4 Steps to Becoming a Predictive Sales Organization
Through our interactions with these customers, XANT has noticed that as the forecasting abilities within organizations mature, they each follow a similar journey.
If you’re looking to adopt a predictive forecasting solution for your business, you’ll want to know these four critical steps to becoming a predictive sales organization.
1. Assess your pipeline’s health
Imagine you’re coaching a professional sports team that is only a few months away from their first game of the new season. In order to get ready, you need to know who on your team is healthy, who needs extra training, and which specific aspects of your play you need to focus on.
Similarly, before a company starts forecasting, they need to assess if their pipeline is healthy enough to produce the desired results. Often, opportunities will need to be cleaned up to start with an accurate picture of reality.
Some important questions to consider:
- Does my data reflect the true status of where I am in the sales process?
- How much of my pipeline is realistic?
- Do I have any blind spots?
- Do I understand how my pipeline changes over time?
All of these considerations will help you set the right foundations for proper forecasting.
2. Follow a single source of forecast truth
Once you’ve decided how healthy your team is and where you need to improve, your next step is to figure out which drills and training regimen to follow.
You can’t base your success on some program you found while browsing online. Professional teams have trainers whose job it is to create a specific program the entire team needs to follow to make sure everyone is aligned.
In order to prepare yourself properly, you need to find one source of truth and stick to that program.
The same goes for any organization looking to improve their forecasting. Companies need to make sure there’s a single source of truth for their forecast.
Imagine running a company with thousands of customers and sales reps worldwide. That leaves a lot of room for people to start making their own projections based on their own methods.
Without a common understanding of the sales process, it is next to impossible to interpret the forecast that is rolled up all the way to the top.
In order to maintain consistency, organizations need to standardize each step in the sales cycle and rely on a single source of forecast truth.
You can accomplish this by having a firm grasp on where all the opportunities are in your pipeline, so you roll up a consistent number and communicate a reliable forecast.
3. Learn from your historical yield
Let’s return to our sports analogy. Chances are your team’s past athletic performance is indicative of how your team might compete in future events. If your team played average last year, and you haven’t made any significant changes, you can expect the same kind of performance this season.
Successful teams look back on last year’s performance and pinpoint important factors, like who the high scorers were and which plays worked best, so they can make adjustments.
Sales is no different. By evaluating performance trends and applying a statistical analysis against the current pipeline, you can make a projection about how you’ll finish out the quarter.
Our customers sometimes refer to this as historical yield or run-rate analysis. Keep in mind, this is a mathematical approach and does not leverage emerging predictive science technologies or machine learning.
4. Apply machine learning to your forecast
Sports are no longer just played on the field. Professional sports teams are now making use of player data and analytics to improve in-game performance.
The future of sports management will include looking at all the current and active data (heart monitors, fitness and competitive data) to take action on the fly.
Similarly, the last phase in this evolution involves using data science and predictive analytics to determine where you can expect to finish, without inputting the numbers yourself.
Not every organization has the luxury of hiring a team of brilliant data scientists to build a predictive algorithm to tell you where you will land at the end of the quarter.
But even if they did, they’d lack access to the vast amounts of data that is needed to prove the algorithms and fine-tune them to your specific business scenarios.
For example, do you have a lot of open and closes in a month, do you have seasonality, do you have a holdout process for a specific line of business?
At the end of the day, sales forecasting is a necessary evil. No ones like to be involved in the process because it takes time away from selling. But at the same time, no organization, big or small, private or public, can afford not to do it.
No one likes surprises – not your executives, not your board members and not your investors.
Having a consistent and accurate view into your sales forecast is key to the success of your company’s growth.
Where is your company in the forecasting journey? Learn how to take it to the next level in the free ebook below.