June 18, 2021

Written by

Collective[i] Team

  • Posted in
  • Sales Forecasting
  • Sales Forecasting Methods

Why historical forecasting is not enough

Historical sales forecasting methods rely on the past behaviors of sales teams to predict the actions that will lead to profitability at a particular business. But what good is it to be in the know about what already happened when anticipating future trends? Just like digging through the dark recesses of your closet, digging through historical performance data only reveals what worked and was popular in the past — not what fits today’s market and culture. Likewise, companies evolve over time to respond to those changes in the market, so what made sense for yesterday’s sales team might not make any sense at all for today — or tomorrow. Traditional forecasting analysis uses historical data about company-specific buyers and sellers to generate predictions. Sales teams cannot grow, innovate, and prosper if they are making decisions based exclusively on what worked for them, and only them, in the past.

customer-needs-expectations

It’s true that companies build an understanding over time of what works in their industry and for their customer base, and those insights should not be discounted. But it can’t be assumed that they are perfect or won’t be improved by real-time information in the present. Historical sales forecasting is a start, but it’s no longer enough to get teams across the finish line of achieving or exceeding the forecast. Teams need insights about the market and current events, the prospects in the pipeline today, and competitor activity. Emerging networked intelligence on the market bridges this gap between past and present to help chart the course to the future.

Historical forecasting is limiting today’s sellers

Historical forecasting is flawed because it assumes the future will be like the past. This is a damaging concept when it comes to sales. Customer needs and expectations may change day-to-day, especially in the new realm of collaborative and cross-functional sales.

Gartner estimates that the average B2B buying group now includes 11 active members and up to seven occasional participants. When a sales professional needs to balance and speak to the needs of multiple internal decision-makers, the approaches and strategies that worked in the past no longer serve. Forecasts based solely on the historical data of the business don’t empower sales teams with context for the present sales environment.

When a current deal doesn’t close or progress in the same fashion as the deals of the past did, it may cause a setback that disrupts the entire forecast. Instead, with the right additional sales forecasting tools, these changes could actually help the deal close faster and to the greater satisfaction of everyone involved.

Prescriptive forecasting empowers sales teams

Prescriptive sales forecasting augments the foundation of a company’s historical data with networked intelligence. What is networked intelligence? This emerging machine learning technology recognizes patterns deep within historical data — but doesn’t stop there. In addition to learning from an organization’s own historical data, networked intelligence learns from publicly available third-party data, market trends, and consumer-behavior insights. Each source is processed and analyzed in context with the others, resulting in real-time insights about the sales pipeline that go beyond an accurate forecast to an actionable forecast.

Sellers can stay focused on the best opportunities for them in the present moment using these insights — based not only on what has worked for one organization in the past but also on buyer behavior and what is working for many organizations in the present.

Collective[i]’s neural network lets you learn from the past, present, and future

If your sales forecasting doesn’t include present-day insights to make actionable recommendations, its utility as a forecasting tool will be extremely limited. It’s often outside factors that impact deals — both negatively and positively. An integral buying team member might change jobs, the market might take a turn, or a revenue windfall could speed up sales decisions. Collective[i] is the only prescriptive sales analytics tool on the market that accounts for these data points. That’s one reason why using Collective[i] means having the opportunity to modernize every aspect of the sales process.

Our Intelligent InsightsTM platform learns from the past habits and strategies of your top sales performers to guide all sellers’ attention to where it will make the most impact in their respective pipelines. As new habits and strategies improve outcomes, the neural network learns along with your team and updates recommendations accordingly.

The C[i] RecommendsTM feature gives every sales professional a daily list of recommended actions, along with news and risk alerts, to help sellers focus on the actions they can take now to make a strong impact and drive results.

Future-focused tools such as Intelligent ForecastTM rely on the neural network to adapt the forecast of future sales in real time based on the activity in both the pipeline and the market. Removing bias, human error, and time from the creation of the sales forecast removes the obsession with accuracy and enables sellers to focus on action.

Historical data is still highly valuable in creating a sales forecast, but it can no longer be the only source of insight if your organization wants to grow and meet buyers where they are in today’s changing business landscape. Prescriptive forecasting is the way forward for sales. Explore Collective[i] to learn more about how our neural network can transform your organization.

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