The Power of Data Analytics
This blog is all about data and, in particular, data insights within smart buildings, whether that is an Office building, Warehouse, Retail store etc. It's all very well capturing data within a building, but that is useless if there is no way of understanding it – it's all about creating clarity.
I am interviewing Luke, who is the Head of Advisory Services at Triangle. They are bringing a fresh approach to the world of data analytics, turning data from an obstacle into an opportunity.
You can listen to the podcast episode here.
Would you like to start by introducing yourself, Luke, and telling us a little bit about Triangle?
Yeah, thanks, Lyndsay, so I've worked in data analytics for 20-25 years now, and I’ve worked across multiple industries, including charity, financial services, vehicle, FM, and now I've gone into consultancy.
I personally specialise in transformation projects, but my background, as an analyst, was grounded in strategic analytics or insight and visualisation, so those are my core strengths, but the thing that makes me get out of bed every day is people and helping people on their own career journey, so that that's the thing I really get motivated by.
You mentioned when we talked previously that you used to work for Mitie, so you're quite familiar with the whole IoT landscape. Would you be able to tell us a little bit more about your experience there?
Yeah, so I headed up Mitie's analytics department. I was there for about three and a half years. There were quite a lot of changes within the FM industry in that time; and business management systems (BMS) evolved quite considerably, as did sensors.
The main project I delivered was a product called Mosaic, which was all about bringing data and analytics to clients, operation teams, and the organisation's leaders. It allowed them to make far more informed decisions, and so the tool which won an award in 2020 was built and designed to empower people; it's all about making your building run more effectively, keeping your people safe.
So we've got a little bit of an icebreaker round to kick-off now, and so the first question I've got for you is, what is it that you love about data?
Well, there's loads, really; I’m a bit of a geek at heart! I think using data changes the conversation significantly, so it gives people the power to make informed decisions in areas that would ordinarily be subjective.
For someone like me who generally sees things a little bit binary in a work context, so I'm a bit more black and white than grey; it really helps people focus on what's actually happening, what's changing or what needs to happen as opposed to that ‘feeling’, e.g. ‘My 20 years of experience suggests that this is what will happen’. Data really highlights where you need to focus your efforts, and then when combined with that kind of subject matter expertise that people with lots of experience bring, it can add real value.
What I find is it creates far better, more informed decisions, and businesses thrive as opposed to if you make all your decisions subjectively, you will get some right, and you will get some wrong. I think using data reduces the number of decisions you make that will be less optimal.
What is the most common data challenge that you come across?
I think probably the biggest challenge is poor capture of information and then subsequently the poor management of it.
You can identify this in a lot of businesses and in a number of different ways, so it may be that there are multiple versions of the truth, for example, the Finance departments figures on your staff costs could differ from the HR view on how many staff you've actually got.
I think one of the biggest flags is businesses being run off Excel, so if anybody is making decisions and they're making them based on a spreadsheet, there's a lot you can do very cost-effectively to accelerate your data maturity considerably.
What would you say, in your opinion, are the main benefits of data analytics within a building and what can be achieved?
I think there's probably a couple of areas. So, I think area number one is that buildings are mostly about people. So, it's about keeping people productive or giving them environments to thrive in. However, it's not all about that, because obviously, if you go into some of the more modern factories, there's significantly more machinery than people. But I think there's a lot of commonality between the conditions that help you manufacture something in certain environments and the conditions you're going to need to manage for keeping your people happy.
Temperature is something that can be monitored, obviously in manufacturing, certain products will need to be produced at certain temperatures, and people in offices etc., will prefer the temperature at certain levels.
You've got things like the humidity levels, and you've got the levels of light and darkness, particularly over the course of the year. So, there's this whole health and safety aspect, as well as productivity, that can come from managing your building. If you use your data to drive it, you can get ahead. So, as you see temperatures rising, because you've got 20 people in a meeting room, you can start to put the aircon on, before people start complaining, you can be a bit more methodical.
Yeah. So, there's obviously a lot of benefits that can be achieved. But I suppose ultimately, it comes down to understanding what your core business needs are. There's a lot that can be captured through data, but you can get bogged down in the masses of data.
Oh, absolutely. Yeah, I mean, this is one of the things that Triangle (the organisation I work for now) pride ourselves on. Our focus is really on understanding our clients. So, every single business has different needs. But there's a lot of commonality, obviously. So, if you're producing something that is similar to another business, there will be similar issues. But I think every business has a unique culture; it has unique staff, it has unique products, unique clients. So the right solution for one is never going to be a 100% fit for someone else. For us, it's about understanding you, understanding the business and the clients, but then understanding the exam questions that each of those people need to answer in order to optimise what they're doing. But the key is understanding those people, what they're trying to do, and the problems they're trying to solve. I think that's where data really comes into its own.
I'm a firm believer that you can't ever be generic with data and reporting; you need to focus on the end consumer. So, any generic dashboards out there, which are trying to be suitable for everyone is another flag of low data maturity. You really need to get under the hood of what motivates people, decision-makers, and the business you're working for.
Do you think that COVID has accelerated the need for data insights within buildings at all?
100% Yeah. It's been really interesting talking to some of my peers across multiple industries; it has had different effects, both positive and negative for businesses, so certain industries are booming, others, particularly retail, and travel are obviously facing challenges.
But, I think the focus is a bit less on people being in the office in the future; I think what COVID has done is made businesses realise that actually people can work far more flexibly.
So, you've got to be far more focused on remote offerings; I think there's going to be significant opportunities for organisations to reduce their office estates or the amount they're renting; it may be that you actually change the purpose of some of these buildings.
One of the things I was thinking about with this current environment is there's kind of three types of work styles. So you've got your ‘head down’, which is where you don't want to be disturbed, you've got your ‘head up’, which is where you're observing, but you're still working. Both of those don't need to be around people because ‘head down’; this is where you turn everything off. ‘Head up’ is where you can have your meetings, but this can now be done over Zoom etc. It's when you get your ‘heads together’ that it’s really important for workshops and collaboration etc.
Certain teams will always benefit from being in proximity because you'll hear, ‘Oh, they've got this problem with something, Oh, great. I've got this solution already’.
But it's ‘heads together’ that I think is now the only key time where you need people together, certainly in the office environment, a little less on the frontline, but it may be that businesses have the opportunity to save costs.
The other thing it opens up is the workforce can become far more diverse. So, people anywhere around the world now can dial in, and you can work really well because we’re no longer constrained by standard office hours.
So, yeah, I think absolutely COVID has really accelerated the need for a change in working style. Remote monitoring, safety and security of vacated buildings can be managed far better by data and analytics and understanding who's where, when, etc.
So obviously, as buildings start their journey to become smart, we've seen a lot of siloed systems that can't communicate with one another. There’s lots of data in lots of different areas, which makes it quite difficult for Building and Facility Managers to use. One of our aims is to converge that data and send it to the cloud or a third-party analytics system. But how can Triangle help pull out those key insights?
I've made the point earlier about capturing and storing the data, so, as long as you're able to do that, there's so many low cost, easy ways of using it.
But ultimately, once you've captured data and got that flow of information coming in, you're only then as good as your data model. So it's really about how you curate the joins between that information. So if you ensure that you're linking data in a consistent way, then ultimately, you can understand things that you would never have done before. This may be linking your BMS to your sensor data and then subsequently to your HR data, for instance. In turn, this can identify sickness trends, which might be because a certain building or a certain room in a building has always got slightly high humidity. And therefore, you'd never in a million years identify that 1% or 2% difference, but maybe over 12 months, you start noticing that everybody who sits there has, on average, two or three days more sickness.
Do you use things like AI to pull out these insights as well?
Yes, but at Triangle, we are more focused on helping organisations start the first couple of steps of data maturity. Still, we work with partners, so we've got a very collaborative working relationship where we do joint projects with them, and they are focused on the data science side of things.
You can have millions of terabytes of data recorded every day from almost every sensor, e.g. temperature change and things like that; you just can't do it as a person. This is where you really have to throw machine power at it.
You've mentioned the importance of having data foundations in place and moving through the logical stages. Can you explain a little bit more about that?
Yeah, so the flow starts with descriptive, which is what's happened; this is your lowest level of data maturity, so most organisations are able to say something has just happened, or we've just spent x amount of pounds. The next stage is then diagnostic, which is why did something happen, so for example, we've had five fires that's the descriptive. The diagnostic is understanding why did those fires happen, e.g. the light bulb overheated and then set fire to the insulation…Then you move to predictive, which is about knowing that those things have happened historically, so learning from that and using computer algorithms, we can identify those thresholds and act ahead of time.
If you're a really advanced business, this tends to be the likes of Google and Amazon; you move to your really advanced AI side of stuff which is your prescriptive stage. This is ultimately how can we make things happen automatically and logically for people.
Obviously, it's very much the future of where buildings are going, you can understand from that description the process, and you can see how ultimately, if you were at the far end of that scale, you’re going to be adding real value.
I don't think computers are ever going to take away everybody's jobs. But they can make things so much more efficient.
Have you seen demand for data change in any industries? In Industrial, for example, things like smart warehouses and driving efficiencies?
Yeah, I mean, I think we've seen this in multiple steps of the chain we work with, from manufacturing to the logistics to the retail side of things. I think this is caused predominantly by the Amazon effect. So what Amazon have done is they have absolutely changed the game. The common person now expects to be able to get most things delivered to their door the next day; you can't do that if you run your business off Excel or even on paper-based systems; you just can't do it.
So, by having that kind of proper inventory management, you're able to go from somebody who's just bought a product from the website or from your shop, data then enables somebody to deliver that product to the warehouse so that it enables it to get to that shop faster. That then triggers a note to the manufacturer to say, we're going to need some more of this product because actually, over the last 24 hours, we've sold 50% of them.
The demand for data, and particularly around that manufacturing industry, with inventory management is huge now.
Obviously, it's essential that people harness the power of data in order to meet the need for net-zero carbon buildings. And at the moment, emissions from buildings account for almost 40% of total greenhouse gas emissions in the UK. So how can data insights help us reduce energy waste in buildings.
I mean, again, I think there are loads of things that you can do here. It's going to be really interesting how the return to normality happens, and whether it will be a new normal or previous, you know, the what we had two years ago.
Simple things like if people aren't there, make sure the lights are out, and ensure that you know the heating system is off or the air conditioning is off can be achieved quite easily.
There are new technologies that are a bit more proactive, for example, having some form of air recycling. If you've got systems above all your meeting rooms, when those meeting rooms start overheating, actually take that excess energy and excess heat and use it elsewhere. There are lots of systems that you can get out there that will do that. So I think it's really about using the data to understand where you've got high points, low points, and then using a bit of common sense, but also thinking out the box about how could we use that byproduct to make something better, and that will keep costs down.
Obviously, there are other things we can do by implementing more renewable sources. Making sure that they've got solar panels on the roof and trying to get that kind of energy consumption, by using the resources around you.
Another area that can also really help, particularly in manufacturing, is weather data to really help organisations reduce waste. Producing products in certain temperatures will either aid or hinder the production and therefore produce more or less scrap. So actually, if we can get the temperatures and the lighting as optimal as they can possibly be for that unique working condition, the net effect is that you create less substandard product, and therefore less waste.
So again, I think data can really be used to drive these changes. But I think it goes beyond that. And I think people just have to have an open mind and be a bit more proactive.
Remote monitoring is really essential, being able to have control remotely, especially because of COVID, we’re not necessarily always going to be able to actually go into a building and make changes; having the ability to control it off-site is really important.
Yeah, talking with you guys a couple of weeks ago, I think what you’re doing is really proactive, but also, the dashboarding you've got for the real-time element, it’s really quite intuitive. You could be anywhere in the world and access the dashboard; you can easily monitor and make changes.
The way the world is going technologically, utilising the cloud, means you can do most things from most places. Yes, there are some jobs that you need to physically be there for. But the vast majority of things, if it's automated and run by computers, you can do it pretty much anywhere on the planet.
Finally, I just thought it'd be nice to end by understanding what you think the Commercial/Office industry could look like in the future. Obviously, we're seeing predictions now for the future Office, where it's going to be a social hub, it's going to be flexible, tech-enabled, and most importantly, utilise data analytics to optimise the workplace in real-time. So have you got any thoughts on this? How do you see the sector changing from a data point of view?
There are companies who've been way ahead of the curve for many years. I alluded to it earlier with this, this head down, head up, heads together phrase. You're not going to need as much space, and understanding how work patterns change, how people in the office environment want to go about their working day is important.
But, personally, what I think you'll see is, buildings will change in a similar way to how retail changed a few years ago, as more stuff went online. You actually now need to make the office more of an enjoyable environment to go to. So the days where you go to the office, you've got your cafes on-site, there might be restaurants close by, you might have a cinema where you can go and watch a movie at lunchtime. But those are the sorts of things I think you're going to have to start thinking about, making it a place people actively want to come to, because I don't think employers are going to have the excuse anymore that people can't work efficiently from home.
Most people will benefit significantly from not commuting an hour or two hours and actually being there on hand for parenting for those extra hours—the flexibility of child care is a real positive and then having the ability to potentially work a little bit later etc. So, you've got the family pressure to not go back to how it was, and that will significantly influence the future office. I think offices are going to need to become a place where people actively want to come to for social and collaborative work. Some people will come in regularly; others will want to work from home; it's going to be a bit more individualist in terms of how you use that space. So Building Managers are going to need to monitor the data, capacities are going to change, and you're going to have a flux; it's going to be very different to how it was.
I really like what you said there about the cafe culture, which is definitely so true. You know, it’s no longer about just grabbing a coffee from a café; Starbucks has created a whole experience. So I suppose it's going to be the same within the office, like you said, it's got to enhance your environment. And I think that flexibility as well as being able to understand how many people are in the office, what regular routes are taken, whether a bathroom has even been used that day. Do you need cleaners to go in because no one's even been in there? That data insight is going to be really essential for saving costs, but also for safety and for efficiencies as well.