Piotr works at Ocado Technology as a Catalyst helping the organisation to deliver great value whilst sustaining value-led, collaborative culture. He coaches and trains teams and individuals on Agile/Lean topics, communication skills; facilitates conflicts and group decision making. Previously Piotr worked in the IT industry leading teams working on banking, insurance and talent management solutions. Apart from day-to-day job at Ocado he co-creates a teal organisation of trainers/consultants dedicated to helping teams collaborate well through sharing NVC and teal concepts across businesses. He is part of initiatives around Restorative Circles and demystifying conflicts. He co-funded an NGO whose mission is to bring democratic education and empathetic communication to more people.
How to trust your data
A lot has been said about why statistical forecasting trumps estimating. The #noestimates topic attracts many people and at the same time is challenged by some. There were presentations that showed that probabilistic forecasting using the Monte Carlo method is not some obscure art accessible to only the enlightened few, but rather a straightforward approach that can be applied in various circumstances.
So we did it. We applied the Monte Carlo method to our product roadmap and got some answers for a 3-year timeframe. We needed to make assumptions and decide how we are going to validate them; we needed to adjust our data so it fit the models we wanted to use. We weren't happy with what the data told us, but we decided to trust it more than we wanted to trust our optimistic gut. We came up with a series of experiments that can bring the reality closer to the business expectations of our delivery. We are almost a year into that and a couple of reforecasts happened. We learnt a lot.
During this session I want to talk about the joint perspective of product roadmap, business expectations and statistical forecasting. I will share our journey, findings, and what is still ahead. You’ll leave the room with an insight about practical challenges and real experience of the method applied. You’ll learn how to adapt the method to your context and how to decide which trade-offs you actually need to make.Slides Video