3 great business cases for IoT in older buildings

Every day I speak to a lot of property professionals – FMs, building engineers, asset managers. There is a lot of interest in turning existing buildings into smart buildings and using the IoT to improve the performance of buildings but still people are stuck with the business case. Clients won’t invest in the tech unless they can see a clear ROI; property assets are so variable that guaranteeing ROI is tricky.

Frustrating for property professionals who can see big efficiency gains in their operation if they can get better data from their buildings, but who are stuck without the tools to persuade clients to invest. Frustrating for clients who are hearing a great deal about the promise of IoT but can’t relate its benefits to immediate pain points.

After three years of pilots, turning average buildings into smart buildings, we have a large estate of sensors in operation, so we’d like to offer three clear business cases to discuss with clients. Tread carefully: different clients with different types of tenure will respond better to some than others.

1. Energy savings.

Want to save 10% of your gas bill simply by changing a setting in the BMS? We’ve written about energy savings before at length but the simple message is that nearly every older building will have opportunities for saving energy at *no* cost beyond identifying where controls don’t match the operations of the building. A couple of examples:

– the call centre in North West England which saved 18k on energy by changing HVAC set points and reducing conflict between zones

– the airfield in Eastern England who identified nearly 100k of wasted gas spend from poorly controlled heating in their hangars

The business case. Most older buildings waste energy simply because the control of their heating and cooling no longer matches the operation of the business. Timings may be off, unused areas may be heated, heating and cooling may be in conflict with each other. These issues are extremely easy and cheap to fix, and lead to rapid payback, but first they must be spotted. A properly smart building uses simple sensors to confirm that the BMS is doing exactly what it should be.

To calculate the possible ROI here are a few basic rules of thumb:

Costs of heating (or cooling) 1 m2 each operating hour £3.60 (from CIBSE benchmarks). Put another way, for a typical office operating a 9 hour day the annualised cost of 1 hours’ HVAC psm is £32.40. Therefore in a typical 1000 sq m office reducing the heating run time by an hour would save £3,240 on your annual heating bill.

Reducing set points by 1° can produce savings varying from 3 – 7%. So for the typical 1000 sq m office above, with an annual energy bill for HVAC of £29,160, that would be an additional £874 – £2041. These figures are hugely simplified – in reality the results will be complicated by factors including external temperature, and varying amounts of savings depending on how far your building is from the external temperature.

The faster and more frequently you can find these energy savings opportunities the more money you can save – at a minimum an annual audit (not from BMS data) should give you substantial payback. Remember these are *no cost* fixes.

This is a business case that appeals most to owner occupiers of space who have some control over their building services and who are invested in reducing their energy costs.

2. Space utilisation

Fun fact: fully loaded with rent, rates, utilities etc, desks in the UK cost employers between £3000 and £15,000 each year. Yet a lot of them are empty for a lot of the time, with utilisation rates often below 60%; so if ever there was a business case for better building data it’s in space utilisation.

So if your client has a large and fluctuating workforce and a big estate then they are probably already thinking about better space utilisation and if they’re not, they should be. Although the cost reduction argument is strong its not the only one, as it is possible both to reduce space and to provide more of the most heavily used facilities so that workers are better equipped and feel supported.  The range of new options for flexible working, from providers like The Office Group and WeWork, and a huge range of digital team working tools, mean that short term staff fluctuations can be easily accommodated and folded into the organisation.

For a quick business case on utilisation audits to discuss with your colleagues:

Estimate fully loaded desk costs (calculator by region here), multiply by number of desks and then ask what level of underutilisation you would need to find to justify the audit.  Even with audit costs of £100 – £150/desk, you’ll find it’s surprisingly small.

3. Productivity improvements

This is where the big wins are. Staff costs are by far the largest cost component of most businesses, and even small improvements in staff productivity can be game changing. It’s not just call centre operatives able to handle 10% more calls each day or traders making 2% more trades but also improvements in the quality of work from creative teams, or better focus from staff tasked with safety critical jobs.

Frustratingly, its also the hardest to prove. Here’s a summary of what we do know:

– Many studies have shown that indoor environmental quality has a measurable impact on people’s productivity

– Poor temperature control can reduce productivity by up to 10% at +/- 5% around a ‘safe’ band

– Better lighting can raise productivity by 23%

– Better ventilation increases productivity by 11% (link to UCL work)

– Productivity in different tasks can be affected by different aspects of the environment (for example noise levels)

The ROI from a better working environment goes beyond enabling staff to concentrate better. A better building reduces absenteeism and staff churn, so that recruitment costs drop.

Not all of these business cases will work for every client, but nearly every client is interested in saving costs and building a stronger team. The next time your client asks you how you can do something different in tired old buildings these are the conversations to have.

Beyond the data: controlling CO2 with Purrmetrix

This is cool: the team at LCMB have been using Purrmetrix to go beyond data gathering and get into some home brewed building control.

LCMB have been monitoring the environment in a university facility for several months using Purrmetrix CO2 and temperature sensors to look at the relationship between comfort and productivity. One space in particular caught the attention of LCMB and the university estates team: an office area which had obvious ventilation problems. With a lot of people using the space the building systems were struggling to keep up with the ventilation needed, especially in winter, when opening windows was unattractive.

It was commonplace to see CO2 levels rising above 1500 ppm, a level where concentration and decision making becomes impaired.

KCL CO2

But rather than going for a costly building services overhaul, the LCMB team decided to go one better and implement their own fix, using ducted fans and a Raspberry Pi to keep the CO2 in the office within controlled limits.

Two fans were set up to provide good coverage across the whole space; each had their own Raspberry Pi low cost computer to read the data from API on the Purrmetrix web service and to drive the fans using a digital to analogue converter. The fans were ducted from outside so the set up also needed a heater in front of the air to temper it to the right temperature. This might not be the prettiest set up, but it’s a prototype and a big improvement on a CO2 headache.

KCL fan

The project took a few days of tinkering time to connect the hardware, in particular setting up the Pi and configuring the internet access for it from the university network. But once the hardware was connected and the right scripts were implemented it produced an immediate result.

KCL CO2 controlled

There had been some concerns about noise levels and air movement – in practice the team found that to keep levels of CO2 around 700 ppm (+/- 100 ppm) the fan was operating at 50 – 60% for much of the day. This delivered a good trade off between air quality and noise level. Allowing a higher CO2 level (around 1000 – 1200 ppm, which is considered acceptable) fans could be quieter, cycling on/off most of the day. In warmer weather as windows are opened, the fans are working much less frequently.

‘Once we had the data from Purrmetrix it was irresistible to have a go at creating a solution.’ explains Tom Cudmore, senior consultant at LCMB, ‘We considered using the alerts system within Purrmetrix to create a HTTP call that would activate the fan, but in the end we decided to keep the alerts for exceptions and take the data direct from the API every two minutes. It took a few weeks to source the right fan product and write the scripts, but we think the results speak for themselves – we’d be happy to work in this environment now.’

If you have a problem office and would like to re-create this low cost solution, to trial the impact in your workplaces, here are the components you will need:

– Fan (we used Helios RR-EC in-line duct fan) sized according to the room volume and desired conditions
– Ducting and window blanking plate
– Heater to put in front of the fan and temper the outside air
– Power supply for fan and heater
– Wiring from analogue convertor to fan
– Digital to analogue convertor – we used a LucidControl device
– Raspberry Pi with internet access and configured for remote access
– Purrmetrix kit – in this case with CO2 sensor

And if you want a copy of the script that LCMB developed, just get in touch.

When good buildings go bad…HVAC recommissioning

Proptech. AI. IOT. Space as a service. Smart Buildings.

There’s increasing noise in the property industry about the importance of technology. You’re probably sick of the phrase ‘Data is the new oil’, especially if you’re tasked with trying to persuade a sceptical boss to invest in it.

Not surprisingly we have a lot of conversations about the ROI from environmental data, which can get complicated as there are many ways in which better insights into your environment create value. So we thought we might create a short series where we could share examples of what our customers are doing with this data and how they get ROI.

First up – how to reduce hvac energy waste

Fact: the energy consumption of commercial buildings tends to drift up over time. If you look at the lifecycle of a typical modern building over time the energy used to run this building will tend to trend upwards unless regular interventions – shown by the green line – are made to review and fix the problems that arise.The effect of control drift

Why these occur is complex, but one of the most common and low cost causes is control drift, and that’s what we’re interested in. Studies in the US of over 600 commercial buildings show more than 50% have controls problems and that fixing these produces a simple payback within a year. These are very simple issues like scheduling, run time, set point adjustments, eliminating zone conflicts.

Further more, fixing them – recommissioning the building – is generally a very low cost win, requiring no new investment. So this looks like an attractive target for improving energy efficiency in any building, but to do this first you have to find the problems.

Causes of control drift

So it’s a common problem, it is low cost to fix – why don’t people pay more attention to it?

I think part of the problem is that, unlike lighting, HVAC control issues are invisible – the BMS is unlikely to flag it up as an alert, and identifying it requires expertise and time. If your buildings supports multiple schedules and set points – and we have come across academic set ups where there are hundreds of schedules for heating and cooling – then manual checking isn’t practical.

Furthermore many facilities managers are a bit sceptical of data reported from a BMS because they know sensors can drift without recalibration and they are often located away from the occupants. If managers don’t trust the data the BMS is producing, then they are less likely to invest the time in an audit.

The value of environmental data in these situations is that, unlike metering data, it is easy to locate exactly which part of the system is running out of control and implement the right adjustments.

The case for recommissioning

A quick back of the envelope highlights why this is worth doing – heating and cooling commercial space is typically 25 – 35% of the overall energy budget for a building. That means, at its simplest, that if the building systems are running for 10 hours where they could be running for 9, that extra hour is 2-3% of the energy budget for the whole building. Running at weekends is ruinous and not uncommon. In fact, based on experience, I’d go so far as to say if you have a building of more than 3 years old, its a stone cold certainty that parts of the HVAC will not be well matched to the operations in the building.

Fixing control drift – real world cases

Over the past two years we’ve seen so many examples of this, and not just in offices:

1) the 10 year old office building in a campus setting with conflicting HVAC zones and heating that was regularly 2 or 3 degrees above set point. Changes to reduce zone conflict and lower temperatures produced a 20% reduction on an annual 80k energy bill

2) a school with a large number of Victorian school houses and a wet radiator system that had extensive challenges with timing heating, incorrect sensor readings and furniture in front of radiators. Fixing these problems produced a 10% reduction in their gas consumption for these buildings.

3) an aircraft hangar with substantial overheating issues and heating systems running out of working hours. Purrmetrix data demonstrates that upgrading controls will create savings of over £100,000 across the whole estate.

Think you might have a silent controls problem? Get in touch  and let’s talk about how we can help.

Does your building need a data strategy?

How much data is your building generating? Are you getting any value from it?

Even if you are not operating state of the art smart buildings with nearly 30,000 sensors, the chances are that you will soon be swimming in data. Industry estimates suggest that we’re well past 500 million end points from commercial buildings, and heading towards 3.5 billion in the next three years (thanks, Gartner). That’s end points…each one delivering a data stream at rates potentially of many times a minute.

data endpoints in buildings

Its a crazy amount of data, and it won’t be tractable without some deep thinking on applications and analytics. If properly harnessed it offers huge scope to improve the efficiency of buildings and their capacity to deliver comfort and improve productivity for the people working in them. For that to happen, though, building operators need to get a bit cleverer about their data and clearer about what their data strategy needs to be.

Where to start with data in your building

A good data strategy will clarify the value of the data being collected and ensure it is fit for purpose – sadly not the case in so many buildings right now. A simple example – consider the difference between a supply air temperature sensor 3M up in an office ceiling and a desk level comfort sensor. This difference is not just location, but also the rate of update and data availability for analysing previous periods. Lower data rates may be good for control applications, but there are certain applications that are only possible with higher data rates.

Screen Shot 2017-11-24 at 19.51.48

So data strategy should help flush out what you want from your data, which drives some important decisions about what, where and how frequently to measure.

The best – and simplest – first step is to assess what your goals are for data. What are the really valuable applications? For most commercial buildings the two major categories of time related data – metering data and building management systems – have obvious lead applications – settling energy bills and controlling building services, but they typically need some enhancement to be able to support detailed building analytics.

Data goals for buildings

I’ve been around in the smart building market for some years, and as it overlaps with green building objectives a number of clear applications are beginning to emerge that support the efficiency of buildings and the comfort of occupiers: data in green buildings

  • Optimise energy performance – Match energy usage to the buildings activity
  • Additional (retro) commissioning – Providing a regular review of the buildings systems to check they are working as they should
  • Measurement and verification – Demonstrating that improvements are performing as anticipated
  • CO2 reporting – For external and internal communications
  • Permanent environmental monitoring – Ensuring energy efficiency does not compromise building’s delivery of comfort. Identifying wasted space and opportunities for supporting improved productivity
  • System innovation in design – Identifying new opportunities for energy savings and improved productivity by making major changes to environment.

From green to brown – how value of data can trickle down

The evidence is that these applications add real value to buildings – green buildings are typically 25 – 35% lower to operate and occupiers report 4% more productivity from staff. Excitingly, it seems there is potential to apply some of these to buildings that haven’t originally been conceived as green or smart, to improve them.

As a quick, scaleable win for occupiers and operators of commercial, data has huge potential, if it is structured correctly. Purrmetrix can help fill in gaps and support your analytics – if you want to know more, do get in touch.

New: movement sensors and sensitivity – the ‘Mission Impossible’ test

How easy is it to fool a movement sensor?

I can’t be the only person who has been working late at night in an office when suddenly I am left sitting in darkness, because the PIRs (passive infrared) movement sensor that controls the lighting has decided I’m too still.

In fact I know I’m not the only person, because an FAQ from customers who want to use our new movement sensors for measuring office space usage is how sensitive they are. And so we decided to do a little experiment in our office with two sensors, some software engineers and a very bouncy visitor.

We wanted to look at a range of activity levels and locations for sensors, including

  • distinguishing between one very active person (moving furniture around), several people talking and interacting and the classic ‘stationary deep thought’ pose beloved of software engineers
  • looking at the effect of location, in particular the difference between ceiling and wall mounted sensors. The ceiling mounted sensor was 2.7m off the ground in the middle of the workspace, and the wall mounted sensor was 1.5m off the ground on a column in a direction that covered half the office space.

Over a week, we found the ceiling sensor accurately reported all presence in the office. It is difficult to distinguish short, vigorous bursts of activity from one person – they look very like a few people interacting – but they did typically tend to be shorter in duration.

Meanwhile the wall mounted sensor did exactly what was expected and recorded all activity in the half of the office it could see. In the analysis below it is the light green trace:

Screen Shot 2017-11-14 at 16.13.53

Most usefully, our tests reveal it’s very unusual for anyone working at a desk to go for many minutes without some small adjustments of their body or working environment. Perhaps reaching for a pen, scratching your nose, or moving a mouse. It’s perfectly possible for someone who is focussed on their work (take a bow my software colleagues) to record no movement for a minute or more but if data is aggregated in 5 minute or larger buckets then we had a close fit between occupancy and movement.

To avoid over sensitivity, our movement sensors work with a target concept that is about the size of a human limb, so, if you are in Tom Cruise mode the best way not to trigger the sensor may be to practise moving one finger at a time at less than 1 m/minute. You might not get any work done, but that’s OK…no one will know you’re at work.

If you want a slightly more technical explanation of the sensitivity and range of our movement sensors you can find the data sheet here.

 

 

‘But why kittens?’

I would say it’s a long story…but it isn’t.

Bear in mind when we first started Purrmetrix the thing we were most interested in was temperature. It’s not surprising that organisations spend a lot on maintaining the right temperature – not only is temperature critically important for many processes, it protects expensive assets and can affect productivity. On the other hand, it is variable enough to carry a great deal of information: you can learn a lot about a building from an effective heat map. So it was the perfect place to start in producing useful building analytics.

And yet, we didn’t want to come across as too clinical. It didn’t seem very, well, comfortable. Which was kind of the point.

What is comfortable and also expert at identifying hot spots, is a cat.

And thus the idea of Purrmetrix, and a whole litter of kitten sensors, arrived.

 

Changes to the Purrmetrix webservice

It’s been quite a year.

Every bit of our service has expanded: customer numbers, project numbers, number of buildings, analyses and hardware served. Thank you to everyone who has used the service and given us very useful feedback.

Based on that feedback, it’s time to make some changes to the webservice. Our aim here is to make it more intuitive and to add some extra features.

The changes will go live over the next couple of weeks, so let’s take a little tour:

1.Webservice layout

The most obvious difference is that we have moved the projects menu and the views menu up into the top bar. This frees up the full screen width for visualisations and analytics. To switch between projects or to add a project you now need to click on the drop down menu in the top bar.

Can’t see what you are looking for? The drop down menus support scrolling.

Webservice temperature analytics

You’ll still be able to name the project and set it up in the project dialogue box (which you enter by clicking on the title of the project).

Similarly, if you want to set up a new analytics view, you click on the drop down menu and select the view you need. It will open in the main screen and you can add your kittens from your libary (the section with ‘Your Things’ at the top) or from other views.

Temperature analytics webservice

2. Checking (and removing) kittens

As before, if you have a kitten in your hand and want to know which one it is, you can squeeze its face and the kitten in the webservice will turn red:

Temperature analytics webservice

BONUS TIP – for power users if you activate the magnet at the top right hand corner of each view, every time you squeeze a kitten it will add itself to the view.

Removing a kitten from a view is also simplified – when you pick up a kitten from within any view, a trash can will appear in the bottom right of your screen. You can drop kittens in them and they will disappear from the view you had selected them from. Note they will stay in all other views in the project, UNLESS you take them out of the project library view (at the top) and trash them. This will cause that kitten to disappear from all views in the project.

3. Scrolling through graphs

As well as making graphs much quicker to deliver information, we have activated a click and drag zoom to help zoom in and out on graph data. Here’s how it works: you place your mouse in the middle of a graph, click and drag either backwards (left) to zoom out, or forwards – right – to zoom in. The longer you drag for, the bigger your zoom.

Temperature analytics webservice

4. Mean/max/min for graph views

For graph views, we have added ‘summary’: the ability to track the mean, max and minimum of any group of kittens over time. The feature can be turned on in the view dialogue box, which you get to by clicking on the view title.

Temperature analytics web service

Selecting ‘mean’ here produces this:

Temperature analytics web service

Helpful if you need to find out what the average performance across a zone is or track the impact of an improvement that affects many areas.

5. Project addressing

Projects and teams can both now hold address information. In future, this will allow your projects to be mapped in Google maps and potentially integrated with other localised information.

6. What’s next?

We will push these changes live in the next two weeks and look forward to your thoughts. And if you’d like to report problems or suggest improvements to performance, please do get in touch. We love to hear from you.

 

 

 

Why you aren’t using temperature data enough.

So here’s the thing: temperature data is the most accurate, cost effective and easily available metric of comfort for your staff and assets. It also has a crucial relationship with productivity, energy consumption and efficiency. So why aren’t you monitoring it more?

You might be relying on your BMS to tell you if your colleagues are sweating or shivering. Or monitoring comfort complaints as a metric of how things are going. As a second line of defence most facilities professionals have a thermometer in their tool box, ready to settle disputes at the point of conflict. But for most people, that’s it.

Allow us to convince you that this is a wasted opportunity. Allow us to convince you that there is a lot more to temperature than dealing with ‘too hot/too cold’ complaints.

Why you aren’t monitoring temperature enough

We don’t blame you. Temperature data as it’s presented today generally has some significant drawbacks:
1) it’s monitored in the wrong place,
2) it’s monitored using equipment that is inaccurate, expensive and requires maintenance,
3) it’s not interpreted helpfully (or at all),
4) there isn’t enough of it to answer the really interesting questions

These drawbacks mean you can never be completely sure if complaints are due to a system problem or colleagues’ personal comfort level. And that HVAC systems can drift a long way from their optimum set up, wasting energy.

Why these problems are worth fixing

Monitored properly temperature has some unique attributes

1) it’s the most important measure of your actual comfort, directly related to productivity
2) heating and cooling is one of the most expensive elements for most organisations. 20% off your HVAC requirement is likely to give you a much higher return than 20% off your lighting budget
3) it’s affordable. Measuring temperature is a well understood problem and the technology is cheap. Why spend £800 or £1000 on purchasing and integrating a new submeter for a single floor when for half the price you can not only get data on a single point but on every desk cluster or fan coil unit, allowing you to pinpoint exactly where and when the problems are occuring.

 

Why should monitoring heat help you save energy?

Heating and cooling is one of the largest energy uses in most commercial buildings

It’s all about efficiency – maximising your heating and cooling for minimum input. In an ideal world you would measure both input (meter data) and output (temperature achieved for that meter data) and we advocate this for a true understanding of your estate’s heating efficiency. But if you can only do one we think you should do output and here’s why:

– in every case you will have meter data anyway, from which you can make some gross deductions about consumption trends.
– meter data can tell you nothing about the experience of your colleagues. The most effective way to save energy in heating would be to turn all heating systems off, but that is not the goal of the game. The goal is to deliver just enough heat/cooling to make a comfortable work environment at the time it is needed
– meter data can tell you nothing about the location of wasted energy. It lacks context – where the heat energy is being used, whether that space is occupied, if there is an extra load on the building’s fabric. Adding location and time to heat data allows you to begin to see the context and gives you important clues about what to do next

Smart meters are great – we should know, the team at Purrmetrix has been responsible for many successful smart metering products. But here’s what they can’t tell you: they can’t tell you where your inefficiencies are occurring and what else might be happening in the building that is relevant. PurrMetrix can.

If we’ve done enough in this post to convince you to take another look at temperature data, then sign up below for our occasional series on using temperature data for fame, fortune and better facilities management.

Can temperature data save your building?

A short course on using data to improve the performance of your building. And the people in it.

 

One of our radiators is missing…

How often do facilities managers lose bits of their building?

More often than you might think.

The curious case of the missing radiator

Took a call from a client earlier in the year, who had a customer running a large educational estate. Many blocks of buildings, dating back to the Victorian era, most serviced from a central boiler room and a number of heating circuits. The problem, simply put, is that no one really knows which radiators belong to which circuit.

Over the years new legs have been added, some bits bypassed, whole blocks rationalised and generally, the records of what has been done aren’t complete. Now the customer wants to improve hot water circulation with new pumps on the circuits and not being sure how much capacity each circuit needs creates a problem.

Letting the data speak for itself

This is where live data comes into its own – there’s something very pleasing about putting sensors on each of these radiators and watching the radiators on plan light up as each circuit is tested. It’s certainly lower hassle than trying to do the same with data loggers and offers the added bonus of being able to identify the delay between boiler supplying hot water and it being available in the radiators.

But look closer – this is problem not confined to rambling Victorian establishments and ‘losing’ bits of a heating system. In fact it’s common to any control system that is trying to deal with shifting agendas over the years. You see it often in a BMS, where layers of different controls are added to cater for long gone meeting rooms or zones that don’t reflect the current layout. Without regular audits and monitoring, performance drift in buildings can chisel away at any gains made through investments in new energy efficient capital equipment.

Fighting back against performance drift

The first step in dealing with drift is making a regular audit part of your maintenance regime. There’s plenty of evidence that ‘retro-commissioning’ heating/cooling systems can provide an energy reduction payback in less than a year, even before the improvements in performance when combined with more efficient capital equipment.

If a full blown retro-commissioning audit is outside your resources, at least making room for regular monitoring of the basics such as run time, set point, occupier overrides, start-stop times can keep your building on track.

Before you get to the stage of losing your radiators.

If you would like to know more about how Purrmetrix analysis can help you avoid performance drift and keep your HVAC on track, contact us now.

Fixing Social Housing with Technology – how hard can it be?

10 million people. That’s how many of us live in social housing in the UK: nearly 20% of our housing stock is owned by social landlords.  With nearly 4 million homes to operate, they face a formidable maintenance task and, in the main, they’re trying to do it with out of date tools – housing management systems straight out of the 1990s, multiple incompatible processes and a mass of silo’d data.

We know how to use technology – but does our landlord?

So in a world where us civilians are coming to terms with Smart Homes, even if we don’t have a clear business case, why aren’t social landlords engaging with technology? It has the potential to massively increase the efficiency of their business or even completely restructure the way housing is delivered. Imagine a housing provider who provides a platform for tenants to self manage their own properties – or a housing provider who rolls provision of all utilities and social care into the rent.

More practically, using the right analytics, imagine a housing provider who can identify and diagnose problems with a building’s fabric or systems remotely and ensure the right team, with the right tools, are deployed to provide the right solutions. Or using the same data to single out the homes that are eligible for funding for improvements.

This is a future that HACT – the Housing Association Charitable Trust – wants to create. Faced with substantial challenges over the next five years – cuts in benefits budget, the escalating price of housing – HACT knows the social housing sector needs to embrace innovation to survive so they have been digging into the barriers and challenges that are slowing progress. Their new manifesto (Is Housing Really Ready to Go Digital), identifies three barriers to change and what can be done about them:

Little visible leadership and accountability for technology at board level. Consequently tech is generally treated as a cost item, rather than an opportunity for fundamental change. Worse, where technology projects are commissioned, there is little embedded expertise in what can be delivered or how to measure accountability.

As a result, an over-reliance on consultant-led change. Without clear leadership on the potential of technology, consulting projects tend to focus on rationalising existing systems.

Low understanding of the potential value of data. Although housing has a huge amount of data it is too poorly structured and tools for effective analysis are generally lacking.

HACT’s manifesto has practical suggestions for how to deal with these problems – starting with a programme to match UK digital leaders with housing provider boards, and supporting their involvement in the business transformations that can result.

For those of us living and breathing tech every day, it’s easy to underestimate the challenges involved in promoting tech initiatives in sectors like housing. Bridging the ‘Digital Governance Gap’ in housing is not only challenging, it could be transformative for millions of people. If you want to know more about how to get involved, check out HACT’s Digital page.