Unlocking the Value of Asset Data: How Bespoke Modelling Transforms Investment Planning

By Pete Evans · 16 April 2026

Estimated reading time: 9 minutes

I sat down with ARK Asset Management Consultant Adam Borrie, after reading his recent LinkedIn post. I wanted to learn more about his work on asset data and investment planning, and providing bespoke models to our clients… you can read his post here (opens in new tab).

In your post, you said you enjoyed helping clients get more value from their asset data.  Why do you find working with housing asset data so enjoyable?

It’s the relationship between data and decision-making that interests me. For example, one of the first things I do in the morning is check the weather forecast. The information the weather app gives me will determine when and for how long I take the dogs out. It will also help me choose what clothes to wear as I don’t like being cold.

Similarly, when buying something, I typically look at reviews and what other people have said about it. The more convincing the reviews are, the more likely I am to buy it. This is especially true for music. Whilst there are artists and bands that I keep coming back to, I also look at songs that are trending or new. This can introduce me to artists that I’ve not heard before. Information and data influence our decisions, both good and bad.

When it comes to housing asset data, if clients can see more data in a usable format, then more “What if” scenarios can be considered. Problems can appear more manageable. As I said in my post, most organisations collect large volumes of stock condition data—but unlocking its value is far more difficult. It can be difficult to pinpoint known problems in the data. Despite having the information, visualising it in a way that enables a broader range of investment options to be considered can be a challenge. In my experience, I’ve seen planned budgets that are as much as 50% reactive, where clients are having to invest quickly to deal with component failures. This can result in investment plans drifting from what they originally set out to do.

You say in your post that the absence of data need not prevent investment from being considered.  How is this possible if the data isn’t there? 

Risk-based investment decisions are possible if you can see information held on neighbouring or similar property types. For example, portfolios typically contain clusters of properties in areas. 

(Adam opens his laptop and pulls up a model he has done for a previous client)

Here we can see component data for properties on the same street. This data can indicate when the same components are likely to be due for renewal or repair for those properties where the data is missing.. They can now be considered for programmes even if the data is incomplete. Properties with missing data can benefit from investment where they might have been previously overlooked. A lack of data is a contributing factor to underinvestment. Old data is also a contributing factor, so the same principle could be applied if the model included the last survey dates.

If scoping surveys are integrated into the delivery stage, missing condition data can be assessed further. Decisions on whether to renew or repair components can be made in real time. The missing data can then be updated after the works have been completed, with the next renewal dates being set at this point. This can prevent the need for further survey activity. However, there is a caveat. This does require a client to have effective contract management and fiscal control arrangements in place. But it is certainly possible if managed correctly.

You also talk about being able to combine component replacements or adjust the timing of replacements.  What is the benefit of doing this?

Let’s take the main components of a roof. Older properties will typically have a pitched roof covering, a chimney, soffits and fascias, rainwater goods (guttering and downpipes), and possibly a flat roof covering to the rear of the property. The expected lifecycle of the roof and the chimney is much longer than the rainwater goods, fascias, soffits and flat roof. Therefore, the renewal dates are likely to differ.

(Adam shows me a dashboard showing property addresses and the renewal dates of different components.)

As you can see here, the dates on this property are all over the place. Being able to see the renewal dates of these components next to each other enables clients to decide the timing of the investment and whether the components are renewed or repaired at the same time. The work can be packaged together. This can reduce costs. The same principle can be applied to other component combinations. In short, it enables clients to package work more efficiently. This can lead to a better use of existing resources.

Combining component replacements can generate investment plans with greater impact. I’ve done this before.

(Adam opens Google Street View to show some before and after images of the same street)

For this client, we considered renewals and repairs to roofs, windows, entrance doors, walls, fencing and gates in a single scope of work. The programme focused on clusters of properties. Whilst the extent of the work varied from property to property, the team aimed to ensure the finish was consistent, so it was difficult to tell which properties received less work than others. It completely transformed the look and feel of the area. This client won an award for this project.

You mention in your post that ARK can develop bespoke models for clients.  Can you explain what customers can expect from them?

It starts with understanding what problems a client has and then using their data to help them create a plan that solves these problems. It also involves listening and understanding what a client is trying to do. This dictates the approach we take and what the outputs are. I’ll give you two different examples of how flexible the models can be.

(Adam opens up a delivery plan he’d developed for a previous client.)

This client was in the process of restructuring their delivery team. They had three people to manage the delivery of the planned investment. A typical investment plan wasn’t going to work for them because it would have overloaded the team. So, I created a data model that helped me produce an investment plan that combined internal components together (kitchens, bathrooms, consumer units, etc.) based on what was due in the next 5 years. The volumes were based on what their existing contractor could deliver each year. A similar model was created to generate an investment plan for houses covering the main fabric and external components (roofs, windows, rainwater goods, etc.) and another covering the same components for blocks. The models combined components into programme years to facilitate the creation of three investment programmes. The three client-side contract managers then delivered their respective programmes with their contractors. It was easier for each of them to manage one set of CDM(Construction Design Management) arrangements, one budget, one contract etc.

For another client, the problem was high repair spend and a high number of referrals coming from the reactive team. So, for them, I designed a model that put properties into repair demand categories and then compared this to component renewal dates to help identify where components might be reaching the end of their life earlier than expected. I’ll show you.

(Adam opens up another model and shows me the analysis of day-to-day repairs he’d undertaken for the client.)

Let me pick a property in the high-demand category. This one is much higher than the average. If we scroll across to the component data, it gives us insight into what might be causing it. [He points at the screen]. Chances are the cause is the roof or rainwater goods because these renewal dates have passed. [On this model, these cells were shaded red]. Using this information, the investment plan prioritised those properties in the high demand category and also those components that were linked to the repair numbers, even if the renewal year was not due for a few years. As I say to clients, renewal years are a guide to assist planning, but they should be challenged if other data indicates they might be wrong. We can do the same using void data if they’re becoming void too often. The age of its key components might be contributing to shorter tenancies. But we won’t know until we bring these data points together. It’s a bit like the weather app, the age of components will indicate when it’s going to rain repairs.
What the models also facilitate is improved consideration of procurement arrangements or resource planning. Being able to see the volume of component replacements in the short term enables clients to assess whether contract arrangements need to change or whether the resources they have are sufficient. As in the first example, a plan was created to suit current resource levels. As the level of resources grows, new plans can be generated.

To use a well-known phrase, these models help clients see the wood for the trees. To give a strategy any chance of being successful, it must start with a definition of a problem or problems. Once this is understood, appropriate plans can then be put in place.

I’ve just finished a model for a client that had 679,000 rows of stock condition data covering dwellings, blocks and garages

Within a few weeks, they could see all their chosen data in one place. We developed it iteratively. They can now develop plans based on areas, repair demand, property type, EPC ratings, or combinations of components. They can also see what investment looks like over the next 30 years by component or combinations of components. They have said, though, that using the model has raised questions about their data– but these questions are the right ones to ask. They are seeing things they were blind to before, and this will lead to better plans and better outcomes for their tenants.
With the right tools, a client stands a better chance of succeeding. If I can leave a client in a better place than when I started, I’ve delivered value for the client and I’ve met ARK’s mission to deliver the high quality homes and services that residents deserve.. Win-Win.

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