7 ways sales and marketing teams can drastically improve their forecasting

20th Jun 2018

Sales forecasting can be perilous, for a variety of reasons. How can sales and marketing teams improve the forecasting process they currently have in place? Visyond founder, Gianluca Bisceglie explains.  

Growing businesses need a clear idea of where they are and where they are going. Sales forecasts are a vital part of forward planning. As an owner or senior manager, it’s essential that you know the numbers for the coming quarters.

You need to have a firm grasp of the value of the deals in the pipeline. How many new leads are coming through every month? What are they worth? Are you on target, or do you need to take corrective action?

With effective forecasting, you should be confident in your sales and marketing pipeline. However, Sales Management Association research has found that only 44% of executives think that pipeline management is effective. Conversely, those companies that implement a more formal forecasting process generate 28% more revenue than their competitors.

Only 44% of executives think that pipeline management is effective.

The issues with forecasting

Forecasts are predictions. When it comes to sales and marketing, numbers are often too ambitious or too optimistic. Sales and marketing are growth areas. Growth makes managers hopeful.

Hope makes sandcastles out of ambition, turning otherwise pragmatic members of the team into excessive optimists, skewing the numbers accordingly. Senior managers and stakeholders will challenge overly optimistic forecasts, unless they're invested in an ambitious outcome, making it harder to set realistic targets.

Other failings in current forecasting models include the difficulty of using Excel to collaborate. Often, companies need experts to create and fix formulae that makes it possible to collate numerous data sources and analyse the results. Putting together a forecast when multiple teams and stakeholders are involved can take weeks or months. Versions of the same Excel spreadsheet multiply exponentially.

It can be a nightmare trying to collate this information. None of it is secure, either; a simple mistake or malicious act could result in sensitive forecasts ending up in the wrong hands.

Hope makes sandcastles out of ambition, turning otherwise pragmatic members of the team into excessive optimists

Surely, there is a better way, improving processes and tools that companies can use to create more accurate forecasts quicker than current methods allow? Here are seven.

#1: Streamline data gathering

Members of your marketing and sales team have valuable data to contribute. It sits in silos, scattered. In CRMs and inboxes, in Excel spreadsheets and documents. To create an accurate forecast, this needs to be brought together and assessed. Some of it will be useful, the rest can be discarded.

Since forecasts are usually only created once a year, or adjusted every six months, this should be a predictable process. But when the urgent gets in the way of the important, those contributing to forecasts aren't always as organised as companies need.

Appointing a manager responsible for the data gathering, with top-level support and resources, will streamline this process. Using software that allows you to upload resources (like supporting documents for assumptions) and track every contribution to the same collaborative document, reduces the need to have many versions of the same files, countless emails going back and forth, and consequent data chaos.  

#2: Take a collaborative approach

Collaboration is key. Try to ensure office politics and departmental tensions don't complicate the process. Get everyone involved on the same page early in the process, setting clear guidelines, expectations and milestones to aim for.

#3: Improve field data collection

Companies with field sales teams struggle with pipeline management. With many using CRMs, information about sales visits and calls rarely comes through in real-time. Field sales agents, unlike inside sales teams, often feel unrestrained from office boundaries, and therefore more likely to focus on the easy prospects, or those they enjoy visiting.

Both factors reduce the accuracy of field sales inputs to forecasts. Consider alternative tools to ensure you can keep a closer eye on what they do, who they meet, and how they perform.

#4: Speed up forecasting

With more effective, collaborative forecasting tools, it should be possible to speed up the process. If, for example, the operating environment changed quickly (e.g. an economic downturn, or losing a big client), a scalable and solid forecast should be revised in a few steps, ideally on the fly. Senior managers and stakeholders shouldn’t have to wait weeks or months for information they need tomorrow.

#5: Reduce cognitive bias

Group-think is dangerous when creating forecasts. Nothing worse than allowing a few louder voices to set the tone, or a bias towards a certain outcome to skew the numbers. Reducing the difficulties around data gathering, collaboration and analysis gives your team more time to consider the context behind the numbers. As a result, bias should play less of a role in the forecasts the team create.

#6: Take off the rose-tinted glasses

Excessive optimism - or pessimism (if you’ve had a bad quarter) - taints the outcome of forecasts. Taking an objective approach to the data and ensuring the leadership team is consulted will reduce the chance of new forecasts setting you up to potentially fail.

#7: Conduct scenario planning

Plan for multiple scenarios. If sales are up more than expected, or down. Plan for good and bad quarters, for new product launches and delays. With the right tools, you can stress test the figures and different outcomes, making it easier to know how the business will perform under a variety of circumstances.

Gianluca Bisceglie is the founder and CEO of Visyond, a cloud-based spreadsheet software that disrupts the way people work with spreadsheets ­– allowing secure, selective and interactive sharing, minimising errors, and performing collaborative analyses in real time.


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