Transforming Asset Data Chaos: Five Steps to Proactive Data Cleaning

Welcome to our webinar this afternoon. For those of you who have never met me, my name is Robin. I'm a senior services consultant based in New South Wales here at Brightley. I've been in asset management for about eighteen and a half years, and I'm primarily focused on the confirmed system, but I do also work with aesthetic on occasion. With me is, Rebecca Harris, who's also a senior services consult with over a decade of asset management experience. Becky focuses on confirmed in Victoria, but like me, she's also a woman of many systems and works with our predictor solution, when the workload, demands it. I think there's a slight lag with the slide, so I'm just gonna give that a couple of, seconds. Okay. So for this webinar, we're going focus on how using data cleaning principles in your asset management system with a longer view of the data and its potential issues. Can offer an overall improvement to the quality and completeness of the data and save you valuable time, money, and resources when it comes to utilizing that data for larger projects. We're going to do this by focusing on the issues that you're probably already aware of. Some of which you might already have halfway, solved, you know, temporarily solved. So if you happen to be a confirm or an aesthetic user, all of this can be achieved using the tools and resources and functionality that you already have. And ideally, we'll be leaving you with plenty of tips and solid methods on creating a less stress simpler and more proactive approach to data quality So I'm gonna start by talking about some of the typical issues that are faced by local governments. This felt a bit like, family feud when we were pulling this information together. You know, we surveyed a hundred people. The typical data issues are we didn't survey a hundred people. What we did is go through all of the problems we've helped solve over the last few years when our customers are performing valuations in the financial year exercises carrying out that kind of long term planning and doing some of their larger asset projects and the sorts of activities that cycle around every year, and we came up with six of the most common issues that are faced by local governments at the moment. So the first one I'm gonna talk about is incomplete data. So incomplete data is most often caused when asset data has been entered into the system because we know there is an asset there. So we need to put it in there. We know the entry is valid and necessary. But we don't know all of the correct details about it. By the time we notice it's been too long and we don't know what we can't remember who to ask all of the immediate knowledge about that asset has gone stale. And then by the time we notice that it's incomplete, we've got a big project on the go it's become urgent and we're running out of time, to find those details. The second thing that quite often goes hand in hand with incomplete data is mismatched to data. So this example encompasses things like finding a gravel road asset with a material type of asphalt, for example, or perhaps a light pole with a gear type that that particular type of light pole would never support. They just wouldn't be able to go together. Mismatched data causes mismatched actions. You know, is the light pole correct? Is the gear type correct? We don't know which one is right. We possibly don't know what sort of maintenance should apply to the asset. It can get caught up in the wrong kind of reports. It can get caught up in the wrong kind of inspections that then builds problem or top of problem into our long term planning. If we're using data extracts to run through a planning system or any sort of, you know, homegrown algorithm. We could potentially end up with skewed results and then that has knock on effects to our budgeting as well. So that can be quite a quite a serious issue. The next thing I wanna talk about is out of date data. This is where, you know, the data is complete, and we know it was accurate once. But now it's still an out of date and we don't really have confidence in it. This can be the result of data collection exercises that were carried out for a specific project. Data collection, you know, takes a long time. And then as soon as it's been used, we move on to the next big project and it sits and goes stale There's no upkeep carried out because we've moved on to that next big thing and we're busy. Right? So the data is used once and then left to go to waste. And the next time we want to do anything with those assets, the data is out of date again, and we need to repeat the whole data collection process. Which again is expensive, as I've already said, takes ages, then we use it, then it's left to go around and sit about and go stale. And around and around we go in that cycle over and over again. So the next thing I'm gonna talk about is overwhelming issues. The problems here aren't massive, but they are just so many of them. This is actually the biggest issue that was told to us by customers that was given to us to help deal with. And the problems that we have with the data here tend not to be big show stopping ones, but there are just so many of them, and it becomes overwhelming. We can't categorize the issues properly we can't sort them from each other and we have so many small little things to deal with that prioritization then becomes too hard. We end up with a massive backlog that we can't keep track of, what individually isn't show stopping groups together and becomes a huge block. And completely show stopping. Now, however many of those problems we solve we then have the problem of reoccurrence to deal with. This is where we've identified issues. We've fixed them but things fall through the cracks, right? So they reoccur. And the thing with this is it starts very small, it starts sneaking in over time. And then all of a sudden you realize you've got a big reoccurrence of the same issue without anyone noticing until it becomes, a really big that's gonna stop your project from moving forward. If we've already solved this problem once, what we end up doing is a lot of time, effort, and money, solving it a second or sometimes even a third time. Now, the last thing I'm going to talk about here is data cleansing and collection. I've put these two together because they so often do go hand in hand. Some people might look at the first five issues here and say, well, number six is actually a solution to those problems. Well, cleansing and collection can also be an issue on its own. Yeah, money is a focus for local government every day, but we don't often like to talk about money. But if we're using cleansing and collection as solutions to any of first five issues more often than not that involves spending a lot of money. Data collection is really expensive, and we have to balance those budgets every single year. And it also takes a long time. So it's expensive in resources and time as well. If we're having fresh data collect before a large project and sometimes before small ones too, usually a large amount of data cleansing has to take So we then do a data cleansing exercise. We give the data collection people the extract of our assets when we're finished. They collect them. We can finally get on with the long term planning project or, you know, whatever work we had planned. Data cleansing in this case becomes a project in its own right, and then the collection project takes place. The whole thing, time, money, delay the start of planned activity. So where we thought we had one project, we end up with three or four all stacked up and taking time and effort that we couldn't really afford. Now all the while that's going along, and neglected day to day workload is just sitting there because we're having to concentrate on all of those other things. Our day to day tasks have to be put to one side and just pile up while we're concentrating on the cleansing and causing even more of the issues that we've already talked about to to stack up and cycle around. So before I carry on, I've just got a little poll question here. So if everybody could, grab their their mouse, before we move on and see if you can tell me how much you have in your current data. You should be able to just click on that now that it's up on the screen. I've got my timer on. I'm gonna give everyone about forty five seconds to answer that and so you've got a couple more a couple more seconds if you need it. Okay. So I'm gonna move on to the next one now. Let's have a look. So we can see that there's quite a bit of confidence there, which is really nice, but there are a few people out there who don't have a huge amount of confidence in their data. So what we're gonna talk about then is, well, Alright. I've said I don't have much confidence in my data. What do we do about that? We've looked at the problems. How do we solve it? What the way we're gonna solve this today is by taking a long term view of our data. And to do that, we need to stop data cleansing, and we need to start data cleaning. And that's my main topic of today. The huge difference really between cleansing and cleaning is that we're data cleansing We have a specific project for a specific purpose. You know, I am cleansing this limited asset set because I have a specific project you take that targeted focus on a very small area of your asset register, but for the whole of those assets. It's very short term, and it comes with all of the issues we've just been talking about. It costs time, it costs effort. It causes day to day workloads to be neglected. It's great for five minutes, and then the data goes stale, especially if no one is keeping an eye on the new assets that are coming into the system. After the project is is completed. With data cleaning, you swap those middle two points around. So we take a whole of asset registered view but we think about the specific issues that we are having, and we do it long term for just a few minutes every day, not just when we have, a specific project coming up. We do it all of the time. And the benefits of that are that when we get that specific project, either, you know, one of those special things that comes along that we have to do or an end of financial year or evaluation situation or so on and so forth. The kind of activities that cycle around every year. We end up doing less time and effort to clean up any issues that we find. Because we've been quietly and consistently chipping away at the entire time. So how can we achieve this? So I've put here We've done this with a couple of customers now and we've distilled it down into five steps, five steps to set everything up. And then once you're up and running, it's five minutes a day to carry it out. Okay? Now I know we've all been promised a flatter stomach and bringing abs in five minutes a day, and we bought that thing off the TV and at best, it went rusty in the garage. Potentially after being used as a clothes horse for a while. But I'm not that woman who can't open a simple milk button. And Becky is not that woman who can't just put slightly less food in the plastic container. We're not selling anything here. So do you remember when I said at the beginning, if you've got one of our asset management solutions, you've already got the tools and the functionality to make happen without spending any money. All that you need from me is a couple of ideas and a few tips to help make work, and then a bit of a demo from Becky to see how it, actually can work in a real sense. So the five steps, that's all we need. If you follow the five, you're gonna end up with a fair amount of data freedom, in this. So let's talk about what the five steps are. So first things first, get everyone on board. Ideally, this is a group situation for both the identification of the issues that you're gonna solve and for the solutions that you're gonna come up with. If you don't have everyone involved, then you're not gonna get a good outcome. This is simple change management principles really. Remember we're talking about following five steps to set this up and then only five minutes a day to carry it out. Then much further down the line, it's gonna save people hours and hours of pain because we're not gonna do all of the solutions flat out the two weeks before the end of the financial year. We're gonna do this every day for the ten months before the end of the financial year. For example, So it's much, much easier. So get everyone on board, sell that idea and get their inputs. The other side of this is, you know, that input at the beginning they're gonna feel ownership. And when it comes to spending that five minutes a day, they're gonna be much more likely to make it part of their routine every day if they've been involved right from the get going. The second one is probably the most important one, and I think if you came to illuminate last year, twenty twenty two. You'll have heard Becky speak about this. Stop trying to make it perfect. Perfect data is the enemy of good data We have to stop aiming for perfect data because it's getting in the way of us having good data and it's getting in the way of us getting things done. It's a bit like, you know, when I try and do my hair in the morning, if I strive for protection, I'm gonna spend the entire day feeling very disappointed, and I'm be and, never be, satisfied with the results. At a certain point, you have to say good enough. Let's move on. Good data is really important when you're looking for good results. And the only way we can get good data is to let go of the idea of perfect. Okay. Now on to more practical things, it's time to make the issue list and give each issue a priority. So this is step three. If we've managed to let go of the idea of perfect, what we then have to decide are what the issues are and what the priority of those issues should be in order to make your data good. The way we did this, for most of the customers we've worked with on this so far is to go back through our last end of financial year, our last set of evaluations, our last big data cleansing project, and make a list of all of the choose we had with the data. So this might be a really, really long list or it might be a really short list. It doesn't matter. If there was a problem in the data, if there was something there, just write it down on the list. Make a list of every single problem you can remember from those last few projects that involved your asset data. And then prioritize it. This is the bit where having everyone involved is important because what I might think is important and what holds me back every day might not be the same thing that holds Becky back every day and that she's used as important and causes her pain. So have a big get together with biscuits that really important and prioritize the list. Sometimes we have to think about prioritizing what's important to us as an organization and to us for the specific project we know might be coming up in eighteen months time. It's not just for us. We have to, you know, make sure we include the needs of stakeholders above and below us. When you choose your priorities, they're not set in stone. Make them for now you might aim to solve the top five big four now issues, and they can change and be added to over time. And I'm gonna come to that in a short while. So it's step four is I have to now decide how we're going to report the sets that are affected by each issue. So I have to make decisions about whether each problem is better reported on a dashboard or reported on an automated email or a data extract to a network folder and so on and so forth. Different data cleaning problems might need to go to different people within the organization. So I might decide that assets with a missing footpath length should go to Becky and she prefers a dashboard. But I'm going to tackle the assets with mismatched light poles and gearing, and I prefer a straight data dump to a network drive so I can get stuck in. So you might end up with several different reporting methods that send out several different issues to different people. For the non system users, a little PDF in their inbox each morning, you know, listing the three assets that I need some extra information about might be best for them. So be prepared to take responsibility for populating the system with data for those non system users. It's all about the system you've got being versatile enough to let everyone work how they're comfortable and confirm and aesthetic are absolutely best of breed at that. I do favor the dashboard as an overall master controller suggest you absolutely make a dashboard as your overall master control because it's so simple to use. It delivers everything straight to you and it's very visual. I can very quickly see if I look at a dashboard if the issues are building up again or if we are solving them if they're if they're moving downwards. Step five is absolutely critical, automate it, automate everything. This will ensure that nothing falls through the cracks. The dashboards in our two systems confirm an aesthetic are already automatically refreshing on a timetable that we choose. But every report, every data extract, every email about a missing footpath length needs to be automated so that you can just set it up and then concentrate on finding the your five minutes a day is all about finding those answers. Then also stick a priority one untouchable appointment in your diary every day. For your five minutes and automate that as well. That's it. That's our whole five steps. That's what you need. I also though have secret step number six because this is a cycle. We have to make sure that once we've set this up, we do put aside a little bit of time to shine it, design it, and refine it. If you identify extra of investigation once you're up and running. Just add them in. Just add them in and then spend five minutes a day on them. Now the key takeaway to all of this that I keep harping on about and I will harp on about it forever is that with confirmed aesthetic you already have all of the tools that you need to achieve this. This is also true with other systems as well. If you are not a confirm or aesthetic customer yet, and you've got an asset management system and something like Power BI or even good old crystal reports, then you also have all of the tools you need to do this. This is all about don't reach for the shiny new toy that promises to solve all of your problems This is about use the resources around you to their fullest extent. So before we move on, I've got another poll quest who amongst us already utilizes dashboards and custom custom reporting to monitor your So you might use it to monitor jobs, you might use it to monitor your inquiries, you might use it to already monitor some of your data quality. They'll set my little timer for forty five seconds again. Okay, so let's have a look. So half of you already, that's out standing. So half of you are already utilizing some of the tools that you can then adapt to do all of the things that I'm suggesting here. That's brilliant. So this is the aesthetic dashboard. So for those of you who aren't using dashboards at the moment and are aesthetic users, this is the aesthetic dashboard right here. Both systems do include, as I've said before, configurable dashboards and reports. It's very, very easy to start identifying some of the issues that we've talked about today. And the kinds of issues that you would be putting on your lists. You can see the aesthetic dashboard has got a range of ways to play the data. We've got pie charts. We've got bar charts. We've got data extracts there. And it's very configurable to me. So I can see just the stuff that I'm interested in because this is my dashboard. Okay? And when I'm ready, I can start drilling in this dashboard here to the data on this one. And this is just a simple report of, pipes that don't have a length. So I might send a couple of emails right now to go and find out the length of the pipes. And then what I'm gonna do is I'm gonna come and drill down even further. I'm gonna fill that in. Christian gave me these screenshots and he highlighted for me the bits. I was interested in. And when I'm ready, I've filled those in, and then the thing is now that asset will disappear from that data extract. It's no longer a pipe with a missing length. So with a dashboard, this is where I advocate for dashboards so much. I'm only ever looking at the data that I actually need to react do. Along with this, we have some report templates that we can set up. This is quite an old confirmed porting template. Okay? And this is one that tells me I've got features that haven't been inspected properly. This has been created using the confirm report writing tool called Data Minor. Confirm reports can be configured in data miner and then scheduled using the report scheduling. So again, just like a dashboard, I can automate this to be sent out at required intervals so daily, weekly, you know, whatever I want to a distribution list, or I can have this as a data dump exported onto a network drive. To be accessed from there. You can easily adapt this for a data cleansing purpose. You know, instead of features that aren't inspected in an allocated month, I can have my, you know, my CSB of all of the pipes that don't have an appropriate length. It's very, very easy to set off. It's very, very easy to start using. So what I'm gonna do is I'm gonna stop talking and I'm gonna hand over to Becky and she's gonna give us a bit of a live demonstration of how confirmed can be used in a dashboard driven way to clean your data. Cool. Thank you very much, Robin. So I'll stand by for a very smooth transition. Just wait for that to come through. I was like, oh, there we go. Brilliant. Okay. Yep. So thanks for that, Robin. As Robin has already said, you already have all the tools you need to kick start this process. So what I'm now displaying is a simple dashboard that can be used to help me monitor my data. It's essentially a digital to do list. And it will update in real time as I work through it. So I've chosen to keep this as a completely separate dashboard. As I don't want to be looking at it, when I'm completing my day to day work. It would just be like a dark cloud hanging over my head waiting for me to action it. I want to be able to drop in and out of this, when I have a there five minutes. So the dashboard I've got set up monitors several different asset classes and looks specifically for my problem areas. As Laura mentioned, if you already know where the problems lie within your data, then that's a good, first step or it's a good third step when you're creating a list of, problems and priorities. And you can then choose to present that information on an easy to use dash board much like this one. You can also make that dashboard available to any colleagues you may be asset owners, and you can of course work through that data together. You'll notice my dashboard is specifically looking at where I'm missing information regarding valuation data. So I've got several, widgets on here, and they're looking for things like, assets that I've never been valued or assets that have this year. Assets that have no active from or active to dates, assets that have exceeded their useful life in the system. Assets of no category, and of course, assets of no replacement cost or valuation quantity. All of that missing data will cause any problems when I come to undertake my end of financial year valuations exercises. You, of course, can start your dashboard to show anything you need. For example, you may have an asset class that requires a specific attribute. So on your dashboard, you will show all assets that are missing a value for that attribute. And of course, as Robert mentioned, as well, mismatch data, you can present that on a dashboard to, sort of showing you anything you need to, validate and check. You can display in kind of any sort of form you want, sort of, bar charts and things like that. I've got mine on, so a mixture of bar charts, column grass, and of course a couple of pie charts to make it look pretty. You can also, of course, present that information on a map if you so choose. So I'm gonna zoom into my data here, so better if I forget closer in so we can see a bit better. So as you can see, I have a large number of assets with no active from date. So they're displayed here in my columns. Mine are separated out by asset groups. So I can click into a column to drill down to the data behind this. So it's now showing me I've got four that are missing, active from dates within the bridge feature group. So I can open up all of those, records at once. Which will allow me to navigate through them using the navigation buttons at the top and I can flick through. So now depending on how I have my data set up when I first went live in my asset system, I may have utilized the asset start date, and that could be my, year of construction. I could have also recorded that information as an attribute with some construction date information in there. So to update this data, I've already got it in the system. So I can click on to my valuation tab. I'm gonna say that my start date is my construction date. I've verified that's true. So all I'm going to do is use that start date and populate my active firm date down here. So there is type that in. And you'll notice that as soon as I, move out of that field, it has also automatically populated my active to date. So that is, of course, based on background rules in the system, looking at the useful life for my asset category for, my bridge here. And I can save that and move on. So I'm essentially killing two birds of one stone here. I'm populating two missing filter data with one action. Of course, I can then move on to the next record and fill in the next day. And it's really that quick, simple. I see as I go here. And in that short save the time, I've now updated, four records. So you see how quick that was for me. And there we go. So, I populated four records well at once, and, As I as I go through, you'll notice that it's very quick to do. I will say try not to get too stuck into it though as it can become weirdly addictive. And you could lose more time in here than you want to. So set that timer. Five minutes a day is really good, as a starting point. So once I filled in that set, I can close out here and close down this one as well. Now I can choose to open up another section here, start populating those as well. Or of course if I finish my asset, updating exercise for the day, I'll then move on to my day to day tasks. Alternately, I could also use some of Confirm's batch updating methods to update this data So as Robin was saying, we can put it in a data dump. I can also, you know, select this data out of this system here and save it as, a spreadsheet. Using the copy button or the save, save button. And I can use that and work through that data in a spreadsheet format if that's something I prefer. And then import the information back back in. So as you can see, data cleaning can be a really quick and easy task. That we complete in small batches. And so that means that over time our asset data will gradually improve, and we'll be in a better position, when we actually want to use it. So you won't have that, sort of big panic and quick sprint towards an unobtainable deadline, and when we're trying to update all of our data at once, we can work through this methodically, and to have clean data for when we need to use it. These dashboards are also available in the web formats. So that means that you can share them with some upper management really easily. And you can send them a link and say, Hey, look, look how good I'm doing at cleaning the data. The how clean our data is, and I'm sure they'll be really impressed with your proactiveness. Obviously, some asset data will require more interment intervention. And potentially some data gathering as well. But at least this way, you will have visibility of it, and you can manage it within your tasks, accordingly. So as long as you've got visibility, you know it's there to do. It's not gonna get lost in that big pile of, oh, yeah. I'll get around to it at some point. So yeah, too easy, right? There we go. Hand back to you now, Lauren. Thanks, Beck. That was awesome. And so you can see there that confirm can really be used in a dashboard driven way, a set it can be used in the same dashboard driven way, to really start making a day in some of those issues well ahead of time, where they're going to actually make, a huge dent in your project. So I'm just gonna sum up real quickly. You know, it's five steps for setting this up and then five minutes a day. So go and get everyone on board talk them into letting go of perfection. It's a useless concept anyway. It's like when people say that's not normal. Normal is a useless concept. Make your list and prioritize your issues. Decide the best method of delivery for each one of those issues. Don't just execute the plan, automate the plan, and then don't forget secret, super secret special step number six which is when you finished, make sure you refine it, shine it and redesign it because this is a cycle. Okay? It's a cycle. And the most important thing to remember about today is that you already have all of the tools you need to achieve this. So with that in mind, can I just ask again, who intends to put some of these tips into action? Okay. I'm just gonna move this slide on. That's amazing. Ninety six percent of you think that and I have not bored you to tears today. I'm really impressed. Thank you so much for that. That's amazing. So with that then, does anybody have any, questions that they would like to ask? We've had a few dropped into the chat already. Okay. Hang on. So can I know more about the tools you are using? Is it part of Riley? So thank you, Matt, for that question. That's a really good question. Yes. So if you are a confirmed user or if you're using setting, then yes, you have the tools already. They are the standard dashboards and report writing tools that are part of your software. And if you need to know a bit more about them, if you don't know where to find them, get in touch with us, get in touch with your account manager, book some time with one of us, and we can talk you through finding those without any problems at all. Yes. We're quite happy for you to have a copy of the presentation. That's absolutely fine. No worries at all. And there's a question about using a discrepancy data source. So, Yes. If you have confirmed, you can use a discrepancy data source. It works in a similar way to the dashboard, with a validation process. The idea of being you have a set of rules set up against your asset group, and then you validate your asset against those rules, and it gets a time and date stamp. So this asset been validated and matches the rules at this time validated by this individual. So, yeah, that's also a really good idea of making sure your asset data is, completely today. Correct? Perfect. I've got a question from Jeff House here. Are we aware of any AI type tool to clean some of the issues, rather than manual methods. So at the moment, yes, we are aware of AI tools that can do this sort of thing. There are currently none included in aesthetic or confirm as systems. But, hey, get on the suggestion portal because I'm absolutely up for that. That sounds brilliant. At the moment to use the tools that we've been talking about here, it would involve a manual update either via manually populating the data importing the data or using some of the batch update tools in both systems. So question from Scott here. So is there a logical way to capture information about a field I e the age or construction date of the asset that has estimated calculated versus actual. So Scott, that goes down to how confident are you in your data and how collected originally. Obviously, if your record keeping over the years has not been completely accurate, is gonna involve, some manual exercise of, you know, data gathering to ensure that your data in the system is correct. Logical way going forward would would be to have a great, asset handler process and capture process to make sure you are sort of keeping track of your renewals and your updates and your maintenance and things like that. Yeah. Okay. I'm gonna answer two questions at once here. Is it possible for Bradley to show us how to create dashboards? Is there kind of training? Other than online knowledge base and are the standard suite of admin cleaning dashboards available that Becky was demonstrating. So I'm gonna answer them both together. Yes, for both systems we can do, reporting and dashboard training. That's absolutely no problem at all. Get in touch with your, account manager book yourself in with one of us, we can do some standardized, reporting and dashboard training, or we can do some specialize towards what we've been talking about today or what your personal needs are for dashboards and reporting. And, the other thing is we don't have a standard dashboard for this that we can give you. However, the stuff that we've demonstrated today, we can lend it to you for inspiration. I think that's probably the best way to put that. Oh, I've missed a question. I'm so sorry, Claire. You've asked if we have a service agreement with Brytely, would this be covered under that agreement? So your service agreement with Brytely, the tools that you have are already there. If you're a confirm or an aesthetic user, then you already have dashboards. They're already included in the software that you have, depending on what it says in your service agreement about providing services or providing training, it may or may not be covered. So get in touch with your account manager and have a chat about that. That's my best advice there. Okay. I think we've about covered of all of the questions there. I'll leave it open just for another minute or so just to let everybody that hasn't asked a question there. Anybody that wants to can can put a question in there for us? Oh, our standard dashboard training for Confirm is a day, and our dashboard training for aesthetic, I believe, is half a day. It is included in your system admin training, I believe, so you should, have hopefully someone on-site who's already had the training. So it might be time to seek out who's got that knowledge and, make best friends with them at this point. So Scott to answer your question. Yeah. Oh, go on. You're gonna take it. I was gonna say Scott, so Canada dashboards reflect data from external sources. The data would have to be put in to confirm for it to be able play on the confirmed dashboards. And just a thank you to anybody who's dropped a compliment into the chat there. That's really appreciated. We don't have any more questions popping up. So from here, it's just my job to say thank you so much from Becky and I. Thank you so much for coming everyone. I do hope you enjoyed this session. Please feel free to contact, your account manager, get in contact with Becky or I if you wanna discuss this further, that's absolutely great. We'd love to talk about this with you. And, as I say, I do hope you enjoy this session, and I do hope you enjoy the rest of the afternoon. Thank you so much. Thanks guys. Bradley.