KPIs and Natural Language for Construction Companies

Alrighty, let's get started. Good morning or good afternoon everyone. Thanks for joining us. My name is Johnny Girardi, I'm Data Sales founder and CEO. I really appreciate taking the time in this crazy times to join us. Let's jump right into the session. Today we're doing a webinar focused on the construction industry in how natural language, AI and analytics can help construction businesses. Let me go over to the next slide. When people come, when construction company come to Dataself, these are some of the challenges that we hear that we usually can address from a very high level perspective is management. You know, many management complaining that they are flying blind. They have very little visibility into the data in their erp, in their data silos and it's usually slow and complex that get data into their decision making process. So very common people saying flying blind. On the IT side, the people who support decision makers, typically the main challenges are they say that reporting, dashboarding, helping decision makers be more informed becomes a complex and time consuming job. It's kind of always trying to keep up with the requests from management. So these are kind of very high level complaints from IT business analysts or consultants supporting these construction companies. More specifically, the areas that we have been building analytics solutions around is to analyze projects, different perspectives from projects, receivables. Some of these construction companies being on top of receivables are critical. So it's another big area, cash flow. Cash flow is important for everyone. Construction, no difference in financials, also P and L balance sheet, things of that nature. Some of the interesting things happening lately in the market is there's a lot of construction, legacy systems out there, you know, construction systems that were designed in the 90s or 80s, you know, long time ago. And there's a lot of companies, construction companies now moving to more modern, usually cloud based construction systems and being able to bring legacy data from the old system in analyzing projects. You know, sometimes projects go across multiple years and when they, they transition from the legacy system to the new ERP system, they don't want to lose the history for analysis purposes. And that can become an issue on the reporting side. And dataself has been helping some of these companies address those issues. So today my webinar, I'll touch a little bit of distant topics. If you have questions or comments as I go through the webinar, you can make notes or use a zoom chatting box to start putting your questions in. At the end of the webinar I'll spend a few minutes to address those questions. All right, so let's move along and from a very high level, the technology behind the scenes, how Data Self does its magic. We've been working, we've been doing business for about 15 years. We started the business in 2005. And the main value of Data Self is bringing technology, analytics technology that is usually available for Fortune 2000 companies. Make it simple, make it easy, make it affordable for company in the mid market to take advantage of that amazingly powerful analytics platform. In a nutshell, we use real enterprise data warehousing, but it's super simple, super fast to deploy, yet very powerful. So we use data warehousing behind the scenes, can be on premises, can be in the cloud. We also use analytics tools, very successful analytics tools out there. You know, tableau Power, bi, Excel. And at the end of the day decision makers will be able to access the reports and dashboards anytime, anywhere using any kind of device. You know, Windows computers, Mac computers, mobile devices like phones and tablets. Anyhow, I'm not going to go into the technical details, but this is technology available for Fortune 2000. Just make easy and simple for mid sized companies and affordable. By the way on the front end we have a lot of reports and dashboards out of the box and in my presentation today I'm going to show some of them and how easy it is to modify and customize them a little bit. So I'll talk about that later. At the end of the day, what are the main benefits of Data Self? Obviously for decision makers instead of flying blind, is easy access to their key performance indicators instantly, accurately, anytime and anywhere. And with our natural language and framework, decision makers can make a lot of changes in their analytics platform without calling others, without calling the consultants, without calling the business analysts. There's a lot of power that this technology gives to known techies to become more self sufficient when it comes to have insights from their data. For the IT side of the business, you know, people who support the decision makers, the data itself, it's simple to set up, it's easy to maintain and typically it automates a lot of the tasks that typically people have to do manually. You know, export Excel, manipulate, transform, distribute reports. A lot of the mechanical parts of reporting dashboarding, Data Self can automate so it becomes a lot more more efficient, the IT work become more efficient. Let's take a look at the product. So let's jump right into it. All right, actually let me go to the demo platform. I'm going to show a few different things in this presentation and keep in mind that this is actually our first ever webinars specifically for construction. We have a lot of clients in construction, but from a webinar standpoint is the first time. So our goal is as we move forward to have this webinar recurring and have the content better. So if you have recommendations later for us to skip things or focus on things, I would appreciate the feedback. Anyhow, I'm going to start the product presentation in the area that is focused on decision makers and for them being able to do ad hoc analysis without calling anyone else. And usually this part of the business or part of the technology is when we use natural language in artificial intelligence to help the process. Natural language query is what I'm going to be showing you is similar to searching the Internet like Google or Bing. A person types in a question or a sentence. The tool will interpret what the person wrote. And instead of giving articles and blogs and whatnot, the tool builds a report on the fly with the answer to that question. So I'm going to show some examples here. Let's see. I want to see revenues by year. So I type just revenues by year. The tool will look at the data model, which in this case is very simple. And we'll try to find something that matches that question. In this case, sum of revenue by transaction date, year, year. Yes, that's what I want. Sometimes you might have many hits here you, you pick the right one. Once you click on it, the tool will build an instant accurate answer to that question. If the question is correct, is well articulated. If the tool find the data points, the answer is instant, accurately and is built on the fly. So this example by year we have revenues. So just showing like a line chart. That's it kind of magic, you know, ask a question, get an answer. Sometimes people want to see information on a tabular format, not on a chart. It's very easy to come over here and tell the tool show me this information in a different format like in this case text table. And now the tool shows the numbers on the text table. Let me show two more examples of natural language. What if you want to see revenues by customer. So another question and the found revenue customer I selected and in this case shows my customers and revenues in a descending order. Maybe on a breakdown by project. You know, every customer might have more than a project. So sure, by project. So again the tool find the answer. In this case only one is selected. And now by customer, by project issue my revenues. Natural language query looks like magic. It's not, but many times feels like magic. Because people like on the Internet, they ask questions in the tool Just answers it instantly inaccurately. Part of the journey with natural language is get users to think properly how to articulate the questions. Like just searching the Internet. If you don't know how to articulate the questions, usually don't find the articles. If you know how to articulate with Google you find a lot of articles. This is similar and this is not for more elaborate reporting. Usually elaborate reporting you use the report designer in Dataself using data warehousing techniques and then you can build very sophisticated or very simple reports using the report editor. Anyhow. So this natural language and artificial intelligence we have many clients where many of the decision makers go crazy and get many of their questions answered on the fly using the natural language functionality. Now I want to dive into the more specific reports and dashboards for construction that we have built for many of our construction clients. And it's part of our out of the box solution. Some of these reports are available with our what we call the advanced analytics by Dataself. Advanced analytics is a very inexpensive product. You know the pricing starts at 299 per month. Some of these other reports I'm going to be showing is only available with the enterprise solution and we'll talk a little bit about it. And the pricing starts at fifteen hundred dollars per per month. But anyhow, let me start with the WIP report. The WIP report is an interesting journey for us. The first time that we designed a WIP report was just because one of our clients was loving data self and they told us hey, can you just replicate my erp? We report in dataself so I don't have to go to a different application to find reports. So initially we just designed a very traditional WIP reporting pretty much the same as the erp. And over time we start to replicate and advance kind of putting colors when something is negative to highlight which projects are doing well or not based on cross profit or whatever the criteria is. And eventually we start to realize that clients needed to drill down from the WIP report into more details and more transactions. So we built what we call the single page analysis. It actually let me go to the WIP historic. That is an even, even more interesting story. Recently one of our clients, the reseller Ash, one of our clients told us that this client of this reseller has a lot of data in the WIP reporting sort of becomes very slow and you would hit the database of the ERP system and is becoming a big issue when they're trying to drill into details of the whip reporting. So what we did in this particular version of the reporting is we have the contract amounts, the estimated cost, the revised amounts, but then these three columns are the transaction cost. So these numbers are as of today, but the actuals can also be filtered by whatever you want. So by default it shows as of today the transaction cost, revenue, gross profit. But if you want to see the numbers some time ago, let's say I want to go back the numbers, how they were at the end of 2018 on any period when you select, it changes the whole transaction cost segment to show how the numbers were back in that particular period. This was a requirement from these clients that was making the report very slow. Now, when you look at the WIP report quite often you need to drill down into a specific project on an ad hoc basis to see more details in here. Let's say if I choose a project like Marlin here, I just click on it. What happens is it highlights the whole line and opens at the bottom this task report specifically for this project. So if I unclick, I'm not seeing any tasks. When I click, it spells out the bottom section. It shows me all the same metrics, but now at the task level. So I have the project id, I have the tasks, the account groups, the tasks and all the details here. And suppose you look in those, those, those tasks and you look at the labor and something is not right. If I click labor or any of these data sets, what happens is it opens a third section at the bottom of the report with the actual transactions. So the top is high level project KPIs. The second section is breaking down projects at the task level, but it's still aggregated by task in the bottom has every single transaction detail. So on a single page I can see all of these things together. And if you were to look, let's say I want to see a few projects together, maybe related to the same customer, I can just pick and select a few projects together and as I add them, it keeps on adding the whole section. Now the tasks has now tasks for all the projects that I selected. And I can drill down to the transactions at the bottom for all the projects selected. And I see the details here. So from an ad hoc standpoint in being able to go from the top level, middle level, all the all to the most detail is pretty straightforward. Now sometimes when you look at the details, this table here can be huge with a lot of details. And this is going to be a very small real estate area. Well, what if I want to see this, you know, on a big screen we have The Go to transaction button, I click on it and now it takes all of those transaction details and put in a full screen. And now you can, you know, more easily scan through to find some data points are important. Or if you want to download this data into Excel, for instance, or PDF or whatever, you just click the download, let's say cross tab, which would be a Excel. And now the data is in Excel. So you could do whatever you want to do in Excel. So the ability to take project drill down, go to more details, go to transactions export Excel is dramatically simplified in Data Self. This particular client of ours that they were having issues running their weapons reporting because a lot of data right now with Data Self when they run the web reports in Data Self it completely has zero impact performance impact in the source system in the ERP and the reporting Data Self runs in seconds, not minutes. That was the case when they were running before in the ERP system. So much faster and more interactive. So this is a WIP report. Let me show now some dashboards we have built that usually is a good starting point for construction companies. Look at their projects and customers. In this example, right now I have here the contracts or the projects. I can see the contract amount revised or if you want to see actual or not, could be easily changed to actuals the cost and the gross profit. So right now this is sorted in a descending order by revenue. And then I can see what's happening with the gross profit by project. So this section is by contract, this section here is by task. So revenue by task, cost by task, gross profit by task across all projects. And sometimes what you might realize is that some tasks that sometimes can be, you know, tagged the same across different projects, they're having interesting threats and opportunities and you can just scan through them, Hey, I want to see for instance what's happening with my task 1, 2, 3. I select those three tasks and by selecting here, it will show which projects are using those tasks, the cost associated, the gross profit and how those things are changing over time. So very interactive way to see contracts, tasks and things over time. All of these dashboards, they're highly interactive. Hey, what if I want to see only one of these projects? When I click on the project here, it will show my tasks associated in my timeline for each one of them. Very interactive way to analyze projects, revenues and profitability. And again, if you select a few of them, you have the whole dashboard to change accordingly. Many clients when they see this on the dashboard say, wow, this is great. But what I want to see is actually and they want to, you know, they require modifications. Sometimes we make the modifications for them, sometimes we teach the client how they can use the report editor to make those changes. And many clients actually are empowered to change a lot of these reports and dashboards by themselves. Another area that is very popular among construction companies is cash flow, cash flow projection, in a way. And this is our standard starting template to show how we can bring data together. This is showing as of today, so this would be today's date. The bars going up moving forward is money coming in. The bars going down moving forward is money going out. And the line is the aggregation of how much I have in the bank today plus inbound, minus outbound money as you move forward. And I also have here my line of credit. So overall, I want to be sure that my projected cash flow never crosses my line of credit possibilities so I don't run out of cash. All this aggregation of information in the chart can be seen on the right in detail. So here on the right you have every single detail. You know, receivable, open receivables, open payables, depending on what version you go. With dataself you can add payroll information, loans that you owe, recurring expenses and revenues. All the transactions can feed into the details that eventually feed into the chart. Now again, let me show how interactive cash flow analysis is in data self. Suppose I look at this dashboard and let's say that yes, I had no problem, the money was not crossing my line of credit. And today when I run this dashboard, it crossed the line of credit. What the heck, right? What happened? And then I realized that on this day, which is October 19th, you know, my cash flow is going negative. I mean it's crossing the line of credit is becoming red. What happened on the 19th? So I can click this data point and by doing so it will filter on the right all the details, only for the details related to this data point. So on the October 19, I see all the transactions associated to that data point and in my sample database I see that this vendor was added and is about a million dollar in AP amount. And let's say it was a mistake. Let's say that this vendor has not been approved, the invoice was not approved and somehow got into my AP list of invoices to pay. And as the cfo, I will say, okay, I'll fix this, I'll talk with my AP person, but let's see what's going to happen with my cash flow once I remove this vendor from my cash flow projection. So I can click on the vendor and say exclude. I don't want to see this vendor in my cash flow. When I exclude it, the cash flow is recalculated and now the cash flow projection no longer crosses the line of credit. And like yesterday, this is how my cash flow is supposed to be working right now. Common question, you know, right now this is a 40 day cash flow projection, or how hard it is to change to 20 days, 50 days, 365 days, whatever it is, is as hard as coming to this particular box here and putting the number that you want, 365. And now this cash flow projection would go 365 days out. Now how do we do the cash flow projection in the long run? Well, by default, the out of the box only look at actual transaction in your erp. Open receivables, open payables. If you have like no cash payroll information, we can, you know, push it out, assuming it's not going to change. So the out of the box setup only looks at open transactions and recurring transactions. But the system can be customized to fill in the blanks. You know, the more out you are, you might want to use averages or projected amounts based on, let's say what was the same amount last year plus 5%. So we can do cash flow projection even when you don't have transactions to support, so you can have a visibility into your cash flow analysis. So popular dashboard. Also for construction companies, the next one I want to show or talk about is the receivables. Some companies, they don't care about receivables. Some companies, receivables is a critical part of their business. And in construction, in some construction companies is very critical to combine together AR receivables as well as pro forma. This pro forma request was actually came from Hartzell. He's one of our clients using Acumatica. They were spending a lot of hours weekly taking their receivables out of the erp, their pro forma invoices out of the RP and combining together. Because pro forma invoices are receivables, but it's just waiting for a signature from a sale from an engineer to make that pro forma an invoice. So this was a big request. We blended the data of both data sets and now when clients are analyzing their receivables, they can choose. I only want to see receivables. What I also want to see with the pro forma, which means it's going to be impacting my cash flow as well. And like any Dashboard in data self highly interactive. So this is the total balance. Open receivables by aging bucket using this color legend by location, where the money is coming from. Again using the same color legend as this by due date, where this is today, on time or going forward in late invoices or using the legend by salesperson, by document, by customer in all the details. Let's say, hey, what if I want to only see the invoices that are late? I can easily select only the late buckets. By selecting them, the whole dashboard changes to only show me the total late by bucket and then the same perspective that I showed before. Or maybe when you look at this dashboard, you want to focus on customers like say my top customer and this one and this, they have a lot of, you know, old invoices. So let me select those three customers. This one, this one and this one. So I'm selecting three customers that have a lot of aging, you know, open balances. And now I have a perspective of these three customers, what's going on, the documents, the details. And this could be a conversation of a salesperson that owns those three customers to see if they can work out the receivables. So highly interactive. And again to get this data into PowerPoint or Excel is just a few clicks away. Moving along. P and L balance sheet and financial we call the financial analytics. The data self enterprise version is extremely robust and provides a lot of ways to look at financial. Reporting on the advanced analytics is something that we're still working with a few clients on a one on one basis. It's more limited. But what some of our clients have been doing with P and L with advanced analytics is kind of doing a P and L by project. So this is an example, kind of a mock up where you have a simple P and L structure with all the P and L buckets that make sense from a project standpoint. And then you can have columns, every column would be a project. So you can see how the profitability, the total sales one, not by project. Right now I have the filter showing all projects and if I don't want to see them all, I only want to see one project, maybe two projects. I just select press apply and now, you know, the P and L by project becomes easily sliced and diced. We're very excited with our financial analytics. In our advanced analytics we believe there's a lot of potential to help clients very inexpensively giving management better visibility and empower them to easier analysis. But right now in the advanced analytics, the financial side is still limited compared to what we can do in enterprise. Alrighty. Well this was mostly the product presentation per se. Let me go back to my website and if you want to learn more about our solution for construction by yourself, if you're kind of self service kind of person, if you go to dataself.com on the industry menu you can click Construction. This page is also fairly new but we are adding content to help you learn about dataself. And if you scroll down you'll see some information including some sample reports and dashboards in a very popular page in other construction in other industry pages is the View Sample Reports. If you click View Sample Reports you'll see on this page a bunch of reports and dashboards available. By the way, the first section is for Advanced analytics which is the inexpensive product that I told you about. So you can see here there's a bunch of reports and dashboard available out of the box and then after you go to the Enterprise analytics which has thousands of reports and dashboards out of the box and if you scroll down you're going to see a bunch of them covering all different areas of the business anyhow. So feel free to explore this page. It's very informative. Alrighty, let me go back to my PowerPoint. All right, I hope you have enjoyed pricing. So the Advanced analytics version as I mentioned starts at 299 per month. The $299 per month is what we call the Core financials. Core Financials is mainly a par open receivables, open payables, sales and for some systems we also have cash flow projection. Like Ecumenica we have cash flow projection that the basics. For other erps we don't but the starting price is 299per month. If you want to add the Construction Edition component then there's an extra cost on top of it. I think it's about $100 to get all of the things from the core system plus the project accounting reports, dashboards and connectors. Now because you attended this webinar we have a special going on which is a 14 day free trial and this is limited availability. So if you want it send me an email and I'll give my email information. At the end of the webinar I can give information how you can enable the free trial to see if Data Cell is going to work for you or for your clients Enterprise as I mentioned. By the way, let me go back to my website quickly to talk about pricing and where you can find some more information about pricing. So how can you learn a little Bit about pricing data Self pick the ER system that you're working with. Let's say Acumatica. When you go to this page you have the Advanced analytics and Enterprise Analytics. Advanced analytics starts at 299 and actually this is the page for Advanced Analytics. You have a lot of information as the solution for Acumatica as a whole. There's the pricing list right here. So the core systems is 299 starting with this resource level and all those details. The construction adds this depending on your source level in Acumatica you can deploy the solution in about 15 minutes. Yep. One time you deploy the solution and you get Advanced analytics right off the box. If you go to the Enterprise analytics button and you click here, you get another page that has more information about the enterprise version including some comparison between the two. An enterprise starts at 1499 and usually we'll have to have a conversation to spec out the details and come up with a pricing specifically for your needs. Alrighty, let's go back to the PowerPoint and with that I close my one way talk and now I'm going to be addressing questions. So if you have asked anything or if you want to put some time, go to the either Q and A section in Zoom or the chat box to ask questions. And I already see some questions here. See. So one of the questions here is from Christine. Is everything you show today available out of the box or do all the reports have to be billed per customer? Christine, thank you for question. What I show today is all available out of the box. Everything that I show today is available out of the box. Most of the things I show today is available with the advanced analytics which is the $2.99 per month inexpensive, mostly on the P and L. Maybe cash flow is when we might need to talk enterprise, but project accounting, receivables, things of that nature is available out of the box as I showed for the construction side. Good question Christine. Thank you. Another question here is is there a security layer if we want the PM to see only their stuff across all areas? My projects cash, my cash requirements related to me, my receipts. Is this achievable? There's no name for this person but it's about security. Absolutely. As I mentioned, Data Self uses technology that has been designed for Fortune 2000 companies and there's a lot of dials how to control security. The simplest way to get started with security is we have the concept of projects. Let's say you have a project accounting project, a sales project, a financials project is a CEO Project a upper management project and then each project you can tell who has access to that information. So if I'm you know, project manager and I mean the project accounting or whatever that I manage folder, I would only see, I could not see gl, I could not see sales, I could not see anything else, but whatever I have entitled to. So that's the first level of security. Just put people in containers and in those containers you put the reports and dashboard that these people care. So that's level one is super simple. Usually as part of our training we teach people how to segment people in different projects. Now what you're asking is the next level of security which is called role level security. And the idea is, let's say you know your question, the project manager, when they go to look at their projects, we can associate the project manager ID with transaction that this person has access to. So when they see a project cost and revenues report that is the same across all project managers. However when I log in, suppose I'm the project manager for the west coast, the solution will only render data from the west coast while let's say Mary from the east coast, she opens the same report as me inside of the same project, the project management reports, but the report only renders transactions associated to her project manager id. While the VP of service is above us, when this person opens the same report, they will have information across everyone and then this person would be able to segment Johnny's or Mary and anyone. So yes, absolutely we have several layers of security that can control what each person has access to and what each person can do. Can a person export data? Yes or no? Can a person do ad hoc analysis? Can a person do natural language? Yes, there's a lot of the control security level. All right, let's see, there are more questions. The question here is from John. How long does it take to deploy Data Self? John, good question. So there are two versions of Data Self, the Advanced analytics and the Enterprise Analytics. Advanced analytics on average takes less than half an hour to deploy the out of the box. If you have a system like Acumatica it's self service. You just go to the website, fill out the form, you got to upload some gis to your Acumatica and you know it takes like 15 minutes to do that job and you know a few hours, your data comes alive in Data self. If you have an on premises system usually takes about half an hour, we will have to connect with your IT people to install a data extractor in your framework. And then usually after this half an hour work in a few hours. The data comes alive in data self. So advanced analytics deployment is fairly self service and is fairly straightforward. Yes, the out of the box might not be ready. Half of our clients, the out of the box is perfect, they deploy the box, they go through the learning, they they go to the training and they take off. The other half of the clients, they might need more customizations, optional fields and modifications, the back end. So it might take, you know, some days, maybe weeks going back and forth to make some tweaks. But overall advanced analytics is super duper simple, yet very empowering comparing to what you have today. When you go enterprise Enterprise has a full fledged data warehouse. The out of the box deployment usually takes about a week. But when you go enterprise, usually your needs are more sophisticated. You might have more data, more tenants, more companies. Usually you have more elaborate business. So on average the enterprise deployment to go live to get users to use usually is at about a month out of the box a week. But you know, testing customizations usually within a month is when the enterprise version becomes ready to go for users. John, thanks for your question. There was the questions. Looks like these are the questions. Let's see if I miss anything over here. Nope, that was it. Well, this webinar is being recorded and we're going to make it available for you tomorrow. And we're going to also post this webinar recording in our construction webpage. If you want to discuss anything more about dataself how it can help you and your clients. My contact information is here. My my email and phone number. I hope you have you have found this webinar informative again is our first webinar specific for construction. If you think we should cover more less of the topics, let us know. We're here excited to help the construction business and help decision makers make better decisions out of it. Hope you have a great day. Thanks for joining. Stay safe, well and sane. Thank you very much.