3 Key Areas for Energy Optimization and Sustainability

Hello, this is Amy Brown, a Director of Events and Education for Trade Press Media Group and FacilitiesNet. Thank you for joining us for today's webcast, Three Key Areas for Energy Optimization and Sustainability. Our presenter today is Dan Arant, sales manager for energy with Brightly. Dan joined Brightly in 2013 as a certified professional energy manager through North Carolina State University. He's also completed his certified energy manager training with the Association of Energy Engineers. And he's passionate about empowering the public and private sectors to reduce utility waste in their facilities and operations. Today's webcast learning objectives include, discuss the three key areas to focus on for sustainable energy usage, see how leading companies adapt a data first mindset and leveraging data to inform proactive facility management plans, and learn how to recognize the bad actors and identify pattern changes in energy consumption. Before we get started with today's webcast, I'd like to just cover a few details. We do encourage audience questions throughout the webcast and to submit your questions, please navigate to the Q&A button at the bottom of your screen and type in your question. Dan will answer as many questions as time permits. At the conclusion of today's webcast, you'll also receive a PDF copy of this presentation's slides. You'll receive a link to a brief online assessment and, upon successful completion of this assessment, you'll receive your CEU certification. Today's webcast will also be archived at facilitiesnet.com/webcast. And with that, I'll turn it over to you, Dan. Thanks, Amy. And thanks, everyone, for joining us today. We'll go and share my screen out here. Yeah, three key areas for sustainability and energy optimization. You know, I know Amy-- thank you for introducing me. I like to throw this slide up for a couple of reasons. Number one, I think my girls are really cute. But number two, they're actually the reason why I'm really passionate to speak about energy management. A lot of you on the call today are with health care organizations, school districts, municipalities, private industry, which are all places that my daughters' get to attend-- with school or they receive care-- in terms of health care. We shop in your retail centers. And so I like to think about energy management and sustainability from the perspective of just personal benefit. The better care that our energy manager in our local school district takes of our facilities, provides a better learning environment for my kids. Right? And so on and so forth throughout other industries. This is why I do what I do and this is why I'm very appreciative of why you all on the call do what you do. Because it matters. Right? And providing these healthy, clean environments really makes an impact. So thank you for what you do for me and my family. That said, let's actually jump in because what we're going to cover today are those three key areas. Right? If you kind of look down here at the agenda we're going to look at billing data analysis. Kind of at a high 100,000 foot view. This is the minimum we should be doing when we try to find areas for optimization. We're going to zoom in and look at interval data, which is more near real-time-- and in some cases actual real-time-- data analysis, and what are the things that we should be looking for. And then we're going to kind of look out into the future a little bit, when we talk about maintenance management-- when we talk about capital planning. What are some of the things that we should look for in the context of a sustainable future? And so we'll flow through this today all under the lens of strategic energy management. The state of energy. What I'm going to show you is no surprise. Right? This is nothing new. As we build or add building stock in the US to our portfolio, as the population has grown, as our cities have grown energy consumption has grown. Right? No surprise here. These are trends that we're familiar with. However, when we combine this growing usage-- and just the reality that the state of energy is seeing growth-- what we get is higher yields of waste in correlation. When we look at just commercial and industrial, as a subset of our building stock, and it accounts for nearly half of our US usage-- about $300 billion annually. We stack that up against this common Energy Star estimation that 30% or more of our usage is wasted through inefficiencies. That's a lot of opportunity. There's a lot of opportunity. And so that's what we're going to look at today, is we set the stage that opportunity exists. And we've responded in a number of different ways in the industry. Most recently, we're seeing a pretty large uptick in greenhouse gas reporting requirements by state. Varying levels of complexity with varying levels of penalties and requirements. But this is our response. In the context of climate, we see standards and policies and regulations come into play in how we manage and operate our buildings. To put that into perspective, when we talk about the opportunity-- energy.gov-- the DOE-- did a study. I really want to focus on this graphic on the right, the commercial energy sector. That first bar is just our current building stock. This is our energy use and density for the current building stock here in the US. And they're giving us some scenarios. Right? When we look at the opportunity we have for efficiency and energy savings by percentage. That next column, from left to right, is-- with the current building stock-- if we replace systems and components with Energy Star equipment. We've got an opportunity of about 21% savings. Next down, the best available equipment that exists. Not just that minimum Energy Star rating but the best equipment that is available. We're doubling the savings. That ET cost is the DOE's emerging technologies. And then that far right column would be if the equipment operated in these buildings were at their theoretical efficiency limits. I show all this to say-- not really to get into the weeds-- I show all this to show we've got some massive opportunities from a retro commissioning standpoint, from a modernization standpoint, from a capital planning standpoint to find saved dollars to reduce our carbon footprint. The opportunity exists. So how do we get there? Knowing that the opportunity exists. Knowing that our consumption and our costs continue to rise in our strategic energy management. Aside from wholesale capital replacements and the retro commissioning, which we will talk about in a minute, how do we improve? And it's really having a plan and a process that first, sets goals. So I'm not going to win any awards here for being an artist. But I think this really captures this strategic energy planning process. First setting goals. Do we have a net neutral or zero carbon target goal? Do we have a percent reduction goal against a baseline year? There's a lot of different options out there. We'll talk about some of those today. But what's our goal? Underneath that, really two main pillars support getting us towards sustainable goals. Obviously the capital planning side and then also operations. I like to think about it as capital planning being the equipment modernization and the building envelope modernization that we can do. The operational side is turning those knobs and flipping those switches. Right? Making sure that buildings are controlled properly, that we're not wasting resources simply because we're not managing them well. So this is the context we're going to look about today-- strategic energy management. First and foremost, and the first step here-- and I'm not going to spend too much time on this slide-- but it's cliche for a reason. You can't manage what you don't measure. We've heard it a thousand times in a thousand different scenarios, but that's the first step to strategic energy management, is just understanding what do I own and what do I manage. So we talk about our building stock. I mean, it really could be as simple as an Excel spreadsheet asset inventory that says, here's my building, here's a boiler within that building, and here's an air handler unit that service off of that boiler. It may be that simple. Obviously, Brightly sells products that help you categorize and collect asset information, but I've seen some really great spreadsheets. This concept flow through is just getting organized. What do I own from a building and asset standpoint? When I look at energy or sustainability data typically we're talking about your utility bills and your meters. So again, building A-- what utility account services building A and what meter is attached to that account? It can be really basic. And then we start talking about analyzing that data. Are we benchmarking? Are we trending? Are we modeling? So this is table stakes. I know it's 2022 but you'd be surprised at how many organizations that I speak with on a daily basis are not collecting this data. What that can look like. Again, when we talk about the buildings that we own and the things within those buildings, yes, Brightly has solutions but this could be done in spreadsheets as well. We're talking about what are those buildings? And what are those things within those buildings? And we'll talk about it a little later about some of these components that we can begin capturing-- or we should begin capturing. What are the condition of our assets? When should we replace them, based off of certain variables useful life or risk? How much will it cost when that time comes? So we can start building upon that basic foundation-- and we'll show that momentarily-- of what do I own and what are the things within those buildings? When we talk about meter data I always advise, at minimum, you should be able to replicate the line items on a utility bill. It could be very basic. Could just be my consumption and my cost. Could be demand and its cost. Could be more complex-- line items to help me capture power factor information, other services, taxes, and charges. But at minimum we should be able to replicate the information on a utility bill because there's a lot of good data there. And that's really where we're going to start when we talk about these three key components for energy optimization and sustainability. We're going to dive into the least common denominator, the low hanging fruit opportunity. Call it your 100,000 foot view. One of the biggest asks that I get as a consultant is, yeah, Dan, we track our billing data but what specifically should I be looking at? Because the reality is there's a lot of data on that bill that you can track, that you can trend, that you can correlate to meaningful information. And you don't have to be an engineer, or a certified energy manager, or even know a ton about the energy industry to be able to get some information there. So at minimum, here are a few of the things that I would look at from a utility bill analysis standpoint. First, month over month percent change. There are a lot of ways to slice and dice monthly comparisons. You can do this against a baseline year. You can do this against a modeled forecast. My blue line are my actuals, my gray line is my comparison. Again, you could simply compare to the same month last year. But bottom line, when we talk about strategic energy management-- number one, taking a snapshot of where we are today and then finding areas of improvement-- looking at utility billing data is that 100,000 foot view that lets me know where I might start to see some down trends. It's directional data. It tells me don't focus on this percentage of my building stock or my portfolio. They're doing fine. But these handful of properties and facilities over here, they're not doing that great. And we can see that at a high level, even with a simple month over month percent change report. And I would additionally say, correlating and normalizing for weather and rates are our best practice here as well. So as much information as we can gather. Right? We're not going to turn it away. But even at a basic level, holding April in my right hand and the last five Aprils in my left hand and saying, how am I doing? And similar to month over month, write a year over year. This report gives me similar direction into my portfolio as to where I need to focus time and money. I particularly like this view and the simplicity of it because, again, I may be presenting to a board or a council that has no idea about the details of energy management-- couldn't care less-- but I'm trying to ask them for funding. Most folks readily relate to red is bad and green is good. Right? So simplistic data presentation-- again, giving me direction-- that of my 10 some odd buildings that I have on the screen, two are not doing so well. That's where I should focus my limited time and my limited resources this year. This is where year over year percent changes give us great insight and direction versus detail. We've talked about some of those basic high level month over month, year over year. Most of you are probably doing this today in some form or fashion. But again, I put this in the bucket of at minimum we should be. Demand is also one of the data points that has a lot of opportunity when it's tracked well. Again, these are table stakes so they should be. But demand is also one of the most misunderstood billing points that I see. You can and you should track demand both monthly and in more real-time, which we'll talk about in a second. But at the monthly level with utility bill analytics, I'm trying to get a direction as to where I need to act or where I need to focus time. And monthly demand data can show me how seasonality impacts my cost. You can see here red bar being this year as an example. In the tail end of my summer months my demand is spiking. So seasonality, depending on the climate zone that I'm in the US, I need to know when I'm going to hit peak demand-- not just in a particular time of day. Not just in a particular day of the week or day of the month but month of the year. When do I see those demand charges the highest? Monthly demand data can give me insights into aging equipment. Or the fact that I'm not shutting down during unoccupied times. Trending demand is critically important. The other thing that we talk about with utility bill analytics-- and typically this is the most common use case with billing data-- is benchmarking energy use intensity or EUI. Again, most of you on the call are probably familiar with this. If you're not, this is the gold standard. This is the gold standard of benchmarking. So if you're on the call and you're new, look into-- maybe create an energy plan for the first time-- EUI is going to be your best friend. CBECS, or the commercial building energy consumption survey, they publish-- it tends to be every four years or so-- they publish independently verified national standards of benchmarks by building type. So what this does is it gives me a number that says, hey, for this building type, this is the number you should be at or below to be considered good. And so that number is useful. We can use that. We can set those as targets. If I'm a municipality-- and I'm just using this as an example-- and I've got a lot of fire stations, that CBECS data shows me that fire stations should be at a certain EUI based on their building type. I can start tracking and trending towards those goals. That energy use intensity is that gold standard. If you're doing this yourself-- most of you recognize Energy Star. That's what an Energy Star score is based off of. If applicable, for your organization-- not every organization has an equivalent Energy Star score-- but if applicable, Energy Star makes it really, really simple. It uses that same energy use intensity as its metric and it translates that into a letter grade. 90 and above is an A, 80 to 90 is a B, so on and so forth. This is very easy to recognize if a building is doing good or if it's not doing good compared to peers. So Energy Star is a great way to really dip our toes in the water of benchmarking. Now the final thing we'll look at when we talk about utility bill analysis is just energy versus weather. Most of the time we automatically normalize for this but it's really great visual correlations as well. If I start to see flat trends with my red line and usage, I would expect to see pretty flat trends with my dotted line and weather. Meaning weather and usage are tightly correlated. When I start to see a dip-- maybe we have less intense or less severe weather but our usage remains the same-- I would take a deeper analysis. Could be we've got more lights running. It could be I'm not isolating out for natural gas usage or something like that. But we always want to take a look at how weather is impacting our usage. Gene, I saw you got a question. It's a great time to talk about this question before we kind of get out of the utility bill side. Is there an easy way to find out where a building's demand steps are so I can get ratchet charged down? It's a great question, Gene. I always advise intimately understanding your rates and your ratchet charges, especially when it comes to demand. Demand oftentimes makes up 50% or more of your utility cost, but they're very nuanced. They're nuanced by vendor, by your utility, by region. There are hundreds of different scenarios, in terms of demand charges, and rates, and ratchet charges. It is worth pursuing. When we talk about the opportunity to reduce your demand cost, a lot of times-- if you don't have familiarity with rate structures and how they're applied, if you're in a deregulated versus a regulated energy market-- a lot of times you might need to bring on a consultant that has an area of expertise in those rates, especially in your region. But 100%, even without even knowing all the details of your question, Jean, 100% it is worth pursuing making sure that you're maximizing your understanding of your rate structures. Especially when it comes to demand. Because you're right, a few days a year can really cost. And that's where systems that we can put in place, that can give us alerts and alarms to say, hey, you're getting close to that demand threshold-- if you go above this demand threshold one time it's going to set your rate for the next 13 months-- that's a common scenario. Very much worth pursuing. Steve, looking at water usage and how it affects energy use. I typically come across that for treatment plant operations. I've had a couple of clients really get into the weeds if they've got large boiler loops, or chiller loops, or maybe university settings where you've got a lot of water flowing. You can find some cooling tower efficiencies-- things like that. But I typically see water and energy correlating to treatment plant operations and making sure our pumps are sequenced and operating efficiently. Definitely worth a look into if you've got a nuanced operation there. All right, so let's switch gears. We've talked about the utility data side. Again, I will say this transparently. My hope is that most of you on the call are doing some version of the billing analytics that I talked about. If not, they really are the least common denominator that you should be doing. The list is pretty minimal, in terms of your time to value-- time to look at the data, time to gain insights from it. It's been around for a while. But it's definitely a minimum of what we should be doing. Comparing that to interval data analysis. Where billing data is your 100,000 foot view, interval data really zooms down to the ground level. I would say it's becoming more and more common. It has been around for a while but typically in more advanced settings. But more and more utilities have replaced the meter on your buildings with smart meters-- AMI meters-- that give them the ability to look at your usage in a building every 15 to 60 minutes. Many folks aren't aware that this data is available to your organization and oftentimes with little effort. So I want to call it out here because it's really insightful data. What is interval data? We kind of shortened it down to IDR, but it's data typically collected every 15, 30, to 60 minutes. It can be used for demand response programs. It can be used to model your consumption patterns. It can be used for your controls adjustments and to validate that your building is resting when no one is in it. There's a couple of use cases that I want to look through when we talk about interval data and where you can start to see savings really, really quickly. So where you take billing data and it directionally drives you to where you focus, interval data gives you much more granular detail. Probably the most low cost, low-hanging fruit opportunity that interval data delivers is correlating usage with occupancy. There's a lot of ways that you can look at the data. In this particular graph my white area is my occupied hours of this building. In this case, it's a dorm. My dark gray periods are unoccupied times. Again, very easy to correlate. There's a building spike at 2 o'clock in the morning when no one is in it. And I don't think this is actually a dorm, now that I think about it, because that wouldn't make sense. But this is where it's really easy, from a low hanging fruit standpoint, to understand that no one should be in this building, so I should be resting. But in fact, I'm not and that has a cost impact. In this case, being able to look at rates at the same time and bring in a cost metric, I'm able to quantify if I don't correct this issue I'm losing $40 a day. So interval data-- there are varying ways that we can look at this but on the most basic level, if I've got a building that has scheduled hours-- let's call it an eight to five office building, or whatever it might be, I can look at overnight hours. I can look at weekend hours. And I should see a pretty well resting building. Again, different ways to look at data. Interval data with a heat map, energy use intensity, or demand intensity. If I've got a building that's controlled really well, I can see that visually, right? This building is controlled very well. It's more or less shut down overnight, or at least it ramps down overnight. It makes it really easy to spot the outliers. Again, this is that same spike that we just looked at in this graph just overlaid in the heat map. And so again, if we need to make controlled adjustments-- that's the idea of this slide-- if I know that this issue was a controlled issue-- that's the reason it spiked up almost to peak demand-- I could look at a heat map and understand why did it do that. And oftentimes we see really intense demand usage, or just really intense usage in general, correlate to times of the year where I might have simultaneous heating and cooling happening. Those areas where it's really cold in the morning, it warms up during the day, and my systems don't know what to do. Right? So heat maps and being able to understand changes that we make to controls, or really understanding do I need to investigate some control changes-- interval data is great for that type of analysis. Similarly, again, a different way of looking at the same data when we talk about needing to make controls adjustments. In this case, interval data allows me to throw a model consumption profile, which is what I see in orange. So I'm able to model what I should be using-- or call this a baseline model-- and blue is what I'm actually using. So if I know that this was this particular week or last week, my consumption is above the model. So again, if we need to make controls adjustments before we move into next week, that's where interval data really gives us those insights. And these models are created based off of forecasted weather. They're based off of historical conception. In this particular case, we've called it our COVID baseline because a large portion-- I think this is actually a model of an office tower-- there's a lot of vacancy. We've got a lot of tenants that are working from home so there's vacant floors. So we've created a modeled COVID-adjusted baseline, in part because of vacancy. And so interval data lets us not just look backwards, and not just look kind of present day-- like we see on the screen here and understand, should I make controls adjustments? Where do I have opportunity? But again, how we alluded, it lets us get into the predictive modeling. Because I've got interval data-- if you're tracking 15 minutes, you've got 96 data points every single day-- we've got it. And this is where big data and the internet of things comes into play. We can use that big data and the system can create models and predictive forecasts, can even get really fancy and throw in your rate structures or your market price. The idea here being, I've got a lot of data that I can make decisions on. So if I know I'm going to pay the most from my energy at a certain point during the day, I want to make sure that I'm not also predicting peak demand. I would really take a look at my operations and my controls over this time period coming up because I'm going to pay a pretty good chunk for all the energy I use in this time period, and it's correlating with some peak usage. The main response or predictive analytics, they really help us make sure-- I think, even Gene, to your point-- if we're in a demand response program, they really help us make sure that we're being strategic with taking systems offline or knowing that we probably need to take some systems offline at certain points during the day. Yeah, Jim, I only got part of your question there. The demand response model showed, of the office building in April-- I didn't get the latter half of that but I'll keep looking here in a second. Our third point. We've looked at utility bill analytics-- that 100,000 foot view. We have looked at interval data, which really zooms in, gives me much more sophistication. If my energy management program is ready for that it gives me much more sophistication and opportunities for that sophistication. Next comes in that forward look-- the maintenance and capital planning. So again, asking the question, what should we plan for? First and foremost, again table stakes, regular planned maintenance. Planned maintenance, in my opinion, is still the best energy conservation measure that you can do in your organization on a recurring basis. JLL did a study-- you probably have seen this before, in terms of the savings that come from plan maintenance, but there is an energy efficiency correlation to increased planned maintenance and decreased energy consumption. When we look at the useful life of equipment and when we look at that degradation with and without preventative maintenance, we can also model degradation of energy efficiency. And if I know that this air handler efficiency is going to be cut in half by not doing planned maintenance, that's key. I mean that's a lot of dollars wasted. I think there are some numbers out there that show if you do the run to fail model-- hey, I'm going to maintain my equipment when it breaks or I'm just going to put it in that deferred maintenance backlog because I didn't appropriately budget for capital plans or for planned maintenance-- adding $1 to your deferred maintenance backlog is going to cost you $4.00 later in capital expense. That was one of the findings that came from this JLL study. So $1 in deferred maintenance has a 4x increase later in capital expenses. And Jim, I see your question here. I'm going to come back to that on the interval data side. I'll come back to it at the end when we got our Q&A but thank you for spelling that out. So what do we do from a capital planning standpoint? We've talked about planned maintenance. It's critically important. I know a lot of councils and boards and executives sometimes don't buy into funding planned maintenance. It is more expensive on the front end. There's a lot of data that we can use to help justify those budgets. The same can probably be said true of capital plans. Do I really want to fund and budget for replacements? Shouldn't I just let it die? Well, there's a lot of options we have when we talk about capital planning. They can be basic-- and when I say basic, they can be based off of the end of useful life. If I know that, in this case, windows and doors-- they've got a 50 year shelf life-- 50 years from now I need to be ready to shell out half a million bucks to replace windows and doors. That's the idea of creating a capital plan based on end of useful life. We're looking at the life cycle and we're applying cost to a future date. So that's the basic premise of capital planning that you all know but there are other variables that we can take into account. We know just planning capital replacements based on end of useful life is not strategic. Meaning we can model a capital plan based on desired condition. So if I've got a brand new building-- that's what I call a state 0-- my service state it's brand new, all the way down to the end of useful life-- we may set a goal as an organization to keep our infrastructure in that mid-level state. It's not going to be brand new. It's not going to have police tape across the bridge so the cars don't drive across it. It's going to be somewhere right in the middle. And these models let us take into account how much money do I need each year to get to this desired state and play what-if scenarios. If I find at this level-- in the dark blue line-- it's going to slowly but surely get me there, and it's cheaper than my purple line in this basic scenario. So being able to model a capital plan based off of asset condition. You can model capital plans based off of a lot of factors. Risk. We know that a roof is a more important asset than a water fountain. I may tell the model, yeah, I'll let all the compressors go out on those and I'll let the water lines rust up before I replace the things. But for my roofs, I want to get a little more strategic about it. So we can play these games. Specifically to today, capital plans tied to energy targets. This is a big one. We're going to be net zero by 2050, or we're going to be 50% reduction in our carbon emissions by 2030, right? All of us have heard these. Many of you on the call may have some of these types of goals. So the big question is, if I've got a goal or a target for emissions, or if I've got an Energy Star goal, or if I just have a basic reduction goal, what are the things that I need to do to get me there? Right? So if I replace a chiller, if I replace a boiler, and I don't replace my doors and windows, how does that affect my model? If I go the decarbonization route and I get rid of everything that burns natural gas and replace it with electrical systems, how soon will I hit net zero? So again, when we talk about capital planning, the biggest thing that I want to highlight here is, on a basic level, yeah, we need to have a plan. And it should be an educated plan based on age and condition. But know that there are software applications-- that there are strategies even-- that help us model based off of different variables. In summary, we've looked at utility bills, we've looked at interval data, we've looked at capital plans. I like to operate under this 10% rule. You're going to remember 10% of what I talked about today. So what is that 10% that we should remember? Number one, track your buildings, your assets, and your data. We have systems that can assist you with this. Other companies have systems that can assist you with this. I've also seen really great spreadsheets. But it's 2022 and this is table stakes-- we've got to understand what we're managing. Billing data shows you where to act. Interval data can show you how to act. So that billing data is that 100,000 foot view. It directionally focuses me on low-performing properties. Interval data is really going to show me control opportunities, adjustments that I can make, set point so that I can change. It gets more specific. From a maintenance standpoint, planned maintenance is your best friend. It is the best recurring energy conservation measure that exists. It extends the life of your equipment and it makes it more efficient. And then finally, have a capital plan. Again, I know that they can be complex. They can take time to put together. But at minimum, you should be able to plan and budget for replacements of equipment. So with that, I thank you we are going to take some time for questions and we've got a poll coming up. I want to know how to be able to follow up with you. If you would like more information about energy management, about capital planning, about asset management, or some engineering services, let us know. You can check any of these boxes. We will be respectful, obviously, with your information and reach out to you on a one-on-one basis. So let us know how we can follow-up. And I will, while that poll is up-- I will take some questions. Or Amy, I think we've got some questions. We do, Dan. Yes. We have the follow-up question from Jim Newman. he was asking about-- it looked like-- if we go back to that model you had-- the model you had shown of the office building, it looked like nobody was in the building. Would that have been correct because that might be a one day normal work week in that building? That's right. That's right. Yeah, actually, Jim, that's a really great question. So again, these are screenshots. It might be advantageous for us to sit down one-on-one Jim and go through some of these models. This is just a quick snapshot. But you're right. This modeled forecast, yeah, is definitely taken into account. This is likely a weekend application. I'd have to go back and look at these dates on the calendar. But this secondary plot-- you had mentioned higher or lower outdoor air temps. Yeah, in this particular model my secondary plot is a rate or a market price. My secondary plot could also be outdoor temperatures and humidity levels. We can really model a lot of correlating variables here in these particular scenarios. These are just the examples that I gave. It's a really great question. And you're right, weather is going to be a key one. Weather is necessarily baked into these predictive models. So if I go back to this view, weather is already baked in here. Your rates are already baked in here. The secondary overlay is just that. It's an overlay so you can see it visually. And thanks, David. Yes, Saturday, Sunday. I knew that's what it was. Jim, good job calling it out. But, yeah, that's right. So we want to take into account occupied versus unoccupied. That's what this model is looking at-- so weekend versus obviously modeling higher usage during predicted occupied hours. Yeah, great insight there guys. Perfect. Another question for you, Dan, is, what are you seeing as the biggest barriers to what you're calling strategic energy management? That's a good question. The response may sound simple but truly the biggest barrier that I'm seeing is priority. So many organizations are assuming, man, if I'm going to get on the sustainability bandwagon-- and I don't want to use the term bandwagon because it's critically important that our organizations take this seriously, but a lot of folks just think that this-- kind of what I see here-- this sophistication of analysis is everything and it can be a little intimidating. It can be intimidating if you're new to the organization or you're new to energy management. And that's why I wanted to highlight, at minimum, analyzing from your utility bills. You should see about 5%, 6%, 7% savings annually off of your budgets looking at utility billing data. So yeah, when we get into interval data analysis you can get into the 13%, 14%, 15% plus range of savings yielded, in terms of an ROI perspective, but just kind of putting a stake in the ground and saying we're going to take this seriously-- we're going to set some goals and targets-- that tends to be the biggest barrier right now, is just folks taking the initiative. AMY BROWN: Perfect. We've got another question. They've never tracked interval data. Where is this information coming from and where's the best place to Start Yep, that's not surprising. Like I say, interval data has actually been around for a good chunk of time. It's not been as readily available in the market as it is today. So first and foremost, we go to your utility provider, like I said. I've got a chart somewhere-- I probably should have thrown it out-- but most of the larger utilities throughout the country have replaced the meters on your buildings with smart meters. It actually helps them charge you more accurately from a demand perspective. So there's a payback for them. But we can usually get interval data from your utility provider. Obviously there are situations where the utilities have not upgraded that meter infrastructure. In those cases we've got organizations that are investing in installing their own submeter network or smart meter network. There's a lot of companies out there that do it. I've got a few favorites that I could recommend that you could typically probably estimate somewhere between $500 to $1,500 per install on those devices, depending on the complexity of the meter that you want, for what it's worth. We can get that from submeter data as well. AMY BROWN: Perfect. Dan, we have one attendee is asking your suggestion on how to motivate commercial real estate holders to save energy when it's the tenant paying the utility bills. Yeah, that's a great question, Scott. This question we deal with probably on a weekly basis. The biggest thing now-- motivate is the word that I would key in on on that question, Scott. If you're the owner of the building, or maybe your company are the owners, or maybe your asset managers, or whatever your role is, you're not paying the bill but likely you have been asked for ESG data or sustainability data for the portfolio that you manage. There's a twofold value for tracking energy data throughout your portfolio in commercial real estate. Number one, it's being able to report to your stakeholders-- maybe a board. It may be an investment group. Number two, attracting top tenants. Being able to show that you are a sustainable organization. Here's our ESG reports, or our annuals, or whatever it might be. So that first phase of answering that question, Scott, would be, the data is valuable for you as the owner as well for your investment portfolio into your stakeholders. In terms of motivating tenants who pay the bills, I've seen a lot of owners give guidance-- work with a firm. We work with a lot of owners who have tenants. And providing software-- like you see on the screen here-- allows them to better reduce their energy consumption and decrease rental rates. Right? You can more accurately charge your tenants for rent because the overall demand on the facility is lessened. Assets are maintained longer. There's a lot of nuance there and I know if the answer sounds a little vague there's a lot of nuance there but we've got a lot of experience in that world, Scott. Now-- DAN ARANT: And it's becoming more and more of a priority to attract investments in the commercial real estate side with these ESG mandates and initiatives. It's top of mind for a lot of us and we're learning a lot as the industry progresses. AMY BROWN: Perfect. We have another question. Is the cost to install and maintain smart meters and IoT UST energy data collection management a factor which might dissuade building owners or managers from investments? Have you seen a little bit about the investment of smart meters and-- Yeah. Yeah, it's a great question. When I think about the ongoing maintenance of a submeter network that you own, I don't typically see it from a hardware perspective. Meaning I don't often see the meters fully breaking or needing to be calibrated all the time. I don't see issues with electrical lines and things like that. The biggest thing that I see is a variable in you owning the meter versus the utility is, depending on how they're wired-- they can be cell pulses. They can be internet, hardwired in. A lot of times there can be gaps in the data. A data can read perfectly and cleanly for 96 points every day, and then the next day you've got a six hour gap where the data just didn't read. We probably see that as the most common and we've got some algorithms built in-- I know other companies do as well. But we've got algorithms built in that smooth out that trend so it'll look at historical usage over similar time periods, and similar weather patterns, and occupancy, et cetera. And it'll basically fill in the gap with some of those models if you're using the interval data for monthly or annual reporting. That's typically what I see is the biggest lift on what we call ongoing maintenance of these meters. And then, of course, the setup. The initial install is a big lift. Perfect. Dan, kind of going back to the commercial real estate. Somebody is asking, how do you see this entire piece on energy optimization supporting the prop tech agenda? Say that one more time, Amy. You cut out. I didn't hear. No problem. How do you see the entire piece on energy optimization supporting the prop tech agenda? I may be mishearing you. The prop tech agenda-- I'm actually not familiar with the prop tech agenda. I can do some research on that and get back to you on that answer. I'm not readily familiar. AMY BROWN: Perfect. If the attendee who asked the question wants to provide a follow-up question just let us know too. Yeah. OK. We have time for just a few more questions so feel free to keep sending them in. Dan, we've got a question. My leadership has never budgeted beyond a simple capital fund that's never enough. What have you seen other organizations do to secure more capital funding? Yeah. I'm looking, Tom, at your statement on educate tenants and I'm keying in on that word. Education is really a big piece of securing funding. Is being able to model out the cost savings over time. When we consistently fund a capital plan for, let's just say 20 years, our models are showing, if you stack a run to fail program on top of a certain investment rate over the next 20 years, we've got a couple of models that show a substantial savings by consistently funding. So a run to fail scenario, you might ask for-- I'm making up numbers-- you may be asking for $3 million one year. You may be asking for $700,000 the next year. You may be asking for nothing year three. So on and so forth. I've never seen a board, a council, an executive team-- I've never seen one fund that strategy at full completion. You're going to ask for $3 million and they're going to give you $750,000. I've never seen them fund that variability and it's because it's variable. We've got no consistency. We've got no ability to predict or forecast a consistent budget. That's the biggest-- I guess that would be what I'd lead in in education, is being able to model out over a 20 year span, we're actually going to save. If you go back to that $1 of deferred maintenance turns into $4 of capital expenses later? That's the model that I would run. And of course, we can help you do that. I know other consultants can help you do that. But it's really just educating on a consistently funded capital plan. Look at it in the same way as an investment portfolio. I put dollars in today, I get a great yield in the future. AMY BROWN: Perfect. Well, it does look like we are slowing down on some questions and coming up to the top of the hour. Dan, any final thoughts for our audience as we wrap up today's event? I appreciate the questions and the engagement. Absolutely appreciate the feedback. And Tom, I would even again jump on your statement of educate tenants. Just providing information may be enough. I just want to validate that statement. Absolutely. There are certain dashboards and portals that our commercial real estate owners provide to their tenants, from our solutions in particular, where the education is quite helpful. So I just want to validate that. But, yeah, thanks for the time and the engagement. AMY BROWN: Wonderful. Well, thank you again, Dan, for being a wonderful subject matter expert for today's webcast, and Brightly for sponsoring today's event. Just a reminder, you will receive a follow-up email with the slides used in today's presentation, as well as your CEU link that you-- after taking a quick four true false questions you can have a CEU transcript for your participation today. And then it will also be archived at facilitiesnet.com/webcasts. Thank you again to Dan and Brightly, and we look forward to seeing you at our next FacilitiesNet webcast. Have a wonderful day, everyone.