When it’s time to upgrade or build new sales forecasting tools and processes in your company, it’s a good idea to stop and develop some requirements.
In the 8 years, I have been working as a sales data analyst, I’ve seen companies across all stages of development using various tools to build forecasts. From educated guesses, Excel spreadsheets, complex reports in their CRM, to dedicated teams of analysts using sophisticated tools.
Based on what I’ve seen, I have compiled this short list of requirements for a good sales forecasting tool. I haven’t yet found a single tool that would satisfy all of these criteria, so you may need to make some trade-offs.
Although there has been much progress made in Machine Learning in recent years, many forecasting tools seem stuck in the past. Unfortunately, they are often still based on reps’ educated guesses or simplistic if-this-than-that formulas.
It’s time to look at modern toolkits like AI if you want to get an accurate forecast. Especially if we’re talking about predicting the future with a large sales team, working in many market segments, using a multi-step sales process and selling multiple products or services. The complexity grows with each variable, but with AI tools, the accuracy actually grows with more variables and more historical data.
This is the most frustrating requirement. A tool says that I’m not going to hit my quota this quarter. But will it elaborate on why it “thinks” that? Will it suggest what I should change to get a better forecast next time?
Answering those questions requires connecting aggregate forecast numbers back to particular deals still in the pipeline. It requires exploring their similarities to opportunities in historical data. Simply saying “Your conversion rate dropped” is not actionable.
The actionability of the insights you can derive from a forecast should be part of your criteria when choosing a forecasting tool.
Visibility across the company
Sales forecasting is traditionally a tool primarily used by management. However, the success or failure in hitting a goal largely depends on the sales team. With correct security and access permissions, the sales team should be able to see how each sales division, team, and client they work with fits together to reach a common goal.
The sales team is also the first to notice when things are not on track. Their input can update the forecast more realistically and it’s their actions that can put it back on track. So, it makes sense to give the sales team access and visibility on the appropriate part of the goal they need to execute.
New clients and new data come in every day. A forecast that is built once a month becomes stale after the first week. This affects the quarterly forecast even more.
A good sales forecast is “live” and updates as soon as new data is available. Even more, it should alert you as soon as you get off track, or if there are any major changes in the forecast.
At the same time, it’s important to be able to review past forecasts in retrospection. If the forecast can change every day, you will need a way to compare a forecast from a month ago to the most recent version to see what has changed and how much progress you’ve made.
Ease of use
If you’d like to use the most sophisticated forecasting tools available on the market, no doubt you will need a dedicated analyst (or maybe even a team). However, this should not be the case – as mentioned before, the sales forecast should be a tool that supports management and the sales team in meeting goals.
A complex tool that requires a science degree to use is going to be expensive and difficult to access, understand, and interact with for most of the people in your management and sales teams.
Today, most of the products and services you can buy store their data on the cloud. This is great for productivity, accessibility, and cost optimization, but it decreases the customer’s ability to manage their data security policies.
Sales and financial records, along with emails, are some of the most valuable datasets available and can become a target for hackers and business espionage. Before allowing any tool to have full access to your most precious data, you should verify their security models against external threats as well as the ease with which you can set permissions and access rights within your organization.
You can hire a company to complete a dedicated analysis of your sales and they’ll build a great forecast for you, but that comes at a price. I’m sure it’s possible to build a tool to automate much of the work and decrease the price.
Unless you’re a small startup and all you need is an Excel template (which you can get for free), getting a quality, automatic sales forecasting tool will be much cheaper than hiring or contracting out a team of analysts.
When it comes to sales forecasting, after seeing the same problems over and over again in the companies I have worked with, I decided to build TwelveZeros – the AI-based sales forecasting tool. It integrates with Salesforce (and other CRMs), and within a few minutes to build a sales forecast for your business.
We’re building it with the goal to deliver accurate sales forecasts that meet the above requirements, so if this list resonates with your needs – give it a try. We have a 14-day free trial with no CC required – just fill out the form below to start.
Co-founder, Head of Data and Machine Learning at TwelveZeros. Out of the 10 years of his professional experience building software, he spent last 6 solving problems of sales organizations using a scientific approach, data, and AI tools.