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Jason
Christensen
Chief Revenue Officer
GSC Technologies
In every environment, from turnaround moments to periods of growth, Jason has helped organisations find clarity where there was noise and direction where there was drift. He has built programmes that transform retailers into destination experiences, enabling them to serve their core customers in deeper, more meaningful ways. He has reimagined underperforming channels through structure, rhythm, and cross-functional belief, and expanded private brand portfolios by connecting loyal customers with products they had not previously imagined, but instantly recognised. Jason has also partnered with charitable organisations to raise funds, clean the environment, build homes for people experiencing homelessness, feed those in need, and bring communities together. Throughout his career, he has led with integrity and insight, and built with heart. He drives alignment, shapes strategy, and fosters trust-filled cultures that turn ambition into momentum. Jason believes the most enduring results are not measured solely through metrics. They are experienced through people, purpose, and the way teams rise, collaborate, and win together.
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19 November 2026 09:45 - 10:15
Fireside chat: Why doesn't anyone trust the forecast?
Revenue forecasting has always been part science, part guesswork, and most RevOps leaders know the frustration of a forecast that looks confident on a slide but falls apart the moment the quarter closes. This session digs into why forecasting still goes wrong so often, from messy pipeline data to over-reliance on rep intuition, and what's actually changing now that AI is being layered into the process. Rather than treating AI as a magic fix, the conversation will focus on where it genuinely improves forecast accuracy, where it doesn't, and what RevOps teams still need to get right on the fundamentals before any tool can help. Attendees can expect to take away: - A clearer view of where forecasting breaks down most often, and why. - A realistic look at what AI can and can't fix in the forecasting process. - Practical steps for improving forecast accuracy without over-relying on a tool to solve a process problem.