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  • Writer's pictureBrian Shea

Why CEOs MUST Apply Precision Engineering Disciplines to Sales Forecasting

Updated: Jan 12


Precision engineering is the discipline of designing a machine or instrument so it can maintain, measure, or move to a position or follow a path with a level of accuracy that is many orders of magnitude smaller than the size of the machine or instrument itself.


Precision engineering offers a range of benefits, including improved product quality, increased efficiency, and reduced costs.


According to #KornFerry "fewer than 25% of sales organizations have a sales forecasting accuracy of 75% or greater. And inaccurate sales forecasting causes plenty of trouble when it comes to predicting sales performance and meeting revenue goals." Current sales forecasting isn't very precise, is it?


This week kicked off our 2024 LinkedIn Live business growth sessions with a topic that garnered a lot of interest, post webinar discussions. Simply put, sales forecasting accuracy has never been so hard. To fix it requires the CEO to be a precision superheroes.


Our featured guest was Jennifer Ives, Founder & CEO of wateringhole.ai. Jennifer is an award-winning business executive with more than 20 years of experience leading high performing teams, crafting successful GTM strategies, and driving double-digit financial results at VC- and PE-backed digital product and data intensive companies around the world. She is the current CEO/Cofounder of Watering Hole AI, a fast growing AI transformation company focused on helping CEOs, CROs, and CMOs drive new revenue via AI modeling - holding the belief that bespoke, small data sets are the new currency.


One word Ms. Ives used repetitively was........ precision.

Precision [ pri-sizh-uhn ] noun

  1. the state or quality of being precise.

2. accuracy; exactness:

to arrive at an estimate with precision.

If you missed the event, here's the replay https://vimeo.com/901246805?share=copy

So why is sales forecasting so hard? Jennifer pointed to "precision", or a lack thereof. First, most CEOs don't demand forecasting precision. This operating standard directly impacts the leadership team's decision making on all parts of the Go To Market machine from hiring, to functional org design, to technology investments, to product development, to marketing, to pre-sales, to sales engineering, etc etc etc. Demand precise outcomes and inspect every revenue system design. There is functional precision required across the entire GTM engine. Next, there is vast amount of buyer data intelligence available. How is the team using intent intelligence technology to precisely understand which accounts are in the market. We now know that 70%+ of the buyer's journey is completed without engaging a seller. Intent intelligence is the flashlight for illuminating “above the funnel” accounts. Third, CEOs must lead the full, 110% transformation to being a customer centric organization. What does this mean? It's when GTM leaders can precisely translate the engagement strategies reflecting using a deep understanding account's signals across every senior buying function. These strategies include deliberate thought leadership tactics aligned to the customer’s GTM strategy, industry trends and challenges, competitors, regulatory impacts, etc. Pressure test all assumptions on how buyers are buying. Forth is the the requirement for consultative selling with active sales leadership engaged. This begins with a buyer engagement strategy between sales AND marketing, not sales versus marketing. With 8-12 decision makers and influencers associated with every B2B purchase, the requirement is consultative, coordinated precision at each engagement point.


And finally, the GTM team needs precisely defined roles and responsibilities, with precise measurements of customer centric performance. All existing workflows and playbooks get rebuilt.


CEOs must require precision for their GTM teams to maintain trust with their investors, board members, senior leadership teams and the organization as a hole. Or CEOs can chose to to be of the 75% of organizations with less than a 75% forecasting accuracy.

Yes building these disciplines is hard. We can help.




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