Not using AI in your revenue forecasting processes yet?

Here’s what you’re missing out on:

1) Greater forecast accuracy:

Nicole Ward, Senior Director of Revenue Enablement and Operations at OneSource Virtual has achieved 95%+ forecast accuracy for four quarters in a row since rolling out their AI tool. It has also cut down the time it takes to build their forecast from days to just hours.

2) Faster forecasting:

David Taub, Senior Director of Revenue Operations at HydroCorp, runs a team which started with no formal forecasting. Now they routinely hit 93%+ accuracy most months since they started using new, AI-backed methods and tools. What used to take half a day for him and his sales leader now takes only 10 minutes.

3) Greater pipeline health:

Beyond just rolling up numbers, these tools are helping with pipeline health. They offer visual dashboards that show stalled deals, assess how healthy different stages of deals are, and even predict gaps in future sales. All of these help sales teams take action more quickly.

3 forecasting mistakes that are slowing you down

The first step in using AI to produce accurate revenue forecasts more quickly is to understand where you’re going wrong right now.

Here are three mistakes you’re probably making. Fix these first:

1) Not using live data

Take the end of a sales period, for example. Nicole Ward says many managers still export all their sales data into spreadsheets.

Why? Because it’s familiar. It’s fast for them to play with the numbers and explore “what if” scenarios.

The problem? As soon as they copy the data into a spreadsheet, it stops being live. New changes to deals aren’t copied across to the spreadsheet, which makes any forecast built on that old data also grow old very quickly.

2) Sales teams themselves

Another common source of slowness stems from the sales team itself. Specifically, their data hygiene.

Laura Fu, Head of RevOps and Strategy at DevRev, points out that, if sales reps don’t put in good, correct information in the first place, then any forecast made from that bad information will also be wrong. It’s the old “garbage-in, garbage-out” maxim at work again.

3) The process as the problem

David Taub agrees that sometimes the tools are the problem, like Nicole put forward. Only using spreadsheets, for example. This can be messy, and can make it hard to track changes over time.

David suggests that more often, though, the problem is the lack of a standardized forecasting process. When everyone has their own method, or if people keep going back to old ways of doing things despite coaching, it slows everything down. This is especially true for bigger sales teams, where it's hard to check every deal by hand.

So… Is the problem with the tools? Or is it with your process? Here’s how you answer that question:

If your sales team is doing everything right, but the information still isn’t easy to see or use, then it's a tool problem. But if the sales team isn’t following best practices, or isn’t following good data hygiene, or not following the steps, then it's a process problem first. No fancy tool can fix bad habits, so fix the habits first. The tools can wait.

2 ways AI can help make forecasting faster

Once you’ve confirmed it’s not the processes causing the issues, turn your attention to tools.

While pulling all your data out into a spreadsheet slows things down, pulling it into the right tool (or integrating the right tools with your existing platforms) really speeds things up.

According to Laura, AI helps you move faster by spotting things you’d miss.

AI can:

1. Act as an early warning signal when deals are at risk.
2. Point out deals that might close sooner.

In other words, AI can accurately spot risks and opportunities. It has access to a wealth of information about each individual deal.

David points out that some AI tools will listen to sales calls. These tools can pick up on direct hints from buyers that a deal might be at risk. This saves hours of work by quickly pointing out how a deal might fall apart, even if the sales rep feels good about it.

When we spoke to Tana Jackson, Vice President of Operations at Upright Labs, at our recent Revenue Forecasting Summit. She suggested using AI to pull information out of sales conversations, transform it, and then push it into CRM fields for maximum efficiency.

In the same conversation, Anjali Chawla, Head of Strategy & Sales Operations, Europe at Nokia, suggested applying machine learning to historical win/loss data, to gain a killer understanding of your deal cycle.

The ultimate benefit of all this is that it helps reps focus their efforts on the highest-ROI opportunities. AI tools just see facts, without feelings, and help make more objective decisions about your pipeline in less time.

Challenge: Getting salespeople to trust new tech

Getting people to trust new tools is always a challenge. AI or not.

Sales reps might have years of experience, and have come to trust their intuition. When new technology tells them that intuition is wrong, you have to expect some pushback.

Your leaders might even be surprised how accurate AI can be. After all, it can process much more data than a human can (and much more quickly). It can be hard for people to give up control and trust new tech, even if that tech is ready.

Nicole calls this what it is: “change management.” She says rolling out the new technology is a sprint, but getting people to use and trust it is a marathon. It takes ongoing teaching and showing salespeople exactly how the AI helps them.

Sales is still very much a human sport. AI doesn’t change that. But AI tools can act as a check on the calls your reps make. In turn, this helps your leaders ask tough questions if the AI's data doesn’t match a rep’s feeling about a deal.

Challenge: When to bring in new forecasting tools

When’s the right time to invest in new AI or forecasting tools?

Of course, it depends.

If your forecasting accuracy is very poor, it might make sense to invest in a tool even while your sales team is still very small. If, no matter how much you work on your process, your reps still struggle to hit their numbers, you eventually have to change tack. A good tool can help you see what’s really going on with each deal.

A good rule of thumb, though, is to not solve problems you don’t have yet. If you’re forecasting manually, and it’s not causing you any problems, don’t fix what ain’t broken. You’ve no doubt got real, pressing problems to solve that warrant more budget and attention.

Once your current forecasting process stops working, begins taking too long, or only reveals the full picture to you right before a big meeting, it’s probably time for a tool.

But, importantly, you must actually have a clear, well-defined process before you invest in a tool. If your process is messy, the tool will either only make the mess clear, or worse, it’ll amplify it.

3 tips for rolling out new forecasting tools

1) Think big

New tools represent new opportunities for greater depth, accuracy, and efficiency in your forecasts. If up until now, you’ve only looked back at historical data, try implementing some predictive analytics based on live data to help with real-time decisions. This means focusing on customer signals (like how many support tickets they have) more than just sales stages.

2) Make sure everyone’s on board

It doesn't matter what tool you buy if your salespeople don’t use it. Unless everyone in your sales teams can use your tools or processes, they might as well not exist. So make sure your team has the resources they need to be able to use the new tools, and follow your processes.

3) Run a data quality bootcamp

Finally, before rolling out a forecasting tool, it's wise to run a deep data quality boot camp. This means making sure your data is clean and correct from the start.

Also, it's important to launch a proper enablement program, with the right training and support, at the same time as you launch your forecasting tool. Every salesperson needs to know exactly how your AI-powered insights will help them hit their sales targets. Doing this preparatory work early can help you realize the benefits and ROI of your tools much faster.

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