Stop sales forecasting in the dark
Legendary executive success coach Marshall Goldsmith famously said, “What got you here won’t get you there.” He intended this statement to be a reality check to business leaders who don’t understand that how they previously achieved success may not be the way to achieve success in the future. The same goes for sales teams.
When sales teams stick to past behaviors that brought them success, they aren’t adapting to current market conditions and customer expectations.
Today, learned behaviors and traditional sales forecasting methods deeply limit sales teams across industries. Forecasts that rely exclusively on a company’s historical data keep sales professionals tethered to the habits and approaches that closed deals last year and the year before — even when those behaviors didn’t close as many deals as anticipated.
Sales teams looking to grow revenue can’t simply repeat the same behaviors and expect more growth. All the historical data in the world can’t offer insight on the changes in the market today or predict how customer expectations will shift tomorrow. As a result, many sales forecasts are happening in the dark, based only on the past events at a single business. They aren’t forecasts at all. Historical sales forecasts are just assumptions that the future will be like the past.
The good news is a pivot to prescriptive sales forecasting is often all it takes to turn on the light.
Limitations of historical sales forecasting
According to Miller Heiman Group, more than 40% of sales operations leaders identify seller subjectivity as their greatest challenge to forecast accuracy. However, in this case, sellers’ subjectivity isn’t really the issue. The issue is the forecasts sellers are held accountable to and pressured to create.
Historical sales forecasting is the process of making assumptions about future sales based on historical sales data and performance.
Prescriptive sales forecasting combines a company’s historical sales data with third-party data, market insights, and machine learning such as neural networks to generate an even more accurate sales forecast.
Sales operations leaders and their teams are limited by historical forecasts, which don’t account for the current wants and needs of their clients. As a result, sellers must make subjective judgments about how their prospects will behave, which doesn’t always lead to an accurate forecast. In fact, sellers may naturally default to making safe predictions that set easy-to-meet expectations because they do not want to overestimate potential revenue growth.
With prescriptive sales forecasting, seller subjectivity becomes a human strength; sellers are no longer guessing about their clients’ behavior because they have data-driven insights to support their assumptions. Tools such as Collective[i]’s Intelligent ForecastsTM augment traditional signals such as seller confidence with a vast network of dynamic market data. Intelligent InsightsTM reinforce the intuition of sellers by using machine learning to analyze and learn from the behaviors and choices of top-performing sellers. These tools guide sellers in how a deal should optimally be approached while freeing them to use their subjective knowledge about customers and prospects to sell and build relationships.
Current deals may behave differently than deals in the past. This isn’t the seller’s fault, nor is it something they should be held accountable for. Instead, a better type of forecasting can help teams see unexpected shifts as new opportunities to do better work for customers.
Buyers are in control — and that’s a benefit
Seller subjectivity isn’t the only variable at play in today’s rapidly transforming sales economy. From day to day, the expectations, values, goals, and desires of target customers can shift due to current events and market forces. This is yet another reason that sales forecasts based primarily on historical data leave sellers operating blind.
Instead, sales forecasts need to be grounded in an understanding of the buyer’s desired outcomes and of how the products or services of the business align with achieving those goals. When a major cultural event or shift in the market changes the buyer’s goals and desired outcomes, prescriptive sales forecasting platforms can integrate that information in real time, enabling sales representatives to react quickly. Instead of sentencing sales teams to force the buyer to align with forecasts based on the past, a prescriptive sales forecast enables sales teams to adapt to a world where the buyer is in control, and gives salespeople all the resources necessary to support them.
The enlightenment of networked intelligence
Historical sales forecasting leaves teams in the dark because the data is being gathered from only one source. On the flip side, networked intelligence crowdsources data about buyer behavior and market trends. This turns on the light for sales teams in several ways.
According to Salesforce, the number of sales teams using artificial intelligence (AI) for sales process automation increased from 41% in 2018 to 53% in 2020. However, many of these teams use very basic AI technology for simple process automation, such as sharing information between team members or entering data in a CRM. But AI-lite tools using historical data aren’t enough to improve sales forecasts.
Neural networks are a subset of machine learning designed to recognize and analyze patterns the same way the human brain does. This means the algorithms get better at solving problems and making predictions over time. Collective[i] uses a neural network to offer real-time insights and recommendations for the next and best actions sellers should take in the selling process for each individual client.
“The word ‘headlights’ comes to mind,” said Neil M., a VP of enterprise sales and a Collective[i] user. “Collective[i] gives me that qualitative view into how we are conducting business. We rely on so much communication in between live customer meetings. Being able to peek into that gives me reassurance that we are on track — or warning signs that we’ve got to step in and do something different.”
Prescriptive sales forecasting powered by machine learning enables teams to take the busy work, guesswork, and anxiety out of building sales forecasts…
Explore the Collective[i] platform and stop sales forecasting in the dark.Explore Collective[i]