Case Study
Asset Management Simulation Platform
90% faster simulations, from Excel MVP to cloud platform
Forming a team, securing investment, and shipping a simulation platform from scratch
Overview
A strategic asset investment platform that helps infrastructure asset managers make Net Zero-aligned, risk-optimised investment decisions through large-scale data simulation. I took it from a cumbersome Excel and Python MVP to a cloud-deployed, client-ready platform, forming and leading the team from day one.
Role
Product Manager
Sector
Public Sector Infrastructure / Asset Management
Goal
Give clients data-backed asset management forward planning studies
The Problem
Asset managers at major infrastructure organisations were running complex investment simulations across multiple Excel spreadsheets, often redoing the same processes for different projects. It was slow, prone to data entry errors and poor data quality, and couldn't scale to the complexity and varied requirements of modern public infrastructure portfolios. There was no real product, just some Python scripts and a spreadsheet MVP proving a concept, and I took the lead to turn it into something scalable, fast and client-ready.
My Role
Ownership & Scope
Product Manager. Responsible for forming the product team, defining the vision and strategy, running discovery with asset managers, building the backlog, leading delivery, and presenting to the product board to secure internal investment. Also defined the adoption strategy and led client demos and trial deployments.
The Approach
Started with deep discovery with internal SMEs, engaging directly with asset managers and infrastructure experts to understand forward planning, investment modelling, asset lifecycle strategy and data quality challenges. Used JTBD to frame user needs, workshops and domain modelling to map the problem space, and OKRs to align the new team around shared outcomes. Ran a competitive landscape review to find where the product could genuinely differentiate using the expertise we had in-house.
The Solution
Led the technical and product transformation from Excel MVP to cloud-deployed platform. Worked closely with engineers to architect and refactor a scalable, sector-agnostic simulation engine that could handle large, incomplete datasets without slowing simulations down. Built data error detection into the product to improve simulation success rates. Defined an adoption strategy with key stakeholders and ran client demos that generated early buy-in for trial deployments.
Results
The Outcome
90%
Faster simulations through a refactored, scalable engine
Fewer failed runs
Data error flagging that improved detection and simulation success rates
New team
Cross-functional international team formed and operating with agile practices
Investment
Significant internal investment secured through a product board presentation
Live trials
Product in active client trial deployment
Reflection
“This product was really interesting to work on. Fundamentally it's a heavy data product, so balancing the needs of non-technical users with the complexity of how it works was a challenge. To solve this, we designed clear user flows from the start of ideation so the engine never felt too cumbersome or technical for the people using it.”
Roly Hancock © 2026