by Laurence-Oakes Ash. 8th December 2025.
Like many people, I had no idea what I wanted to do following university.
I didn’t really want a job. I definitely didn’t want to take orders from anyone, and I couldn’t see how I’d enjoy working for a big corporate. I’d avoided the corporate milk rounds like the plague — I hated the whole idea of conforming to a corporate ideal of suit-wearing and acronyms.
To hold off going into employment for a few years longer, I thought I’d become an academic. I liked the university life – the maths and physics problems felt important, and I liked having plenty of free time for clubs, in particular amateur dramatics. I didn’t want to leave that environment.
So, to further my university lifestyle I secured a place at Cambridge to do Part III Maths. Within two weeks however, I’d dropped out.
I was self-funding everything and whilst I’d worked all summer and thought I’d planned a decent budget, the reality of self-imposed austerity quickly hit home. Within those first two weeks I’d already said “no” to every suggestion to do something social, retreating to my room to spend evenings with a book on Quantum Field Theory. It was grim.
Then I had the worst day ever. I’d bought a bike (everyone in Cambridge buys a bike), but on a tight budget. Cycling to a lecture, the bike gave up beneath me and collapsed into a heap of tyre and frame. I turned up late to that lecture, carrying a bag of debris. But from here the day got worse. I vividly remember standing in the aisle in Sainsburys and working out how much I’d spent on my weekly shop – things weren’t adding up. To make my shopping basket match my austere budget, I was going to need to make a difficult choice – would I have milk or peppers this week? Having worked all summer, I was not used to having to make difficult choices – I wanted milk and peppers. I couldn’t have peppers on my cereal after all, and I couldn’t put milk on pizza. The whole thing was a nightmare. The next day, I went to see the administrators and quit.
It had taken an existential crisis in the aisle at Sainsbury’s, but I’d finally come round to the idea that actually I was ready for a job. And so I immediately got started trying to find something.
That’s how I ended up on the graduate scheme at Lehman Brothers. I’d never intended to work in the City. I recall one interview where I was asked what I thought the stock market would do and I responded, “if I knew that, I wouldn’t be applying for a job here.”
The more interviews I had, the more I realised how the game needed to be played, and also which firms were the most respected. At that time[1], the more I heard about Lehman Brother the more I thought it sounded great — it was prestigious, hard to get into, and full of the smartest people in town.
Having a place like that on my CV, I thought, would make me feel better for having dropped out of Cambridge.
The interview process was intensive – tests, tests, assessment days and more tests but eventually I got the news that I’d got in. It all started with a golden handshake (upfront cash – I assume so that people like me would not worry about buying peppers and milk on our next shop) and a fabulous 2-week induction process where all the new graduates were treated like royalty.
But then the work hit.
Suddenly I was getting up at 5am every morning and working non-stop. During that period, falling asleep at 8pm on a Friday night while out for dinner with friends was not an uncommon occurrence. The first two years were gruelling. One Friday I was up all night panicking that I’d lost £20 million, so I went in on Saturday just to check. It was fine — no losses — but that’s the sort of baptism of fire the trading floor gave you.
Why am I telling you all this?
Well, because I want you to understand the environment I landed in. I was a maths graduate, fresh out of university without much of a plan, suddenly working on the trading floor at Lehman Brothers. It was in this environment that I got my first taste of using data in the real world. Everything I did depended on data – data was the lifeblood of the trading floor. Since everything happened in real time — every piece of information needed to be available instantaneously. We were provided this superpower through a system called Bloomberg. With Bloomberg you could call up any information on any stock, anywhere in the world and visualise it, analyse it and model it instantly.
When you see photos of trading floors with traders surrounded by screens, three and a half of those screens are filled with market data tools like Bloomberg. Data was everywhere. It was fully recognised that if you were doing anything that involved operational decisions, you had to have data – you couldn’t do your job without it. And being good at being a trader, meant being really good with data feeds. As a consequence, my early career environment was one where whatever data I wanted, I was provided.
As time went on, I got better and better at using all the data available to me and really started to enjoy working in the City. I loved the fast-paced nature of it and responding to things happening as soon as they had happened.
By 2007, I was trading financials — banks and insurers. Now, if you know your financial history, then this was a very interesting time to be trading banks (one year before the global financial crash).
In truth, I’d never really understood the housing market boom. It all felt too easy. You’d hear stories about someone from school who had a portfolio of 20 properties at the age of 22. But the markets had seemed to ignore the insanity of it all for a long time. I had no idea what it would take to get investors or lenders to start to question whether all of their lending had been sound. Until the cracks slowly started to show.
It was HSBC’s earnings in late 2006 that were the first hint that something wasn’t right. At that point HSBC’s US earnings were treated as an isolated case. Then in February 2007, further signs were starting to emerge with a couple of US homebuilders issuing profit warnings. One day in February we were running a skeleton staff and I recall a panicked afternoon of sell orders – everyone suddenly wanted to sell everything. I’d never seen that before. Up until then, markets had only ever gone up.
That day made me start to question everything — maybe stocks could go down. Maybe the unease I’d felt about the housing market was something important. I became convinced that the issues that were slowly becoming to the fore in the housing sector could feed through to more of the banks and eventually to the wider market. Despite it becoming increasingly obvious to a small handful of us, this point of view felt like fighting an uphill battle. Stocks continued to rally until the end of the year despite an increased sense that, under the surface, things were deteriorating.
But as we all now know, by 2008, it all fell apart. Everything — including Lehman Brothers, a company I’d genuinely come to love.
When Lehman collapsed, I was working in New York. I’m sure somewhere there is old footage of me carrying my box of papers and stationery out onto 7th Avenue. After the fallout, I eventually came back to the UK and got a job at Nomura. But those intense two years had started to change me and my overall perspectives of the financial markets. A year of warning people had worn me down, and there was no sense of pleasure in being right when everything collapsed around me. It also bothered me that no one went to jail, that the cracks were plastered over, but nothing was really fixed.
The European debt crisis (starting in 2009) confirmed that, and by the peak (2011), I’d had enough. Gary Steveson’s book, the Trading Game, provides a better description of how the City can lock you in and how there are very few ways out. I was fortunate to find a route out. As the market turned down, there was chatter that there might be redundancies. I made clear that if there were, I would like to be on the list and that’s how I escaped.
Released into the real world with the, now tarnished, Lehman Brothers name on my CV, and a handful of barely transferable skills. What to do next? I did the thing most people would do – I moved to Devon without a plan.
At that point I thought I would start a maths app. I liked maths, and I liked the idea of building something. The vision was to teach a five-year-old mental arithmetic, take them on Dragons’ Den, have them answer impossible questions. The Dragons would be so amazed to see them do the maths in their head that they’d all beg to invest. But my plan was to then say “no” and walk out of the Den, knowing full well that any parents watching that show would be immediately downloading the app. My plan seemed foolproof! I just had to teach a 5-year old mental arithmetic. I quickly realised however: I didn’t know many 5-year olds, I wasn’t a very good teacher (years in the City trading in real-time had not fostered patience) and I actually wasn’t that good at mental arithmetic myself.
Still, through the process of thinking about developing a maths app, I met Glenn Woodcock. Glenn was an investor in a much more well-developed maths app called Sparx and was based in Devon.
Glenn was also deeply interested in something called Net Zero. He didn’t want to use my maths app idea, but we did start to spend a lot of time talking about Net Zero.
“Do you know anything about Net Zero buildings?” he asked.
“No,” I replied.
“Don’t worry,” he said. “You’ll be fine. Come and look at a project I’m working on.”
Little did I know that that conversation was the beginning of the next ten years of my life.
We began by working out how to make one building Net Zero. That went surprisingly well – we secured some great meetings and deals to actually develop some more sustainable buildings with leading house builders. It was a natural progression for Glenn to ask, “How do we do this for a whole city? Can we take a city to Net Zero?”
That question changed everything. That’s how City Science was born.
Planning Net Zero for a city is radically different to planning it for a building. Cities can’t be approximated to boxes like buildings. They’re vast, complex things with multiple sub-systems. They are geographic objects – you need to see them on a map to start to understand anything about them. To understand a city, you need to understand its transport systems, its energy networks, its buildings (old and new), its economy, industries, land, and people. And you need to know what decarbonisation options are most likely – what is nearby? Is there land for renewables? Are there sources of heat? You very quickly have a lot of geospatial questions and suddenly need a lot of data.
To help delve into questions like how to decarbonise transport, my first port of call was to try a get meetings with transport authorities. Many were very helpful and actually entertained me when I asked detailed questions about their modelling processes. One very helpful council actually sat me down and talked me through the SATURN simulation software. I was shocked.
SATURN had initially been developed in the 1980s but by the look of the interface, it hadn’t been updated since. It was the worst interface for a system I had seen since some of the programmes I used to code as a kid on the Commodore VIC 20. Transport demanded to be seen on a map, but SATURN output a jumble of black and white lines and people seemed to accept this. I couldn’t understand it.
I started digging further into different types of data necessary for the decarbonisation question and continued to find issue after issue. This was not the marble palace of data I was used to from the City but a complex web of legacy systems, high costs, poor data, limited standardisation and no interoperability.
What was I missing? Surely the Chief Executives of the local authorities had access to data at their fingertips like I had had in the City. Where was the data? Who was looking at it? And why didn’t the Chief Executives have access? I searched for over a year and eventually concluded that it just didn’t exist.
That’s when it clicked: I’d been spoilt for data in the City. But the work government does — Net Zero, housing, transport, planning — is far more important than trading stocks and shares. Cities and regions deserved the same access to data. But it seemed like you needed a PhD in GIS to process data onto a map. It felt like it you needed to spend weeks joining datasets just to see open national data. Data is a basic necessity of any role within local government, just as it was for me in the City, but it was all just too hard. We had to start helping people get the data they needed on maps and do it in a way where they could do it without bottlenecks or headaches.
So that’s when we decided to build Cadence. Our goal was simple: make geospatial data easy. Help people get the data they need on maps, instantly. And that’s what we’ve been doing ever since.
We’ve worked hard to iterate Cadence, using it alongside all of our consultancy work on Net Zero, making sure it is packed with the data, tools and insights needed to really understand places. We’ve made sure data is standardised and can be connected between systems. We’ve made sure it’s easy, insightful and fast. But most importantly we’ve made sure it’s simple – accessible to everyone – especially time-pressed executives tasked with making critical decisions about places.
I now use it every day, just as I would use data systems in the City. And every time I do, I’m reminded why we built it — because better data means better decisions, and better decisions shape better places.
[1] Before Lehman Brothers was blamed for crashing the global economy, it was considered to be a very respectable company.
Figure 1: One of our interesting map example as part of this year’s #30daymapchallenge using Cadence software