It’s that time again and you’re ready for the sales forecast meeting. Sales representatives speculate, state their numbers: “40%, 80% chance to close…maybe?” Their answers aren’t straight forward and as a result, you start to question where the numbers are coming from. Then you notice the look of trepidation in their eyes and realize that perhaps you might miss this forecast. At this point it might be too late to take action to fix the forecast because all the numbers are in and fixing mistakes now is a backwards looking exercise. Managers don’t want to fix problems after the fact, they want to be prepared to spot a bad forecast while it’s happening and then take the necessary steps to ensure the forecast delivers on its previous commitments.
This blog offers some tips to help avoid a bad forecast so you don’t feel like you’re trying to hit a bullseye blindfolded.
Ensure Opportunities are Realistic and Achievable
In large organizations the buying process becomes increasingly complex and this makes it more difficult to predict the forecast outcome of a complex buying decision. Sales forecasts don’t always take into consideration the predictable or unpredictable factors involved in the buying decision, or the volatility of the market.
One tactic to ensure future forecasts are achievable is to make sure there are more opportunities that have a realistic chance of closing in the given period. This can be done one of two ways depending on the state and budget of your sales organization. The first is management can go through the current opportunities and decide which are most likely to close and which opportunities are not. If it doesn’t seem like there are enough likely to close opportunities then sales managers can look at future opportunities or add more pipeline for the sales representative.
The second way is to use a type of sales analytics software that would “rank” opportunities based on a number of factors and criteria to enable sales representatives to target more likely to close opportunities. This option would certainly save time and allows sales representatives to see the information first hand and make decisions based on the rankings. Both approaches reduce dependency on only some opportunities and instead develop a system that introduce more high-quality opportunities at the top of the funnel.
It’s commonly acknowledged that part of the problem when it comes to forecast accuracy is individual bias from everyone involved in the process. Their bias could be optimistic, so each forecast is above what’s realistically achievable, or they could be pessimistic and low ball their final forecast. Whatever the case may be, it still comes down to the same thing—individual bias.
There’s no complete solution to eliminate individual bias, but there are ways to manage it and that is by tracking individual sales representative behavior, current and past. When behavior is tracked it becomes easier to predict possible future outcomes. If Bill keeps sandbagging every month, there is a high likelihood he is going to sandbag next month and future months. Management can take a proactive approach by coaching Bill to understand the importance of the forecast and also best practices for forecast accuracy.
Regularly Revisit the Long-Term Forecast
It’s often the case that forecasts become less accurate the further in the future one predicts. Predicting the next month or quarter may not be too difficult, but predicting further ahead should take into account a range of probabilities because there are unknown and unpredictable factors that could affect the forecast. This is not to suggest that organizations shouldn’t predict further ahead, but rather, if they’re going to take this approach they should regularly revisit the forecast to ensure it is on-track. The forecast isn’t useful if it’s left collecting dust and the data in it becomes increasingly stale and out of date. Vortini provides historical forecast trajectories that monitor how “on-track” the forecast is. When the forecast goes off track management is warned so they can refine the forecast to meet previous financial commitments.
Improve Bad Data and Data Input
According to Ventana Research, industry data shows that most sales representatives spend four hours per week manually entering data into the CRM, with only about 40 percent accuracy. If the data that is used to create the forecast is inaccurate, then it logically follows that the forecast is going to be inaccurate. Accurate sales data is one of the most important components for a reliable sales forecast.
Other factors that contribute to poor data quality could be insufficient or bad historical data collection. Poor data quality could mean your organization doesn’t have the right data for the forecast in the first place and if you don’t have the data you need or it’s inaccurate, this makes it even harder to analyze sales trends or predict future sales. So the questions many organizations are grappling with are a) how to enforce data entry, and b) how to ensure it’s accurate.
We know that enforcing data entry isn’t as simple as telling your team to input all their opportunities in the CRM and make sure everything is up-to-date. More often than not, sales representatives are scrambling at the end of the month to input all their information and this is really a sign a bureaucratic compliance than active participation in the process. The key is for managers to explain the value behind accurate data entry, not just for the company, but also demonstrate an immediate value for the sales rep. Sales reps need to be involved in the conversation early and tell them what some real benefits could be, such as:
• Saving time
• Easier customer research
• Better data for lead qualification
If someone only updates their opportunities once a month and right before the forecast is due, this is a red flag and managers should have another look at their opportunities and final forecast submission. On the other hand, a sales rep that consistently updates their opportunities will be considered more trust-worthy when it comes to their data accuracy.
Improve the Sales Forecast with a Mix of Art and Science
As everyone knows, accurate sales forecasting is a blend of art and science—the opinions of those involved and the data used to back up these assumptions. The best way to improve the accuracy of the forecast is to use both and this has to start with a solution that values human insight and participation, along with sales analytics and machine learning techniques that help identify patterns of success and failure. Request a demo with Vortini today and learn how we’re reimagining sales forecasting.
Jess is a communications professional and Vortini’s lead content/web developer. Her current interests lie in the intersection of sales technology and machine learning. In her free time she reads a book-a-week, practices yoga, and is an avid gardener.