How to Improve Your Sales Forecast & Your Company's Performance

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How to Improve Your Sales Forecast & Your Company's Performance

By Special Guest
Rowan Tonkin, Head ,Sales and Marketing Solutions, Anaplan
  |  January 18, 2018

It’s hard to overstate the importance of consistently producing accurate sales forecasts. By definition, forecasts are about the future, and in a very real sense, a company’s prospects for the future are its heartbeat. Privately held companies gain confidence in their business when leaders are able to trust forecasts. For publicly traded companies, accurate forecasts confer credibility on Wall Street. 

Accurate forecasts are also essential to sound decision-making. Confidence in forecasts reverberates across business units, letting marketing know how effective its campaigns are, informing manufacturing about demand trends, and much more.

Forecasting is also critical from a reporting standpoint. But how can business leaders ensure their forecasts are accurate?

The first step is to understand the challenges involved. Obtaining reliable data is the first hurdle, and the old garbage in, garbage out principle applies.

Salespeople typically dislike administrative tasks, so it can be difficult to compel them to input data and ensure its quality. CRM systems streamline the process, but companies that don’t consistently receive reliable data via their CRM systems are operating in the dark. 

The challenge is exacerbated when indirect sales teams are involved. If it’s tough to get good data from an in-house salesforce, it’s even more challenging to compel employees who are outside direct company control to input quality data.

New approaches like text-scraping technologies and machine learning can be effective ways to streamline data entry and assist with updating activities. 

Process matters in sales forecasting because it ultimately has repercussions for overall company performance. Business leaders who are looking to improve sales forecasting should therefore take a close look at their processes, starting with how information is collected and how frequently data is captured. Predictable and reliable input is the key.

Companies with strong processes around data collection and dissemination tend to outperform their peers, so it’s hugely valuable to get this right. It’s also crucial to recognize that different parts of the organization will need to have their versions of the truth. For example, sales managers might adjust the data submitted by their sales team to reflect certain trends or account for ongoing initiatives. 

So, how should business leaders improve their sales forecasting processes? The first step is to make sure salespeople submit data in a timely, accurate way. One best practice is to provide value back to the salespeople in return for submitting their data. Responding with analytics and insight that can help them upsell customers based on specific transaction trends is a great way to aide sales teams and in turn motivate them to perform data entry of their forecasts. 

Another best practice is to consolidate information in one place so it can be analyzed and compared to other datasets. Since different roles (e.g., salespeople, sales managers, regional managers, etc.) will have different versions of the truth, the person who creates the sales forecast needs access to everyone’s information, and that’s difficult if contributors keep separate spreadsheets containing their data only. 

With a central repository that enables all parties to contribute data via a single platform, people who are creating a sales forecast can view all data in one place instead of looking at multiple spreadsheets. A connected planning platform can also enable them to view historical data, forecast methods, and statistical analyses that can yield incredibly valuable insights, which can be applied beyond a single forecast. 

By analyzing forecast data in the context of a broader planning platform, company leaders can identify trends, such as which sales teams or individuals adjust metrics up or down at which point in a cycle, when sales cycles lengthen or grow shorter, etc. Statistical analysis also can yield clues on individual performance and even signal when a top performer may be preparing to leave the company. 

All of these insights make it easier for company leaders to plan and make better business decisions, and it starts with better access to real-time data from sales. With the right approach, business leaders can not only create more accurate sales forecasts, they can manage their people more effectively and boost overall business performance. 

Rowan Tonkin is head of sales and marketing solutions at Anaplan (www.anaplan.com).




Edited by Erik Linask
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