Sam:

Welcome, everybody who's jumping in so far. We're excited to get this webinar started. But we'll give everybody a couple minutes. In the meantime… Definitely let us know in the chat where you're all coming from, or where you're at, throughout the world. customers every part of the world, I feel like. Obviously, most of it is in the U.S, but… We have customers all over the place. So, yeah, let us know where you're at. Manases, Virginia. Barbara, welcome.

I probably said it wrong. Manases. Did I say it right?

Hey, I got it right.

Mach John, SLC, Present.

Brandon and I are both in… Provo area. About 60… Miles south of Salt Lake.

Is that… Justin? S. Justin is a Buffalo Bills fan. And I'm a Denver Broncos fan, and the Denver Broncos beat the Bills in the playoffs, only to have Bo Nix break his ankle in that game. And then not be able to play in the conference championship. So, it probably should have been the Bills in the first place anyway.

Edwin, welcome, from SMG. Good to have you here.

Alright… We'll kind of let this song close out, and then… Yes, thank you, Justin. We'll let this song close out, and then we'll get started, so we'll let the two that might be still jumping in jump in.

Also, just as a way of, letting people know, we… We do want you to… utilize the Q&A function that is at the bottom of the Zoom meeting. If a question comes up while we're speaking about something, please just enter the comment there. Or the question inside of the Q&A button, and then after my portion, which is gonna be the first part of the presentation, we're gonna… give the… the wheel to Brandon, where he's gonna go over some of the things live through the portal, and we can answer questions then, and we'll make sure we leave some time for any additional questions that might arise after the demonstration.

Alright… Also, if there's anything that you… You just absolutely love? When we're talking today, use the reaction button at the bottom of the page as well. It allows you to just send reaction, helps me and Brandon know if we're doing an alright job. Okay. Well, let's get started. Brandon? and I are super excited to go through this webinar today, where we're talking about turning the raw data that you are capturing in Otuvy currently, From inspections and work orders, and turning it into operational signals. This is a customer-only VIP access event, so if you are in here, you are one of the… folks that is an Otuvy customer and utilizing the solution, we're excited to get things rolling. So for a way of just kind of giving you an understanding of what's going to happen today. The first half, we're gonna talk about the framework that we believe you can implement right away, regardless of the style of data that you have right now. But ways to really improve it through operational intelligence platinum functions. You've probably interacted with Brandon, who's our Head of Customer Service and Solutions, or myself, I'm the COO, over the past several years, and our discussions with users and folks just like yourselves has led us to understand the difference between just capturing raw metrics and turning them into operational signals, and the difference between those two things. So we're gonna talk about that. We're gonna talk about 3 steps you can implement today. How proactive client communication can really enhance the overall growth of your operation and the business. And then, what manual monitoring looks like versus automation. And then, as I mentioned a second ago, the second half is gonna be an actual live demo by Brandon. Where he's gonna log into O2VQM, showcase those premium functionalities, and then we'll give you an understanding of how you could access that, be trained on those things, ultimately get your system in a place that would allow you to automate those steps that we're gonna talk about today.

So, if we're ready to get started, let's dive in to first… the core problem. So, as Otuvy customers, you already have a lot of operational data that's being collected in your system every day, through the inspections, through the work orders. You might be capturing things like response and completion times, you're gathering notes from the inspections, different communications on work orders, potentially. All of those things showcase trends across your locations over time. And that's why you use the dashboards the way you do, so that you can understand those trends. But, the challenge that most teams that we work with face is usually Not access to the data. But, and raise your hand if this is true for you. the challenge, send an emoji in the chat. The challenge is actually knowing when the data actually requires action, right? You capture the data, what's the action that should happen? with that data. So, often, performance issues are only addressed After, they've already had an impact in some way to your customer. So, maybe that customer notices something first. Maybe you see the trend weeks later. So what I want to highlight today in my presentation, and then through the live demonstration that Brandon will give later. Is how do you turn that data you're capturing every day into signals that actually tell you when to act? How to act?

Alright, so here's… here's the contrast, right? Raw metrics are things that we notice and react to emotionally. For example, Our inspection score dropped at this location. what do we do? Right? That's… that's a reactionary and emotional moment when we see that number. If you create it as an operational signal. For this example, our inspection score dropped below our defined threshold, which triggers retraining within 72 hours. Do you see the difference between the two approaches? The first one is very reactionary, the second one is proactive. And that key difference is the signal, right? Not just seeing the number, but a signal that actually requires action, and has action tied to it. So, there's 3… Things that we believe a signal requires. The first is a metric. You need to know what you're measuring. So, in our dataset, that is also in all of your data sets, is inspection scores, response time, the… the amount of errors that might be coming up inside of the quality data you're finding. Things like that. Those are data points. Then, a threshold. A threshold is you need a specific trigger point, not just this is lower, but an actual number, right? So, it would be more like, this is below 85%. or whatever your standard might be. So you gotta find that threshold to define the level of the trigger. To then lead to the predefined action. Which, before the signal fires, you're already decided. What happens next? Retraining. Escalation. Investigation. Reach out to the customer, whatever it is. that action comes after a metric and the threshold designed. If you don't have all three of those, it literally is just reporting where you can and will most likely remain reactive to those numbers.

So… Now, I'm gonna dive into the 3 steps of the framework that we suggest that you implement today. And you should be able to take this information today and start using it in your teams, especially if you're managing the data for your organization.

So, step number one. Establishing a baseline using Otuvy. So… when we… talk about data. It's important to create a defined amount of time that would lead you to data… That gives you that normal performance snapshot. So we suggest that you need about 8 to 12 weeks of scores, so being consistent and frequent in your scoring through inspections. And or work orders, whichever module you're trying to gather data on to set those triggers. We suggest 8 to 12 weeks of historical data to define normal. What does that normal performance look like for your operation? So it could be inspection scores and deficiencies, could be work order response times, work order completion times, it could be work order frequencies. Once you've gathered that, then you can go into that detail… And… talk about what the baseline is and the normal range is, right? What's your average? What's your normal range? The reason you get to this point is because then it will allow you to actually create what… Triggers or, opportunities you're looking to actually have trigger.

So, I did highlight there one of the examples, like, let's say it is inspection scores. Go to that inspection dashboard, you filter by location, you pull the last 8 to 12 weeks of scores, and then you identify your average and normal fluctuation range. I put an example there. Let's say your average score is 92% on your defined baseline, right? On average, we have a 92% for this specific location. And the normal range it fluctuates in that time frame is 90-94%.

Once you have that baseline set, you then have the opportunity to go a little deeper into defining the triggers. But I do want to talk about, briefly, what happens without a baseline. So, if you don't create that baseline, and it's just… you're looking at data when you're ready to look at data. you probably feel like you're a little bit in crisis mode all the time, right? Every metric that spikes triggers your little alarm bells inside your head, hey, we gotta go take care of this. And so, there's a few key problems that come up when you don't take the time to create that baseline.

So, first of all, every fluctuation feels urgent. I'm sure some of you have felt that way. When you feel that fluctuation happen, usually when it goes down. Often the context that's missing to distinguish between the normal variation and the real problems, everything feels urgent, everything feels a little more chaotic.

The next one is team… teams chase the noise, right? Resources may get pushed to go fix that initial problem that just pops up because you saw the number, and it could mean that you're diverting the resources to false alarms instead of addressing genuine issues, right? So… Again, the baseline allows you to say, is this really an urgent matter, or is it just data that usually is fluctuating?

And then finally, the last one we suggest is the gradual decline goes undetected. It kind of falls through the cracks. Without knowing what normal looks like, slow deterioration of that data sneaks past you unnoticed, ultimately leading to Poor quality of service, right? And so, grab a pen, grab a digital notepad, I want you to write this down.

Baselines are your anchor to objectivity.

Baselines are your anchor to objectivity. They remove the emotional reaction and panic. So set the baselines, because if you can't identify what's abnormal. you've defined what normal actually… until you've defined what normal actually looks like, or is. And so, it's foundational to making smarter decisions. By setting that baseline. Thank you, Brandon, for writing that out.

Alright, so number 2. And by the way, Brandon will plan to showcase more of this in just a minute, so hang tight, stay with us, because he's gonna actually dive in and demo how to set up that baseline, or, you know, study that baseline through the data you have. And then, set up these if-then type triggers.

So… That first step, once you take care of it, you now move to tracking the metrics that take… will give you the action, right? And we call them if-then triggers. This is a very common approach in operations in general. So if we take that example of the inspection score that we had in step number 1, we can suggest that we have a clear threshold, right? Our… our baseline is 89%. With triggers, you can say when it drops below that threshold for 2 weeks straight. You're not gonna debate on what you should do. If you've set it up and run through this process. You have an action to take care of it, so maybe a supervisor goes and retrains within 72 hours.

Let's take work order aging, for example. If you say, hey, we have more than 15% of our work orders that sit beyond 48 hours, it escalates to a regional manager, right? the response is predetermined. So if this happens, then this. So the magic, where it really functions well for you, is deciding the response before the problem happens. So you're not scrambling, you're not… holding meetings of what to do next. Literally, you're using the data that Otuvy gives you To define the triggers, That matter to the business, and then actually give you the… The outcome you're hoping to achieve when that trigger launches or hits. This is another one that you should write down. Speed comes from pre-decision. The moment a threshold is crossed, everyone already knows what happens next. That's how you move faster as an operation, is when your whole team knows, when this happens. Let's go do this thing. Right?

So that's step number two. Define if-then triggers. The final step? is adding operational context. The signals trigger investigation, But context is necessary before reacting.

One of my favorite books, by Stephen R. Covey, The 7 Habits of Highly Effective People. I have an actual little mini book. Funny story about this, I'll tell you about it later, you can ask me about it. I thought it was the legit book I was buying, and I got this mini-book in the mail. Anyway, I was like, what? It's miniature size. But I got the full book, read the full book, and in that book, one of the concepts that, Steven shares is that you seek first to understand Then to be understood.

So, let's take inspection comments, for example. You pull up Otuvy, you review what's actually been noted, you look at what categories have dropped after you saw the alert appear that, hey, this has dropped. That's gonna give you more detail into why that might be lower.

Think about work order volume. If you see a KPI alert drop or increase, maybe we have more work orders, right? Did work orders spike at that same time? Why would there be high volume? Can I understand, through the different historic areas of the solution, why performance might have dipped?

Something that you all go through. on a daily basis, I'm sure, is staffing changes and challenges. So, going into the system to understand, where did we shift that effort? Were there absences? Is there turnover during this period? Perhaps that led to that drop. And there could be local events to the buildings that you're managing or that you're servicing. And so, always checking with site managers, understanding the legitimate reasons, and creating processes that will give you this context through the inspection and work order processes that you've launched through Otuvy.

The bottom line is… if you have steps 1 and 2, you're gonna wanna use Otuvy to gather Step 3 context. Because if you gather that full picture through those inspections and work orders before escalating, it's gonna prevent the false alarms, it's going to help you actually be more productive in the conversation with the sites, the contacts at those sites, your team, and the customer, ultimately.

Which… Speaking of customers, That's where proactivity really plays a part. It's critical to lead the conversation, not just have conversations. Customers coming to you is reactive. You coming to customers, because you've set up operational signals. Let you lead the conversation. Lets you get ahead of issues before clients even notice them. Some of our best customers communicate early. They don't wait for performance to drop to then be attacked by a customer, right? They… they proactively and transparently communicate early. Showcase what's already been done, or what is happening. And then ultimately giving them that visibility, which a client expects these days. A client expects visibility. They want to know what's happening in their account. The transparency builds trust and strengthens relationships. So, be the one to control that narrative, and signals will help you do that. Signals shift you from reactive to proactive communication. Where you're no longer defending past performance, you're leading the conversation and demonstrating value.

So…

Let's talk about this, the manual side, the automating side, and then I'm gonna give it over to Brandon for the last 10 minutes of the webinar.

The manual monitoring of data involves four key tasks. You're gonna review inspection trends, you're gonna check work order completion and response times, you're gonna compare against those baselines, and then escalate when through the thresholds that you've set with those if-then KPI alerts. So, when you only have about 5 locations, it's totally doable to keep it manual. One person can usually manage that.

But, when you jump 20-plus locations, and the consistency begins to fall apart. You can't reliably track everything the same way across all sites. So, the framework I just gave you… Is and can be launched manually. But… Automation through operational intelligence will actually allow you to accomplish this better.

And so, when you add the Operational Intelligence Platinum dashboards to the automation side of this framework. It's not gonna change your strategy or the data sources. you're still using Otuvy inspections and work orders, but when you incorporate OI Platinum, you're gonna be able to customize more dashboards. Bren's gonna show you some things in a second. You can tailor the views to what matters most to the team. You can set KPI alerts, the if-thens that we just went over, to get notified immediately when metrics hit a certain threshold. there's quicker data refresh, so you're gonna see those trends and those KPI alerts hit sooner. And then, there's continuous monitoring and scheduling of those dashboards now. So you get that oversight, but you also can schedule those dashboard filters to be sent in an email through a PDF format to easily know what the level of value is through your quality data.

So the main point is, the real change is how you actually monitor the signals. Not what we monitor from just a data standpoint, logging in and seeing and hoping what's happening is right. The automation is actually going to reduce the lag between that collection of the data and the action you need to take to actually keep a customer satisfied and happy. So, plus it will eliminate a lot of the manual piece of what you may be doing.

So… How can you start today? Choose your top 3 operational metrics. Review 8 to 12 weeks of data. Define your normal range, create if-then triggers, and then standardize your responses. What do we do when this happens? I… Promise you, if you set up this framework and utilize OI Platinum as the automation piece, it will give you greater capability to understand Where the opportunities are to improve your service, ultimately helping your business grow, and your operation run a lot smoother. So, with that, Brandon? Let's go ahead and have you, share your screen.

Brandon:

Alright. Okay, can everyone see my screen?

Sam:

It's loading, there it is, yep, we're good.

Brandon:

Alright. So here is our dashboard. This is one of our standard dashboards. This is our inspections dashboard. We have, inspections for the last one year pulled up, or for the last calendar year. This is 2025 data. It looks a little bit Our data for our current year. But this… This is where you will go to find your baseline. This is the overview dashboard for inspections. We can also look at the overview dashboard for, work orders.

We can see the response time trends, completion trends, percentage of open versus filed and closed. for a lot of different data points. And this is where you're going to go, you can set it for different time frames, client by client, location by location. Or even inspector by inspector for this information. You can also see us side by side, if we go to the inspections and work orders dashboard.

And these are standard dashboards that are available to everyone, whether they have OI Core or OI Platinum. The great thing about having them side-by-side here is that gives you that context. You may have inspection scores dipping, but you have work orders increasing at the same time. That will tell you that, okay, yes, we had more stuff to do, we took care of more things, but that means our average quality was a little bit lower.

That gives you that insight that you need.

So, once you've grabbed that baseline data. You know what your average expectation is. Maybe you're below what is expected, maybe you're already overachieving. you know where you currently are. And then you can set those, those, targets for what to do when X happens.

For example, let's say if our average inspection score dips below 90% for a given time frame, let's say 2 weeks. We need to retrain or investigate, see what's going on.

If it goes above 95%, Do we need to investigate and make sure things are accurate? And if they are accurate, take Celebratory… you know, celebratory… Action then, you know? Congratulate someone on a job well done for being consistent at that job well done.

So, in either direction, you can set things up internally to your process, but again, this is a manual process if you don't have OY Platinum. You can look at the data here and do that on a periodic basis. You can download your PDFs. And get all that data just… just like normal. But when you have OI Platinum, you have the ability to set up… individual KPI alerts, so if it crosses a certain threshold, it sends out an email. Notifying you that this has happened, and you can also set,

custom… message, so let's say the, average score… Less than 90%, so that's gonna be 0.9, because we're dealing with percentages. You can see the current value is 0.911. So if it drops below 0.9, I want to send out an email. additional instructions. Go and check in on… processes.

Sam:

It's that… that action after the alert, being able to easily notify the people that See this number that, hey, it's dropped, here's what we're gonna do about it, right?

Brandon:

Exactly. Now, this will just send information about this one KPI, so it doesn't send the full big picture, but I'll get to that in a little bit. You can also manage the recipients. They do not need to be OI user, or a QM user. They don't need to be an Otuvy user. You can put anyone who needs to be kept in the loop about this KPI.

Now, it does populate with a bunch of users that you can choose from, but you can also put anyone's email address in there to send it to them. And then you can create that alert. Periodically, the system will keep watch on that, and if it does dip below that threshold, it's going to automatically, instantaneously send out that alert. Triggering some action from you and your team.

It doesn't give us the whole picture. It doesn't give us that context. So, what we do is we're going to, let's say, send out a daily report. if… that dipped below that 90%. So it's only going to send out the entire dashboard, which gives us that context. If it dips below that threshold. The first thing we need to do is we need to set a, a… view. We need a set of view on this dashboard. Now, this does require OI Platinum as well, so… well, I mean, you can save views, but the reporting feature requires OI Platinum. So I'm going to set this view to be a rolling 2 weeks, so I'm going to say this is going to happen on or after the last

14 days. So that's gonna include today, As well as the last 14 days. Apply that. I'm gonna save this view.

This is… I've labeled this view everything for 14 days. I'm gonna make this… Alright, I'm gonna save this. I'm going to, the reason why I said everything is because I didn't filter this down to individual clients, or locations, or inspectors, or authors of the work orders. This is just showing me all the data across my organization for the last 14 days. I'm going to go over here, and I'm going to create a schedule.

Now, in here, I can schedule this to happen… Every… day, every hour, every 5 minutes, right? However frequently I need it to go out.

I can say it's gonna send out every morning at… 7 AM. I'm going to include weekends by turning that off, that's gonna be… Denver time. And I can add a gating condition, because I don't want it every single day, that's going to get noisy, it's going to be lost in the shuffle of things, I'm going to start ignoring it. I only want it to happen when

That average score dips below my threshold. That is my triggering condition. So, average… detail… no, average inspection score, percentage. There is a little bit of understanding of what these different data points are, so if you have questions, reach out to us, and we can help walk you through it.

So the average inspection score is the average full inspection score. The average detail score is individual. details. So, if you want to, you could say, well, the average detail score for an individual detail dips below that threshold, I want to be notified immediately for every single detail. that's a little too noisy. So, for me, I'm gonna go average inspection score percentage, less than…

0.9. That's the 90%. It says the formula is ready to save. So, I'm gonna go down through the rest of this and set what kind of attachment I want, whether that's PDF, Excel, or a CSV. If it's a PDF, I have some advanced PDF settings that I can select from, whether it's the entire dashboard, individual tabs on that dashboard. If I have created a custom dashboard with multiple tabs. I can also do individual visualizations, those are those individual dashlets, so I have the right context in that email and nothing else. Get rid of all the noise.

In this case, I'm gonna just select Dashboard. I'm gonna leave it as landscape format instead of portrait. Because I've got a lot of data in here.

If I wanted to, I could add a note in the footer. And again, selecting recipients. They could be… QM users, they don't need to be QM users, just put their email address in there. If they are a QM user, and you put their email address in here, the data that gets sent to them will be pared down to only that data that they can see for locations that they can see. It'll still have this information… Or this frequency, it'll still have the triggering event, they'll still get that email, but it'll only see data… they'll only see data that they would be able to see if they logged in. And then… everything for 14 days is the view that I just created, so I'm going to select that as the select view. Or I could just have the original dashboard. I only want to be looking at a rolling 14 days every single day, so that it'll send me that alert.

And then I can create that. And then tomorrow morning, at 7 AM, if that triggering event is true. That our average score for the last 14 days dipped below 90%. it will send an email to Sam.

Sam:

Awesome. Brandon, thank you so much for showcasing that. Again, the steps of… Figuring out what normal looks like, what's the fluctuation, and then… developing these if-thens through features that you can custom create and build through the KPI alerts, the scheduling of those reports, as well as the Customized Dashboard Builder. Coupled with our AI function now that can help you generate those… those dashlets. Saving those views, those are all ways that you're gonna be able to automate the flow of… the actual… what normal looks like, and then when we should actually take action. Again, it's about taking the data and turning it into actionable data. And the way you do that is through those if-then triggers, and then getting the context from the use of the software. So we really appreciate the time today. I'm looking at the… I'm looking at the Q&A. I don't see any queue or questions that have risen. If you do have a question and the webinar ends, you can reach out to our team, whether you're inquiring about how to set these things up for your current subscription that may include OI Platinum, or if you are on OI Core or don't have the dashboards yet and want to add it. All you need to do is email us, vip@otuvy.com. And it will be routed to the appropriate person based on your request. And we would love to help you get rolling into turning, potentially, your reactive data into a proactive set of data through these KPI alerts and other functions that come with OI Platinum. So thanks so much, everybody, for joining our webinar today. We're gonna be doing a few more here in the future, but we really appreciate you all for partnering with Otuvy, being Otuvy customers. Have a great rest of your day and week, and let us know if you have any questions by emailing us, vip@otuvy.com. Have a good one, everyone. Bye.