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Faster Horses and Better Buggy Whips

Writer's picture: Bill KantorBill Kantor

Updated: Feb 10

Do you want to report sales news, predict it, or change it? Hold that thought.


Revenue Tech platforms abound. But are these applications just automating outdated methods or delivering innovation? These two quotes come to mind.


If I would have asked people what they wanted, they would have said faster horses. ~ Anonymous, often misattributed to Henry Ford. 

The <better> buggy whip analogy is “an obscurity sitting on an anachronism. ~ Daniel M. G. Raff

Have recent innovations in RevTech and AI forecasts improved on the traditional approaches? They offer many more summary reports, streamlined data entry, and claim better accuracy. But they don't fundamentally improve the sales forecasting process, or help you sell more. 


These applications may be the faster horses and better buggy whips of sales/revenue operations. There’s a better alternative.



Classification forecasts, the time-honored way

For years, salespeople forecasted using bottom-up "classifications" of active deals. CRM systems provide a Forecast Category field for this—employing terms like Commit and Best Case to describe the likelihood of a deal closing. Deals are classified, and summarized in rollup reports. Then management makes a “call”—a made up number—overriding the rollup. 


Rollup forecasts have their limits. A Commit list can be a very good predictor, but with short lead times—often only a few days. The Best Case provides more lead time but has very high variance. Neither of these includes forecasts for new pipeline that will be created and closed in the forecast period. These things may be addressed by management's made-up number. 


Businesses have forecasted this way for years. It started on paper, then moved to spreadsheets, and to web applications. And in the process, RevTech vendors have added lots of reports. But the forecasting process is unchanged. They've replaced paper with a "Submit Forecast" button.


The great innovation of the web forecasting applications is facilitating hierarchical management opinions about what their teams will deliver. This offers a more formal way to incorporate prospective new pipeline (it's often in the made up number); to adjust for inconsistencies in how individuals make forecast category calls, and to make up for the short lead time of Commit deals.


It is more streamlined, but is this any more informative? That depends on what you hope to get out of it. Here are the possibilities:


  • Accurate forecasts

  • Resource allocation priority lists

  • Accountability


Accurate forecasts

We’ve looked at the raw rollups of Commit and Best Case to assess their accuracy. The results are very unattractive. Here’s a very good example [1]: 75% average Commit accuracy by amount (60% – 85% range), with a few days advance notice, for a list that covers less than 85% of the closed sales during the quarter. Best Case rollups are less reliable and highly volatile. 


Before we dismiss this approach, I have to acknowledge that we have no visibility into the judgment calls that sales leaders make concerning their "calls" (an informed but made up figure) on where they will land. They may be great. But that’s hard to do consistently. People are really bad at assessing probabilities. And sales outcomes and timing are inherently volatile. So I would venture that these are similarly inaccurate but give an earlier indication. Although people’s recollections may be different.


Resource allocation priority lists

This may be the most effective use of classification forecasts. They inform the business about the important deals. And this affects how the business allocates resources. 


Accountability

Having people make forecast classification calls does add accountability to the number. But this is a two-edged sword. Accountability drives salespeople to be very conservative about calling a deal in the Commit. Hence the short Commit lead times. And these rollups will be volatile based on hierarchy.


A manager with many deals in the Commit, benefits from averaging. Deals that arise during the quarter can make up for slips. And managers can adjust their forecast “calls” to allow for that. But an individual contributor may have only a handful of deals. Accuracy at the individual contributor level is therefore more volatile but sometimes highly accurate.


Unfortunately we may never know if the observed accuracy is real or due to chance. It would take many quarters of forecasts to make a strong statistical test. This diminishes the validity of forecast accuracy accountability—at least for individual contributors and possibly even for sales managers—depending upon how many transactions they are forecasting.


RevTech to the rescue?

To address the accuracy, RevTech vendors offer hyper-accurate AI forecasts early in the quarter. While these sound attractive, they miss the point. Accurate forecasts don’t pay the bills. You need to maximize sales. Beat your goal, not meet your forecast. 



So where does that leave us? RevTech has streamlined the process but not changed it. These applications offer summary stats to show you what happened but not how to sell more. AI forecasts may be an improvement over classification rollups or made-up forecast calls—particularly, early in the quarter. But accurate forecasts definitely don't help you sell more.


The biggest value to the forecast submission process is to inform resource allocation.


So RevTech vendors have focused on helping you report and predict the news. What about creating the news?

Improve your sales efficiency.

Try Funnelcast.


A new and simpler way

To maximize sales, get back to basics. 


  • A sales process with well defined stages

  • Diligent maintenance of CRM opportunity data for Stage, Amount, Close Date


Note that these are the minimum requirements for using a CRM to track deals. Everything else (for instance activity metrics, notes, next steps, industry classification, ICP scores, lead scores…) is secondary. Use them if they have predictive power. But make sure you get the basics first.


With this minimal data, you can make realistic forecasts for open pipeline and prospective new pipeline. Current month to next year. Yes. It’s that simple and robust. 


More important, the same data can provide optimized ranked deal priorities from which you'll sell more than from traditional resource prioritizations (Forecast Category, deal size, or whatever). Instead of spending time submitting and overriding forecasts with opinions, you'll be focused on more winnable deals and selling more. 



Faster Horses or Real Innovation?

RevTech and AI forecasts may offer incremental improvements that help you report or predict the sales news, but they haven’t fundamentally changed the way we forecast or how we sell. These are faster horses and better buggy whips—refinements of outdated methods that don’t address the real challenge of maximizing sales.


Your call. Faster horses and better buggy whips vs. real innovation. Do you want to improve your sales reporting and streamline forecasting, or to maximize your sales.


Give us a call when you are ready.


 
  1. Computed as: the value of all won deals in the quarter that were classified as “Commit” during the quarter/the value of all deals that were classified as “Commit” during the quarter.

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