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17 min read

SBA 237: Building Automation As A Service?

By Phil Zito on Feb 8, 2021 6:00:00 AM

Topics: Podcasts

In this episode of the Smart Buildings Academy Podcast, we discuss building automation as a service. What is it?

Is it viable?

Why would you use it?

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Show notes

Phil Zito 0:00
This is the smart buildings Academy podcast with Phil Zito Episode 237. Hey folks, Phil Zito here and welcome to Episode 237 of the smart buildings Academy podcast. And in this episode we are going to be talking about building automation. As a service, this topic has been really, really in focus lately. But I bet you wouldn't know it if you weren't looking for it. You know, still on LinkedIn, we are seeing analytics is all the rage digital twins is all the rage. But beneath the surface, we are getting increasing questions around SAS models, Software as a Service models, our customers are coming to us large real estate firms owner operator firms, and they're asking us as a vendor agnostic provider of training and workforce development. What do you think of software as a service? Is it a viable approach to our business? Will it be something that we should be thinking about? Or that we should be considering? Is it going to be something that is, you know, a viable solution for our assets? And this kind of surprised me, because a lot of these people who were asking these questions, were real estate owners and operators and thinking to myself, well, aren't real estate companies struggling right now to have cash flow? Why would they be asking about software as a service? And so I asked that question. I said, aren't, aren't you guys struggling to bring in cash right now? And why would you be interested in software as a service? And they said, Well, we are struggling to bring in cash. But we also realized that moving forward for a lot of our assets to be valuable to our occupiers, they need to be modernized from a technology perspective. Additionally, we're seeing increasingly that our it groups are taking more and more control of facility assets. facility assets are riding on it networks, and since facilities can't speak it, and this is a general statement here, there's plenty of facility folks who can speak it very well. But from a general statement, and this is these customers words, not my words. Since the facility struggles to speak it, it is getting more involved in selection, and it loves SAS models. So what is a SaaS model? What is an as a service model? Well, there's three primary service models, right? There's Infrastructure as a Service, there's platform as a service, and there's software as a service. So throughout this podcast episode, I'm going to go through what SAS is. We're gonna talk about the benefits of sass, I'm going to talk about the misconceptions of sass, we're going to talk about the different SaaS solutions that are kind of in the market. Right now we're going to talk about the push by a lot of the large OEMs to adopt a SaaS model for like, the fourth time, because there's a lot of OEMs. I mean, I used to work for an OEM, who went out and had a huge push for SAS model way before its time was actually a really cool solution. You probably heard of it called pan optics. Back in Johnson Controls land, it was a really cool solution. It just did not gain adoption. And then all the parts and pieces of it got kind of split out in the organization, and reabsorbed by other products solutions. So we're going to talk through kind of all of that. Before I get started. I do want to mention that this podcast episode like always, is sponsored by our smart buildings, Academy training, and assessment programs. And that's what I want to talk to you about today. If you are a business owner, controls business owner, or maybe you work in facilities or run a facilities team and you're like, man, I know we need to get our folks up to speed we have all these vendors coming to us with their training solutions. We have all these schools saying that they could do training and development for us but you know, we just don't know where we should invest our training dollars, then I encourage you to reach out to us go to podcast dot smart buildings academy.com forward

Phil Zito 4:38
slash 237 scroll down and click on the online skill assessment link. It's there that you will be able to set up a window to perform a complimentary online skill assessment for your team. This online skill assessment will pinpoint exactly what your team does and does not know and will provide quantitative data that enables you to understand the strengths and weaknesses of your team. So you can make proper training investments, obviously, I would hope that you would choose to utilize us as your training provider. But if you do not, you can still take this information that you have gained about your team and use it to make the appropriate learning and development strategy decisions. Alright, so let's dive in to software as a service. As I mentioned, there's three types of as service models, there's actually more but these are the three most common, there's infrastructure as a service. And this is common where you go and you actually purchase infrastructure, you see this in a lot in networking, right? you're purchasing infrastructure, and this infrastructure is then utilized by you, but you don't own it, you're not making the capital investment. So you're leasing infrastructure. And you can see this actually, every time you travel on a plane, most of the jet engines, the infrastructure, are actually as a service model, they you pay for the miles basically, that you utilize the jet engine. So that was kind of interesting for me to find that out that a lot of people actually do not own the jet engines in their planes, it was kind of interesting. Then you have platform as a service. And so platform as a service is like Microsoft Azure, right? Microsoft Azure offers you platforms, they offer you, platforms that you can build upon, you can build your applications on these platforms. Same with AWS. And same with the Google Cloud, you can build on their platforms and develop your applications. And then deploy these applications and SaaS software as a service is just what it sounds like, right? You are purchasing software you are getting Well, you're not purchasing, you are basically leasing software, you don't actually own the software. Now, there are some terms that are unique to building automation specific to data. But I would argue that it's more of just dealing with an objection with an answer that's not necessarily effective. And I'll talk through that in much greater detail. But often, folks, one of the first questions they ask is, what do I owe? And if I choose to end the SAS model, and you'll often be given the kind of cliche answer, well, you own your data. But yeah, you may own your data. But is it in a format that's even ingestible? to any other system? We'll talk about that in a bit when we talk about some of the downsides of SaaS based models. But why software as a service? Well, if you're thinking about software, right, and you're thinking about how much it costs to develop software as an OEM, having a SaaS model where people are predictably, paying a certain amount of money enables you to rapidly recoup your r&d costs. So you can basically predict, okay, we're going to make an investment and we're going to predict that we're going to have this many adopters, and the adopters are going to cost X dollars are going to pay X dollars, and that will recoup our r&d and then it becomes a cash flow asset for us as an OEM. So that's kind of the thinking behind creating SAS models. Now SAS model also, since it's typically cloud based, acts as a single source of truth for multiple clients. So rather than trying to deploy updates and firmware changes and things through multiple customers sites, which they may or may not have the same infrastructure, they may not be accessible. A SaaS model enables you to do constant just in time upgrades. It enables you to roll out cybersecurity updates, firmware updates, if you are using your SaaS platform properly as an OEM and you're actually tracking how occupants and how end users are using the system, you can actually and this is the level of detail that these systems will go into, they will start to look at where do people click, they'll heat map that and heat mapping is basically tracking through cookies where people click and where their mouse cursor goes. And by doing that, you can say okay, it's taking people four steps to get to this report. So and we see 90% of the people are utilizing this report, we are going to adjust our front end graphics to make that report a one click.

Phil Zito 9:37
And so there is a viable, really, besides for the constant upgrades. There's a viable benefit in the background of user experience of increased capabilities that are pretty beneficial if properly deployed, and I use the F as kind of a big air quotes there. Because you've got to have a strategy in order to properly deploy SAS. Additionally, there is predictable cost on the owner side. So now as you're making a operational investment in lieu of a capital investment, you now have a predictable cost that you can budget and you can go and potentially pass on to your tenants, there's a variety of things that you can do with a predictable cost add, shift my chair there for a second. And you can also have additional services, so you can do kind of a good, better best, you can have your baseline SAS model, which may be purely visualization. And you can have add on services ties into digital twins ties into data model analysis ties into analytics. But is all of this really cheaper? Yes and no. So here's the thing, and this is why I was reading a post by James dice the other day, and he was like, why hasn't analytics caught on and my, you know, snarky little self was like, Well, the only way it's gonna catch on is if it's governmentally mandated, because people aren't going to adopt it. And as I started to think about the response, there is some truth to that. But one of the problems with SAS and analytics and all of these services, is that it's not like traditional SAS. And when I say traditional SAS, if I go, and I want to create a podcast graphic for our business, let's say my marketing lady's busy, she's working on a webinar deck or something for us. And I get a, you know, crazy idea. And I want to go create a graphic, which really should not be happening because I have the artistic talent of a two year old. But let's say I do, we use Canva, and Canva is, Oh, my gosh, it is an amazing SAS software. But it requires no infrastructure, I mean, short of my computer to be able to connect to Canvas website, I don't need any infrastructure. But that is not the case. With building automation, SAS, you need controllers, you need supervisory devices, you need input and output devices. So SAS is a add on to an existing capital cost. Anyone who is telling you that SAS based building automation systems are going to reduce the total cost of a building automation system are full of crap, it's not going to reduce the total cost, it's not going to reduce the total cost of ownership. No, it's not. I know you're saying it is, it's not going to, because they are still going to have to go and buy all of the infrastructure and put in the infrastructure. And you're like, But wait, we have an existing building automation system. So surely that doesn't apply. Actually, existing building automation systems are often more costly to integrate with, then new automation systems, because you often are pigeon holed into a data model that your existing control system may not match up to. So you have to go in and adjust naming schemas, you have to adjust data sampling schemas, if you've got a legacy system that's running at 9600 baud, and isn't possible for that system to go and have the data flow rate that the

Phil Zito 13:26
SAS based building automation system necessitates, then you're going to find yourself in a world of hurt. So there is a cost related to retrofit modernization in order to utilize a SaaS model. So is a SaaS model cost effective? We'll talk about that in just a second. But before we go there, I want to talk about something I kind of hinted at a little bit earlier in the episode, which was the data ownership. Oftentimes, folks will say, What do I own? If I invest in a SaaS model? What do I get? What happens when I stopped paying? You know, I asked that of a company the other day, and they said, while they you, they keep controlling, right? The system keeps controlling, they can't turn off control, but they lose the visualization and they lose the analytics capabilities of it. That's not as bad as I thought. I mean, I could envision some companies defaulting on their SAS payments. And it would be really bad if everything just shut down. But as long as everything keeps running. I mean, that's not very different than some commercial buildings and schools that are out there right now. Where they just keep the BA s in the closet anyways, and the only time they go in there is you know, when they've had a really major complaint, most of the stuff they just drive in hand and then they wonder why things aren't controlling properly. But that's a whole nother topic. But The issue of data becomes a very pertinent issue. People are like, Okay, well we own the data. Okay, that's great. You own the data. But can you actually use the data? So you get a CSV file or you get a JSON, ask export from an API and you get a huge data dump? What do you do with that data? What does that data matter to you? Now, let's say you get it all in CSV format, or you get a database dump or something like an SQL database? And you're like, Okay, what can I do with this? Can you import it into someone else's software? Can you import it back into your VA s? Oftentimes, the answer is no. And so this argument of you get to keep your data, your data is your most important asset. I agree your data absolutely is your most important asset, from space planning, to analytics to purchasing trends, to optimizing your designs, data has so many potential benefits to it that are not really being recognized by our industry. That being said, just grabbing a data dump from an existing system is not necessarily going to be beneficial to you. So I just want to be clear on that because I feel like people are being goof goosed goofed. I don't know, whatever the proper word is. They're being led astray, not intentionally, I don't think I really think the people who are echoing these you own your data lines, they don't even understand what that means. Because they're not data scientists so mean to them. They feel like they're doing the right thing for their customer, and maybe they are, but owning your data is not necessarily a useful thing. That being said, how do we go about evaluating a SaaS solution? How do we make a decision for utilizing a SaaS based model for our building automation system? Well, the first thing we have to ask is, what would the SAS based model allow us to do now that we currently can't do? If all we're doing is trying to get a SaaS based model so that our latest software can stay up to date? Why not just get a software subscription? Why do you need to switch to a SaaS based model? If you are going and looking at a SaaS based model for analytics, but you have no facility operations and troubleshooting process? What's going to be different? You're going to get this analytic system that's going to overwhelm you with data, you're going to get all these potential faults and suggestions. But how are you going to implement these suggestions? What culturally is going to be different within your business? Okay, let's say you gather a bunch of data and you understand space utilization, and you understand operation. And now you're going to output all of that data into a digital twin. But why? What benefit Are you going to get from that? Especially if you never go and modernize your buildings? What if you have no future plans of doing tenant finish outs? What if you have no future plans of building new buildings or having new built assets? What would having all that data and outputting that data into a digital twins model do for you? Probably not much. Now, all negativity aside, let's say you're a huge property management firm. And one of the things that your value prop is tied to is optimizing the valuation and the utilization of space within these commercial assets, well, then you may be able to use the SAS based model, that SAS base model may be able to tell you how spaces are utilized. And then you can kind of project out different space utilization strategies to optimize the use and the cash flow of space, you may be able to say, well, this space type delivers X dollars per square foot, and that space type delivers y dollars per square foot, we're seeing that utilization is z. And we are going to then go and do a calculation and figure out how do we build our buildings differently? How do we utilize our systems differently? Additionally, let's say that the current administration at the time of this recording does indeed decide to drive some pretty heavy handed sustainability and energy efficiency requirements in our space codes start to adjust. We're starting to see forced adoption of ECM energy conservation measures. How do we go about modeling those out? A SaaS based model may be a great solution for a large portfolio, the ability to consume the data, the ability to do projections in a digital twin model, and say that we can forecast these things out because I don't know about you, but anyone who has ever worked With modeling software,

Phil Zito 20:03
it's difficult, it's quite difficult. And if you can put it into a platform, if you can ingest the data into a platform that's already created, and makes it easy, you're gonna save a good amount of time. And if you're able to then go and calculate the benefit of ECM, energy conservation measures or fims, facility improvement measures, and you're able to calculate those before you make capital investments in infrastructure changes, tenant finish outs, retrofits, etc. The software solution may pay for itself. So as we evaluate solutions, we need to look at that we also need to be cognizant of the trends in the industry right now, which are we are losing a significant amount of our workforce. I know I've hammered this for the past several years on the podcast, and at times, it's been accurate, and at times I've been completely wrong. The trend has continued to move towards a mass exodus of talent in our workforce, the outside factors, the external factors have slowed and accelerated that at times, but we are still seeing that trend. You can only age so much until you become cognitively ineffective, I guess that would be the PC way of saying you're just too old to do your job anymore. But the reality is, there's going to be people who they just hit their cognitive prime, and they can't really effectively do their work anymore. And we'd be remiss to not discuss that. And the reality is, what are the ways that you augment a ageing workforce that has a lot of tacit knowledge that has not been captured or passed down about legacy systems? Well, one of the ways you augment that is by going and taking the complexity out of the system, using analytics, using data analysis, and really going and trying to pull the key nuggets so that less experienced operators can take action on those key nuggets of information. And that's something not enough people are properly discussing. And I think we're gonna see a lot of assets, start to really appreciate the impact of that, as people start to leave the workforce. And these legacy systems that they can no longer procure, are unable to be maintained, and you're going to see a push for retrofit. And then you're going to see people who are operating these new retrofitted buildings, and they don't necessarily operate them the same way. And this is where a SaaS based model is going to come into play. But we have to ask ourselves, is it a BA s as a service? Or is it really just specific SAS models, and we should be looking more at less of an OEM play. So less of a we're going to take the OEM SAS model, and we're rather looking into the market to see the best in class providers of task specific SAS solutions. So for example, a task specific that's man, that is a mouthful to say, a task specific SaaS solution, I feel like we're doing English grammar, one on one here. But one of those is going to be something like an analytic solution, maybe a fault detection solution. Maybe a work or force management may be a space use analysis. There's a variety of different SaaS solutions. But that's where I really see us going, not so much platform adoption, you will see large scale SAS adoption by large scale companies, because quite simply having a single source of truth for an OEM that can provide consistent support not only from the home office, but also in offices located in your specific Metro is definitely beneficial for a widespread company. But for the smaller scale companies, the more regional or Metro specific companies, you're going to see those more focus on individual players. That's where I see the market being built out. The challenge is going to continue to be though data models and issues with data models and getting data out of the building automation system. Still to this day, back net is the protocol of choice. please, for the love of god don't adopt BACnet sc. It's, I don't know why we are trading our ability to have API's and JSON and data feeds. We're so close. We're so close. People just do that. In lieu of getting yet another

Phil Zito 25:01
I'm going to call it proprietary. Although people argue it's open, I'm going to say it's proprietary from the fact that no one in the IT world is going to understand it. But the issue is going to be that we're going to have yet another barrier to data flow and data consumption. And because of that, we are going to see really poor adoption of these SAS based models. Because here's the thing. If you look at a lot of the web applications that are SAS outside of our industry, they use common protocols. They use common API's, they have common SDK, they do proper API versioning. We are so immature, as an industry when it comes to doing that. And those issues lead us to being unable to properly deploy SAS models. Alright, so I'm going to kind of recap here on a couple things. First is, there's three types of of as a service models, infrastructure platform as a service and software as a service. building automation software as a service models are dependent on having infrastructure in place. So there is definitely a first cost component, whether it's new construction or retrofit, the benefits definitely are that you get consistent upgrades, you have predictable cost, and you can have additional services. And those additional capabilities and services can be rapidly deployed to the market. So you're able to see those quite quickly. But at the same time, it's not necessarily cheaper, you are locking yourself into some solutions. The data you get when you decide to divest yourself of the solution is not necessarily usable all the time. And we need to be aware that once again, SAS is very much infrastructure dependent. As an industry, we're an industry of two conflicting worlds, we have a lot of venture capital based companies that are moving into prop tech, and are moving into building tech. And they've got innovative ideas, and they're creating them rather quickly. However, as an industry, we still have legacy data models, we have protocols that are not easy to work with, and are surprisingly backwards, for, you know, how advanced our industry has become, at least on the software side. And so those are going to continue to be challenges we're gonna face. The industry is at a set of dividing point right now, where we can choose to continue down these industry specific protocols, we can continue to say that it's too difficult to do object models, it's too difficult to do data standardization. And you know, we're not looking at other industries that have figured it out, they figured out how to work with API's. And we're gonna go down and do BACnet sc and we're gonna continue to do our little proprietary bastardized building automation protocols. Or we can continue to go down the path of the IT industry, looking at standardized IoT protocols, looking at lightweight protocols like mq, tt, HTTP API's, etc. and we can adopt those and their associated data models. And we can go and really see a bright future for our industry. So I'm interested in your thoughts. What are your thoughts of software as a service? Have you used it? How have you used it? Has it been beneficial? would you use it again? What would you have changed? What would you have not changed? Am I all wet on us? not creating another protocol, but utilizing it protocols? What am I missing here? I'd love to hear from you in the comments, wherever you're listening to this. either go into the discussions, the comments, whether you're on Facebook, YouTube, on the podcast, etc. Thanks a ton. And I encourage you to go check out all of our resources at podcast dot smart buildings academy.com Ford slash 237. Thanks a ton and have a great rest of your day. Take care.

Transcribed by https://otter.ai

Phil Zito

Written by Phil Zito

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