Sales forecasting has been a major problem for many organizations engaged in the sale of goods and services for a long time. With the onset of the pandemic in 2020 and now the gloom of oil price hikes and inflation, making close-to-accurate sales forecasts has become almost impossible.
One of the forecasting challenges faced by sales managers is seller subjectivity. As proven in psychology, sellers tend to be overly optimistic of their forecasts, only to under-deliver at the end. This is why more than 40 percent of sales operations leaders identified this as their biggest challenge to forecast accuracy, according to a study by Korn Ferry.
Another challenge is the lack of data to predict accurate forecasts. While customer relationship management (CRM) systems are now widely used, many sellers still view inputting data into these systems as an administrative task. Input data is usually not well thought of, leading to poor data collection.
The flipside challenge is the lack of technology to capture sales and customer data. Although CRM systems are now cost-effective compared to a decade ago, a lot of companies still do not have systems that effectively capture sales data. If they do have a CRM, it may not integrate into other internal systems, making the collection and manipulation of data cumbersome and fraught with errors.
The last challenge we see is the lack of sales management process rigor. Sales meetings may not capture seller biases and forecast errors due to a lack of sales review methodology. This is aggravated by the poor data coming from the CRM.
To improve sales forecasting means addressing these challenges. Companies need to invest in seller training and coaching, process, and systems and technology. Senior management and sales leaders need to bring these together to create a seamless and cohesive system that captures correct data real-time and detects and corrects forecasting errors.
The most important action for management and sales leaders is to invest in technology. An effective CRM is cloud-based and can be easily integrated into other systems like that for enterprise resource planning. User experience (sellers and sales operations staff) should be a primary consideration as it will dictate whether users religiously use the CRM or not. The system should also mimic the sales process to make it easier for sales leaders and sellers to capture, extract and use data.
Part of the technology and systems are management dashboards that are updated regularly and in real time and are viewable by sales leaders and sellers. These will enable quick decision-making to address customer or internal issues in order to preserve the validity of the sales forecast.
With regards to the sales process, there should be a weekly cadence review of seller forecasts. The sales leader should lead this together with sales operations and run with individual sellers to inquire and uncover forecast errors and validate the forecast.
Of equal importance are seller training and coaching. These should instill discipline among salespeople to update the CRM regularly and accurately, apart from being able to address ad-hoc issues with customers and internal processes.
Most important is instilling a data-driven mindset and culture among all organization members. Forecasts come from data and without accuracy manufacturing capacity, logistics, warehousing and hiring of people will be affected. If the sales forecast is underestimated, the company loses out.
An organization with a data-driven culture is one that is willing to invest in technology, big data and data scientists to churn out actionable data, is willing to learn how capture data and interpret dashboards, and is perennially curious about data set relationships to test business hypotheses.
The author is founder and CEO of Hungry Workhorse Consulting, a digital and culture transformation consulting firm. He is the chairman of the ICT committee of the Financial Executives Institute of the Philippines and a Fellow at the US-based Institute for Digital Transformation. He teaches strategic management in the MBA Program of De La Salle University. The author can emailed at firstname.lastname@example.org.