568: Operationalizing AI in Planning: Go From Experimentation to ROI, with Anaplan

Scott Jennings of Anaplan talks about operationalizing AI in planning, eliminating latency tax, the shift to autonomous multi-agent systems, & your next steps.

IN THIS EPISODE WE DISCUSS: [02.52] Scott's role at Anaplan, what they do, and their ideal customer profile.

"If you're not collaborating, you're going to get stuck in siloes - and that's what we hear from companies time and time again. It's that ability to collaborate with your peers, and with all the different technology that's available, that determines success or failure."

[04.38] From use case selection and success criteria to cost, why – despite huge investment in AI experimentation – many organizations are still struggling to demonstrate tangible business value, and why 2026 is the year of change when it comes to businesses moving from AI experimentation to proving ROI.

"Companies are beginning to ask questions, about trade offs – did they pick the right use cases to experiment with AI? They're not sure. Did the experiment work, and can it be scaled?  They're not sure. And then the bill comes, and it turns out that tokens are expensive."

[08.10] What 'AI ROI' actually looks like in planning, and the metrics executives should be looking at to know whether an AI investment is genuinely paying off.

"Finance talks a lot about working capital, but the moment you move to supply chain you're talking units. Bringing those two concepts together, so you can understand the financial impacts across the board instantly, is what's been driving most of the AI projects I've seen."

[12.18] Why planners are often reluctant to rely on AI recommendations, and what organizations need to do to move from a 'black box' to a more explainable, transparent approach.

[15.56] Why 'AI for AI's sake' can actually create more problems, and why it's critical to ensure your data is ready for AI use.

"When you think about AI, you want to think about what's going to drive the big metrics that are important to your organization, and then work backwards. What you don't want to do is just start running AI projects… sometimes the cost is higher than running the exact same project with humans!"

[20.17] The importance of real-time planning, the cost of the 'latency tax' when decisions are delayed because data, teams and systems aren't connected, and how significant that impact can be for large organizations.

"You can lose 5 cents on every dollar due to decision delay. And that's millions of dollars for a large company."