as economic forecasts and industry trends.

6. No simple way to include bottom-up inputs from sales

One of the most common obstacles to sales forecasting is a lack of simple, reliable methods for including bottom-up inputs from sales. While forecasting should ideally be a top-down process, with senior management feeding their expectations down through the layers of an organization, this approach doesn't always work.

Sales teams may have no way to quantify or qualify their forecast, resulting in a disconnect between the forecast that senior management sees and the one that originates from the field.

7. It's based on your gut feeling

Sales forecasting can be a tricky task if you don't have any reliable data to work with. Data is crucial to making accurate forecasts and ensuring that your forecasts are on track during the year. The information you gather during a thorough analysis will help you better understand why your company is performing as well or poorly as it is and also allow you to predict how your business will perform in the future based on current performance and trends. 

To Conclude

Sales Forecasting is a never-ending cycle of assessing, allocating, and adjusting goals. It can be pretty easy to get lost in the ruckus of assigning tasks and tracking goals. However, to master forecasting management, you must keep track of all the metrics in conjunction with sales quota and commission plans to gain a competitive advantage.

Deploying an automated system can help improve performance, reduce salesforce turnover, reduce time spent adjusting yearly changes, and ensure accurate account allocation.

Diya Mathur
Diya Mathur

Diya is a Product Marketing Associate and content writer specializing in Incentive Compensation Automation. Diya has honed her ability to bridge the gap between intricate software functionalities and accessible, reader-friendly content. Her articles are a testament to her dedication to breaking down intricate SaaS solutions into digestible insights that cater to both tech-savvy professionals and those new to the software landscape.

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