<p>In this host-only episode of the RevOps Lab, Janis and Philipp take stock of what three years of building a forecasting tool — and hundreds of conversations with sales leaders, RevOps teams, and CROs — have taught them about getting to a reliable, repeatable forecast number. They unpack why forecasting is a process (not a number), why AI only works on top of a clean data foundation, and how the best companies combine roll-up, dynamically weighted, and AI-predicted forecasts into a single operating cadence.</p><p><strong>We cover:</strong></p><ul><li><p>Why forecasting accuracy is the <em>output</em> of a well-run sales org, not the input</p></li><li><p>The operating cadence: weekly meetings, deal reviews, and stakeholder alignment that make forecasting work</p></li><li><p>Building the data foundation: activity capture, multi-threading signals, conversation intelligence, and CRM autofill</p></li><li><p>Why deal hygiene and shared qualification criteria (SPICED, MEDDIC) are non-negotiable before you forecast</p></li><li><p>Splitting the forecast into new logo, expansion, and renewal — and why bookings ≠ consumption</p></li><li><p>The three-pillar forecast: dynamically weighted + bottom-up roll-up + AI prediction (with corridors, not single numbers)</p></li><li><p>How to run a roll-up motion: baseline vs. best case, rep forecast vs. independent manager forecast</p></li><li><p>Why running roll-ups in spreadsheets breaks down at 50+ reps</p></li><li><p>Calculating dynamic stage probabilities by rep tenure or team — and when it&#39;s worth doing</p></li><li><p>Why AI predictions are only as good as the data foundation underneath them</p></li></ul><p><strong>Links:</strong></p><ul><li><p>Janis Zech on LinkedIn:<a href="https://www.linkedin.com/in/janiszech/"> <u>https://www.linkedin.com/in/janiszech/</u></a></p></li><li><p>Philipp Stelzer on LinkedIn:<a href="https://www.linkedin.com/in/philippstelzer/"> <u>https://www.linkedin.com/in/philippstelzer/</u></a></p></li><li><p>WeFlow:<a href="https://www.getweflow.com"> <u>https://www.getweflow.com</u></a></p></li><li><p>WeFlow RevOps resources:<a href="https://www.getweflow.com/revops"> <u>https://www.getweflow.com/revops</u></a></p></li><li><p>Join the RevOps Chat Community:<a href="https://www.getweflow.com/community"> <u>https://www.getweflow.com/community</u></a></p></li><li><p>Subscribe to the RevOps Letter:<a href="https://www.getweflow.com/revops-letter"> <u>https://www.getweflow.com/revops-letter</u></a></p></li><li><p>Operating Cadence master deck: ping Janis or Philipp on LinkedIn to request</p></li></ul><p><strong>Chapters:</strong></p><ul><li><p>(00:00) Intro: Has AI fundamentally changed forecasting?</p></li><li><p>(01:34) Why forecasting is a process, not a number</p></li><li><p>(02:25) What an operating cadence actually looks like week-to-week</p></li><li><p>(04:23) The data foundation: why CRM alone isn&#39;t the system of truth</p></li><li><p>(06:53) Anchoring deal conversations on a shared qualification methodology</p></li><li><p>(08:42) How AI adds an objective layer through automated capture and CRM autofill</p></li><li><p>(09:29) Stage entry/exit criteria and deal signals for deal health</p></li><li><p>(13:06) Why &quot;comparable deals&quot; matters as you scale past 50 reps</p></li><li><p>(14:23) Forecasting as the end result of a well-functioning sales org</p></li><li><p>(16:05) Splitting forecasts: new logo, expansion, renewal, bookings vs. consumption</p></li><li><p>(17:22) The three-pillar forecast: dynamically weighted, roll-up, AI prediction</p></li><li><p>(18:50) Roll-up forecasting: baseline vs. best case, rep vs. manager numbers</p></li><li><p>(24:07) Anatomy of a roll-up: hierarchy, gap-to-quota, pipeline coverage, deal-by-deal</p></li><li><p>(26:43) Why spreadsheets break down for roll-up forecasting at scale</p></li><li><p>(28:07) AI prediction models: aggregate vs. deal-by-deal scoring</p></li><li><p>(29:02) Dynamically weighted forecasts and rep-level stage probabilities</p></li><li><p>(32:44) Why AI predictions only work on top of clean data foundations</p></li><li><p>(34:27) Book recommendation &amp; close</p></li></ul>