One of the single most important processes at any B2B company is sales forecasting. The number that the sales team delivers drives a series of other critical processes, from resource allocation, inventory planning, attracting investors, to reporting out to the street. Yet, the tools companies typically rely on for this process are largely outdated.
A significant portion of B2B tech companies still use a combination of CRM reports and complex spreadsheets to produce their forecast. This is despite the fact that we frequently see in the news that spreadsheets blunders have cost companies millions and that studies have shown that 90% of spreadsheets contain errors.
Here are the TOP five risks of using CRM reports and spreadsheets to drive your sales forecast:
1. Humans Introduce Million Dollar Data Entry Errors that Compromise Forecast Accuracy.
As your organization grows, spreadsheets inevitably become more complex. Over time, formula and data entry errors creep into the spreadsheets, which severely and materially impact forecast accuracy.
Accounting for spilt deals, currency conversions, and sales crediting issues make data entry mistakes common. Additionally, errors creep into the spreadsheet as the sales organization changes. Spreadsheets are often designed to handle a specific organizational rollup. But sales reps churn, and new reps and overlays are added. Matrix organizations become common, and spreadsheets can’t always easily adapt, resulting in deals or numbers getting “double counted.” As staff turns over, understanding how to run and maintain the spreadsheet is increasingly difficult.
It’s happened to all of us — it only takes one formula or data entry error to completely throw off your entire forecast, and erode the credibility of the sales and sales ops team.
2. Forecast Numbers Constantly Change, Making Spreadsheets Quickly out of Date, and Leading to Arguments Over the Data.
More often than not, the latest data entered into CRM is not reflected in your spreadsheets. We estimate that 99% of the time, these two tools are out of sync. We understand why people started using spreadsheets — using CRM alone for forecasting doesn’t work. CRM systems do not have strong forecasting modules. They leverage single point in time data and do not offer multiple forecast views across different business pivots. Using spreadsheets to augment your CRM, however, isn’t the answer.
Spreadsheets are generally updated once per week with data from CRM systems, so the minute reps change a deal status or forecast, the spreadsheet is out of date. Since spreadsheets often contain stale data, this leads to a lot of time wasted arguing over numbers, and takes time away from coaching and more strategic deal-level discussion.
3. Sales Ops Wastes Hours Per Week Working on Spreadsheet, Rather than More Strategic Activities.
A vast amount of time is spent collating, maintaining, and verifying data in spreadsheets. Excel spreadsheets were not designed to do large collaborative projects, so typically sales operations builds multiple spreadsheets that are distributed, copied and used. Version control can become a big issue. Sales ops must distribute, then collate, check and often re-enter information into a master spreadsheet that becomes the official forecast.
The problem is amplified at organizations with multiple levels, as each level of the organization adds their own judgement to the forecast, and Sales Operations must re-collate, re-check and re-enter data in multiple master spreadsheets.
Sales Operations is faced with the unenviable task of accurately rolling up a forecast in a short period of time with a system that is inherently unstable. Your team ends up wasting time that could otherwise be spent on more strategic activities such as pipeline and territory reviews.
4. Spreadsheets Provide Limited Visibility into the Business, and Don’t Help You Answer Basic Sales Questions.
In the CRM-Spreadsheet forecasting process, the CRM holds the detailed data on deals and pipelines, while the spreadsheet holds summary forecast information and historical information. Since the two system are not synced, you cannot drill down into the forecast to see what deals make up the forecast. This process is further complicated by the judgment added by each level of sales management.
You don’t have the visibility you need to run your business or the forecast call. You’re unable to see which deals are impacting your forecast. You can’t see judgment applied across the hierarchy. Answering routine and frequently asked questions is next to impossible. You can’t easily tell if a deal is in or out of forecast, what changed in the forecast and more importantly, why.
5. Spreadsheets Do Not Offer Predictive Insight.
Leading sales organizations now leverage big data and AI to do predictive forecasting, but the existing CRM/Spreadsheet system does not offer predictive insight. Spreadsheets contain only summary level information and CRM systems keep limited historical data that machine learning algorithms would need to make AI-based predictions.
You’re unable to leverage your historical data to gain insights into how your quarter will unfold or see an objective AI forecast for comparison against your team forecast.
Forecasting must be modernized. Using single point in time CRM reports and amalgamating spreadsheets cannot be the future. Early adopters such as Xactly, Splunk and Apttus have moved to a cloud-based forecasting tool, which delivers the following benefits:
- Automates the rollup to eliminate spreadsheets and the errors that come along with them
- Enables multiple forecast views with the click of a button, giving you a 360-degree view
- Has a deal-level forecasting feature that shows which deals are in and out of forecast
- Provides the ability to drill down into the deals making up your forecasts
- Provides visibility into deal-level detail and judgment applied across every level of the organization
- Keeps a complete history of every every deal, pipeline and forecast so that machine learning models can be used to do predictive forecasting
- Syncs with your CRM for always up to date data