RevOps Lab · 2026-05-04 · 37 min
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. We cover: Why forecasting accuracy is the output of a well-run sales org, not the input The operating cadence: weekly meetings, deal reviews, and stakeholder alignment that make forecasting work Building the data foundation: activity capture, multi-threading signals, conversation intelligence, and CRM autofill Why deal hygiene and shared qualification criteria (SPICED, MEDDIC) are non-negotiable before you forecast Splitting the forecast into new logo, expansion, and renewal - and why bookings ≠ consumption The three-pillar forecast: dynamically weighted + bottom-up roll-up + AI prediction (with corridors, not single numbers) How to run a roll-up motion: baseline vs.
#118 Inside RevOps at a $100M+ ARR Consumption-Based Business - with Markus Jaensch, Head of RevOps at Aiven80 / 100
#117 Why Your Forecast Is Inaccurate (+ How to Fix It) - with Andy Smidmore, RevOps Leader (ex-Confluent, Cloudera, Docker, Ditto)
#115 Building a Customer-Centric Revenue Org - with Robert Kaiser & Christoph Dünhuber, Revenue & RevOps Leaders at Tacto
#114 Running RevOps on AI Workflows & Agents - with Eric Portugal Welsh, Head of RevOps at PlanetScale
#113 How to Earn Your CFO’s Trust - with Stephen Diorio, Author of "Revenue Operations"