We know from television and movies that a woman with a crystal ball claims that she predict what will happen in your near and distant future. Her sage words of advice might impact the next decisions you make, but you’re still hesitant because let’s face it, a crystal ball is not quite science.

But still, there is a way for you to predict what is going to happen to your sales pipeline and make logical, effective and impactful decisions because of it. Commission forecasting could be a very important component of your entire sales strategy, especially if you are a modern organization based on a subscription business model.

Using a Sales Performance Management (SPM) solution is one of the most accurate and powerful ways to forecast sales commissions. By integrating with a CRM platform to draw data, your SPM has the ability to model and forecast changes in territory and quota assignment and incentive plans that affect your performance metrics and directly influence the success of your strategy.

There are a few very important things to consider when you are selecting your very own crystal ball, an SPM solution that can truly perform accurate sales forecasting. Many SPM vendors claim that their solutions are precise, but they might just be as accurate as that fortune teller.

1. Is it just in the Sales Pipeline?

The pipeline is usually a starting point for forecasting, but does it ever serve as the actual forecast?  Once the pipeline is established, there is a bottom up adjustment process that has to happen in order to refine the forecast. Then, if the forecast spans a long enough time or the company has a short sales cycle, the forecast might need to be supplemented with some top-down or driver-based additions for the forecast periods that aren’t covered in the CRM. This is especially important in subscription-based businesses where commission expenses don’t come exclusively from a CRM. With the addition of Customer Success and other teams focused on retention, expansion and growth, the source of data becomes much broader. The CRM doesn’t include the data for all of the teams on commission plans, so the SPM solution needs to be able to access data from additional systems.

2. How robust is your Plan Modeling?

Modeling plans and forecasting data from a compensation earnings perspective is an essential function for a successful commission forecasting. To ensure accuracy, it’s important to be able to quickly modify the mechanics and data points within the plans and the forecast data. Being able to quickly and easily make adjustments to your plans and forecast data gives you the ability to see a clear picture of where you are and if there are any areas where you have to readjust priorities to ensure you reach your commissions goals.

3. Are you accounting for the Accounting Regulations?

Another aspect defines the effectiveness of your SPM solution is its ability to model the compensation accounting rules to accurately calculate the accrual, expense and capitalization amounts based on the forecast data. For example, if you are able to model compensation accounting rules then you can funnel your sales forecast through your compensation plan to calculate compensation earnings then accrue monthly based on the monthly seasonality of your sales.

The ability to forecast and make informed decisions based on actual data, gives sales and finance leaders insight to their organization’s commission expense spending helping to mitigate risks. For a subscription-based business this is especially important. Insight into anticipated costs allows organizations to forecast expenses and earnings and course correct, if necessary,  in real-time. And remember, near integration comes from near real-time processing. Real integration comes real-time processing.

A robust SPM solution is one of the most accurate and powerful ways to forecast sales commissions, so why leave your fate in the hands of a fortune teller when you can have your very own crystal ball?


To discover how Obero SPM can help you with commission forecasting, request a personalized demo.

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