DataSelf Analytics (Tableau) for Sage ERP/CRM Webinar

Get more value out of your Sage, ERP and CRM data. That's probably why you are attending this webinar today. And typically when people come to our webinars or talk with us from the Sage market, they're trying to improve their reporting processes, typically from areas like this, Financials, sales, inventory, data blending. Data blending is a kind of concept where people want to combine data from different places, where it's very complicated. Maybe you want to see in your financials information coming from your AR or AP or so information connecting them is complicated. Or maybe you're trying to connect your sales with your sales order, your quantity on hand and your inbound items. It's kind of hard to blend data from different places or maybe on a combined data from your CRM with your ERP data, maybe with your payroll. And blending the data is complicated. Other companies come to us to talk about data consolidation. They have multi company systems. They want to see all the data together. Can be challenging in some people because just giving people information, distributed information is challenging. Welcome to our session. So this is Data Self analytics. We're going to be talking also about tableau for Sage ERP and CRM. My name is Johnny Girardi. I'm the founder and CEO of Data Self and I'm really glad that you joined us today. So let me show you here the agenda for today's presentation. So first of all, I want to talk about some reporting concepts and just so you know to understand a little bit of the things that may be challenging for you today. Then I want to show how those things can be solved and how Data Self can add value to the process. We spend quite some good time showing our product how it works. We'll have a QA session at the end and then throughout this presentation I'll do three quick surveys just to be sure we're collecting your input so we can improve our services and our communications moving forward. Alrighty. So let's talk a little bit about reporting processes. Why so many people have challenges with reporting processes? Well, first of all, there are different pieces of the puzzle that are usually complicated. The first one is we call data preparation. When you ask for a new report, the person who will be taking this report and building it needs to know where the data is and how to put it together. So they need to know the source database, let's say your ERP system, tables, how to join the tables, how to make calculation with the tables, data. This is the data preparation and usually also called the pipeline to bring the data from wherever it is to a format where you can see the information. This part of the work is usually highly complicated. The person doing this job needs to know a lot about the database structure. So not easy. The next step is data presentation. All right, I got all the data, all my sales information or financials and now I need to build a report showing I know this year, this quarter by GL segment or this customer or this product and whatnot. So how you organize the data on a report is called data presentation. The last step is, hey, now we need to give this data to people who need to consume it and that's the data distribution. Quite often in the mid market, all of these three pieces of the reporting process are done by a single person or some consultants, highly trained people that will be spending time and time to understand the data, connect the data using a reporting tool to bring it to a format and then emailing or somehow giving people access to it. So you know, usually it's time consuming, is expert centric and it's not very productive. So that's how usually the reporting process works for companies using a Sage product or competing products. So now before I move forward, I want to quickly make a survey here asking you guys what are your reporting challenges? So let me launch this poll so it should be seen on your screen. A questionnaire. I ask you to just choose all the options that apply to your business. You have four options. Your reporting is difficult to use, it's low, queries is low. There's a lack of access anytime, anywhere, so it's not mobile enabled and there's no lack of consolidation. Maybe other. Click all the options that apply to your business and click Submit. So give a little bit of time. So be sure to check all the options and click Submit. We're still having a lot of people submitting, so I'm going to give a few more seconds and I really appreciate that. Five more seconds. Please submit your answers. And appreciate. I'm going to close and I'm going to share. So as you can see here, a lot of people saying it's difficult to use. Pretty much everyone complain about almost everything. Slow 42% lack of access anytime, anywhere. 50% lack of data consolidation. 63% wow. The biggest one. Cool. And others. Okay, much appreciated. So thank you very much. So let's move forward here. So just going back here. So those are the things that usually people go through and the pains that you just reported or submitting in the survey. That's pretty common because quite often people are using a single tool or different tools that are not really designed for making this process more automated. Well, typically I'm going to show an approach that usually makes this process automated. Whatever the computer can do for you, this framework is usually a great way to tackle it. So here on the far left we have your data sources, your Sage urp, your Sage rm. Maybe you want to combine data with Google Analytics, maybe you have Salesforce, social media, a payroll system, a point of sale system, doesn't matter, you have all of those silos of information. Well, to take care of the data preparation process, typically you need to move the data out of those systems into a separate database where you can blend the data together, you can massage the data, you can make it clean, you can make it more descriptive for business people. So in many businesses the way to do the data blending is using a data warehouse. And for many people, data warehouse seems something complicated, expensive, time consuming. It can be. I'll talk later how we do it. But a data warehouse has the benefit of combining your data silos. Your data sources can be Excel files into a single place and now all of them will be able to be reported together. So typically data preparation is solved through a data warehousing. Now when it comes to data presentation and distribution of data, there are so many options out there in the Sage world to do that. Usually some of them will do something really well, inexpensively, but quite often they don't give you the whole picture of getting data in an easy format, in a format that your business users will be able to consume it anytime, anywhere. So maybe some of your users are going to be consuming the data using their mobile devices, or maybe they want to receive the reports on a scheduled basis in their inbox. So different people access information in different ways and having a platform that can fulfill or deliver functionality for all these different methods is critical. And most importantly, once the data has been prepared, one of the main things you want to do on the data presentation is a framework that will allow your more data driven decision makers to become self sufficient. They should be able to consume the data anytime, anywhere. They should be able to drill down, they should be able to slice and dice, they should be able to even build new dashboards, new reports without calling for it. And how is that possible with this framework? Well, if you look at this, this part in the middle is still highly technical, probably more technical than what you're using today. Building maintain a data warehouse, you have to be a more IT expert than probably just building a crystal reports. But the beauty of this is once this data warehouse has been properly plugged, to your data sources and all the data has been blended following whatever rules that you want to see your once that hard, difficult work has been done. Now if you have the right analytics platform, business people be able to start spinning reports, creating new insights without calling for support. It is amazing how much easier data analysis becomes once the data preparation has been properly taken care of. And we'll show how we do that later to see how much value get out of this. But anyhow, there are in the sage market different people offering some kind of framework like this. We're one of them. We've been doing this for the longest but I encourage you as you're looking for your options for people who provide you with a data preparation format like this, using a data warehouse in an analytics solution that is really going to fit your needs. Now that's overall the reporting challenges in how you can tackle them in the long run. Let's talk about Data Self now. How do we do it and why we're doing this way? Let me go a little back in history. When I founded Data Self I was already working with BI in this market mid sized companies thinking oh my gosh, decision makers here, they need data. Their problems are very critical from a reporting standpoint. But the tools available in this market, inexpensive tools, are kind of clunky. It's very hard. Decision makers, they're not typically IT experts, They're running business, they're managing people, they're selling stuff. The reporting tools in the mid market are too clunky. I don't think I'm going to work with them. What I want to do in my vision was I want to find in the Fortune 2000 world the best of the breed reporting tools that can fit this market. And I want to add my own secret sauce to make them simple, to make them affordable so you can take advantage of it. So that's what we do. We go to the upper market, we take the best of breed technology. It make you work together, it's that simple. So I'll talk a little bit more about how we do it. But overall it's taking the best of the breed. Make it work for you and you're not going to break the bank, you're going to get a lot of value out of it. Quite simple idea. Let me talk how our solution came together. Since we started the company, we've been using Fortune 2000 vendors to complement our technology. One of the ways to see which ones are doing best is using at the Gardner Magic Quadrant for BI and analytics platforms. Over the years we have been always using vendors who are really well positioned in the Gardner Magic quadrant right now. The latest solution we have has nothing but the very leaders, the top vendors, Tableau and Microsoft as being part of our enterprise grade technology. So again, what data self is bringing as value to you is nothing but what is really best for Fortune 2000. Making simple, making affordable for you to take advantage and to maintain it. Putting back the architecture that I showed before, this is how our pieces work together. So the data warehouse that I was talking about before, something we do very differently than other vendors is we use our own ETL tool. ETL means extraction, transformation and loading. And this tool extremely simplifies the process of deploying and maintaining a SQL Server data warehouse. In SQL Server Data Warehouse, in one of the most popular frameworks out there, many of our competitors also use a SQL Server data warehouse, but they use SQL Server programming which is usually very time consuming and usually takes a long, long time to deploy and maintain. Because of our etl, we are the opposite. It's easy, it's fast and simple. Then on the analytics side, the data presentation and distribution, we use the Tableau in memory analytics platform which can be deployed on premises or in the cloud. Both approaches available. But this technology has been proven to be the most successful platform for empowering business users to access their data anytime, anywhere and being able to change data to slice and dice, drill down and even create new reports without calling for it. So this is how we put the pieces together again, enterprise grade technology. The leaders made it simple, made it work for you. Now on the tableau side, I like to spend more time because it's an amazing what Tableau does when we're choosing five years ago a replacement for our old client tool. Eventually we chose Tableau. And I think this sentence is one of the most critical pieces of why we bet on Tableau. And then it become really, really good. So this says, you know, a lot of data visualization research is really about making pretty pictures. But we worked with psychologists and graphic designers to understand how people deal with visual data in process. It it's impressive because you know, when you are trying to get data insights out of your data, it's a discovery process like let's say, hey, I want to see how things are not doing so well, what's going on. You know, people go through a process of discovering their trends. They're looking at different spins, different charts. It's a process. And many of most of the other BI vendors analytics platforms than Tableau, they try to make flashy, beautiful Things, but they're not necessarily insightful. They are geeks designing flashy things. Tableau focuses in what functionality will give you the decision maker, quick insights into what you need to do. And it's going to be beautiful. Yes, but the most important thing is they want to see you insights. The focus is not in the beautiful, is the insights. Let me show a few examples which I think hope is going to relate to you. How about this? What should I do? We humans, we know when we see this, we just get the hell out of it. We have evolved as a species with being visual. And if you see something that quickly gets to your senses, you react quickly. And if we didn't have this kind of sense, maybe we haven't survived. So it works. So that's kind of the tableau way. How can we have this kind of perception when you look at your data and you quickly see what's going on? Well, this is a little extreme example and I'm just trying to make the point. Overall, most companies use a lot of rows and columns reporting out of the data. And it's great. It is valuable and, and Tableau definitely support this approach. There's a lot of ways to do it, usually much easier and faster than other options. But you know, rows and columns is a great way to analyze data, especially in a more granular level. Now there's also the more visual and I want to see information in different ways. So let me show an example that Tableau really excels at. Suppose you want to see these numbers and you want to count how many knimes do you have here? Some people may quickly give you the number because they are very gifted at seeing how many knimes are out of this myriad of characters. Most of us, it's going to take a while. So what tableau does is how about this? It's using simple techniques to highlight what you want to see and give you insights more quickly. So when I look at now, yeah, there's about 10, much quicker, much more visual. Another example, maybe I'm looking at this spreadsheet and if I'm one of those few gifted people that look at these numbers and in a few seconds I can tell trends across the board. Who's the most profitable, who's selling the most. Most of us can't. Unless you go through and look in detail, it's very hard to look at that information. With Tableau, the engine has been designed to give you this. Now if you look which are the biggest sales, much easier. The big bars here shows that Central is The biggest area of profitability of sales. Which ones are not so profitable? Well, quickly you can see. So now visually you have a much quicker insight. One more example here. Pie charts. So beautiful. 3D pie charts. So beautiful, so insightful. Really. They're very beautiful, no question about it. But they can be deceiving. So when you put in an angle the slices, sometimes you have not a good idea which slice is bigger. So Tableau makes it hard for you to make 3D pie charts because they are deceiving. What you need is Insight in a 2D pie chart is what you should be looking at. So again, these are some of the things that tableau does really well at focusing on giving you insights. Beautiful insights, but mostly insights. And not just fluffy views. The final piece of the value that we provide out of the box is just a good starting point of reports and dashboards. If the good starting point has more than 5,000 templates, reports, dashboards and KPIs, how did we build them? Well, my team, we have been doing this enterprise grade BI for mid sized companies for 16 years now. And at the beginning we started with zero reports, it was just a pretty tool. But as we learned how our clients were looking at data, we started to realize, well that's really cool. How about we add to our out of the box solution? So we kind of crowdsource our list of out of the box reports and today it's a great starting point. More than half of our clients find that the out of the box solution is all that they need. They take it on and they just take it over. The other half require more customizations, data blending, whatnot. But for them, the out of the box still proves to be a great starting point. So not only about having a great reporting platform, but shortcutting. The time is going to take your company to really get value out of your data. It's all about getting value out of your data. Alrighty, let's make our second poll. Very quickly. I'm going to open another poll and you should be seeing now what are your main reporting areas. So please vote. You know which areas. If you're going to be trying to improve, you want to have tackled as soon as possible. I know maybe you have all of them eventually, but if you see in the next few months which ones would be the most important, please submit your answers and press submit. Okay, I'm going to wait five more seconds. All right, I'm closing the poll. Thank you. Let me share it. So look at that. Really appreciate it. Financials is the biggest Sales is the second, inventory management the third, CRM the fourth and others is the fifth. Much appreciated. Okay, thank you very much for your feedback. So let's go for the product demo. What I'm going to be showing you is self service bi in data discovery. And pretty much what I'm going to be showing you here today is the Tableau user interface. We have an OEM with Tableau. So what you see is actually data self analytics branded but using the Tableau engine behind the scenes. What I'm going to do is actually replicate one of the situations, one of the case of one of our clients, a California company, distribution here in California, where the CEO needed to get many reports for his monthly board meetings. And every time he was going through this process, he was spending, he and his team were spending quite a lot of time to get the data ready for the meeting. And I'm going to show how he was able to do it himself. So the first part of it is they need to see this month's sales details. They want to see sales by product, sales by customer, invoice number, invoice date. So I'm going to show you how rows and column reports come together. Then the second one was actually a data blending need. They have Google Analytics data and they want to combine with their actual sales to see how marketing initiatives in their website was affecting sales. So I'm going to show you that as well. Then the next one is they were selling across the whole USA and they want to see sales by state and how big the deals are or were. So I'm going to show those examples and also some other reports that were required for the board meetings in all in this part of this presentation. Let's do it. Finally get out of the PowerPoint. I know some people get bored with PowerPoint. Okay, so now I'm switching the user interface into the data self analytics desktop and I'm going to start showing you how to build things from scratch. And then I'm going to show you how they look and how they can distribute, how the information can be distributed automatically to your users. So let's start with the first problem which is the report showing this month's sales details. So once this company acquired dataself and they went through training, the CEO was able to do this. So hey, I want to see this month's sales details and I want to see actually by product. So it's pretty much everything drag and drop. So I come here, I see my connector in this case is a revenues connector and I see the dimensions or things. I want to see my numbers by my customer, products, territories, whatnot. And then I have the measures, the numbers that I want to aggregate and analyze. So if I want to see product, sales, what I do is I come to product, I drag and drop product into my report. So these are all of my products. And then I want to see sales. I drag sales into my report. So right there I have sales by product, very simple. Now I want to see this month's sales because of my board meeting. So let me take invoice, date and just drag and drop in my columns. So now I have by year sales for all my products. Well, I can drill down from year to the quarter or I can drill down from quarter to the month and I could go down to the day, I can go down to weeks, fiscal periods, it doesn't matter what kind of time buckets you want to analyze. Once we do the data preparation at the data warehouse, it's this easy for decision makers to find information. All right, now I only want to see this month's data. I mean, here I have my whole company history. It's a lot of data. Well, I want to filter it again, drag and drop. I'm going to take the invoice date, drag into my filters area and I'm going to select a relative date because I want to see this month, which is next. And here I select month in this month. Click. Ok, there it is. Now this report will always show me. Oopsie. Will always show me this month data. And you know, if I'm the board meeting and then if my board asked me what happened last month or what happened this quarter, last year and whatnot in the past, the CEO would have to make notes and I'll get back to you now in these board meetings. Oh, you want to see last month. There it is. Oh, you want to see maybe this quarter. There it is. Very easy, very intuitive, very fast. Now they have data on their fingertips. Okay, so I'm looking at sales this month by product. But the CEO was going to the meeting showing this report by product, by customer and by invoices. So let's add that information again. It's all drag and drop. Let me add customer. So customer, I'm going to drag and drop right here. So by product, by customer, I want to see invoice number. So invoice number here. Maybe I want to put between the two of them. And maybe invoice date. Let's put between the two of them. Just whatever you drag and drop, you get the information. So we with this kind of functionality, it's very straightforward and very easy. Where the co just did it, hey, I want to see quantity shipped, just quantity sold. Drag and drop and you get the data. So tabular reports like this become something very easy, very quick and very intuitive. Again, you do not need to be a technical person to be able to slice and dice your data and create new reports from scratch. Very intuitive. All right, now what about marketing versus sales trends? Well, now we have a data blending problem. They want to see Google Analytics data and compare with their sales coming from Sage. Try to do that with whatever tool you're using today and good luck. Well, with a data warehouse like ours, we just brought Google Analytics data along with the Sage data. We meshed them together in the data warehouse. It was a technical work, it took some time, but once we did that, a one time configuration of this data blending. Now the CEO was able to do this well, I want to see sales, I want to see sales by date. I want to see this actually by month. So I want to see sales by month. So right now this is sales by month for the whole company history. Now website visitors is here. It's part of my revenues connector. How it was done, it took care of it. The CEO didn't just order it, do it. Once the it did it, it became part of the automatic refresh. Now the CEO took website visitors from Google Analytics and dragged and dropped into the report. So these are website visitors. Let's make bars. So they are, you know, easy to tell apart and let's actually put them together on a dual axis and look at that website visitors and sales all together and they can see how one is affecting another. Very straightforward. They can spin it in different ways, different periods, by different territories, all drag and drop. And you can start analyzing your activities and really pinpoint where the opportunities are trending up or trending down and where the threats are. All right, regional sales by deal size. Well, now we're going to see sales by state in how big the deals are. So what we do is we pick, let's say customer state. I want to see invoice sizes and sales. I just pick those things and I tell the tool. Show me this data. The same thing that I showed before with the snake. A little joke. You see how easy things are here? This tool, this tableau engine again has been designed to make visual representations of your trends easy and fast and informative. Not only beautiful, but informative. And it takes little effort for a business person to become self sufficient in doing analysis like this. Just like the CEO of this company was doing. Okay, awesome. So I built these three views together and the CEO is going to the meetings with his iPad. He want to have these three views together to be on an iPad. So now he creates a dashboard and then he's going to say, I want to have my map at the top, I want to see my trend analysis at the bottom. It's all drag and drop, quick and easy. And I want to have this view on the right quadrant. Drag and drop and you build quickly this beautiful representation. Again, the idea is you should not make this something complicated. You should make this something that business people can quickly slice and dice the data without requiring assistance. Once this dashboard has been created, in a few more clicks it can be published to the web server. And now everyone having access to this portal can have this data and start analyzing and slicing. And dicing. On the case of the CEO, sometimes in his board meetings, a board member would say, hey, I'm traveling to California and Texas. How are we doing over there? And the CEO, okay, he makes note, next week I'll send a report showing how well we're doing in those two states. Now with data self analytics, he comes here and during the meeting, oh, okay, California is here and Texas here. He just marked those two areas. He got the report right there on his iPad and he emails the report from within the iPad. And what's the next question? Shrink dramatically the time to get to the data, increase the time to analyze your data, make decisions and act on things that only humans can do. Everything else the computers should help you to do. Alrighty, so let's see some sample reports available out of the box out of the 5,000 lists we have and show how people usually consume the data. Most people will be consuming the data using a web portal like this. They will be logged into the web portal. When they log to the web portal, they will only be able to see their teams, reports and dashboards. So if I'm from the finance team, I'm going to be seeing financial reports and dashboards from the sales team. I want to be sales team dashboards. And then let's say suppose I come here and I search for my top customers, top customers. And suppose I found the report, I open the report. Now when they open the report, security can be controlled in a way that will only show your own information. So this report would be the same for all salespeople. But if I'm the California rep, this would be my top customers in California. While the VP of sales opened the same report in views the customers in the whole country, in this case they are the top customer by sales change, meaning who grew the most since last year to date and who declined the most since last year to date. Or maybe I want to come here and see, I want to see pipeline information for CRM and then I open one of those reports and let's say maybe I want to see my funnel and then it shows the sales funnel with all the details and I can actually say hey, I want to see only for a particular salesperson and you can keep on changing the sales funnel. You get that response right there. Or maybe I want to see my pipeline and these are the salespeople, how much opportunity they have and what's the total, all the details. If I click Ed Martinez here now I only show Ed Martinez opportunities and I only want to see what is open. Very easy, very intuitive. Using a web browser, a tablet like an iPad or a mobile device, you can get this information. Or maybe you are in the financial department. And then you open one of your dashboards or reports. Now let me show about the drill down capabilities. Sometimes when you're doing these things you need to drill down and get into the details. How can you do it? There are many ways you can get data at a detail level. For instance, you can click on a framework like this and then you can have pre configured drill downs to some more specific visualizations. So in this case I'm looking at the New York, I click on the New York bar and I say show me my monthly details. When I click that I go into a different report pre configured that will have the more detailed information in a certain way. And now for New York only I have all of the details for all the months. Or maybe I actually want to see the actual numbers behind this. I want to see all the transactions. Now I drill down into all transactions and now I have all the information here. If this would be, let's say invoices you would see invoice number, invoice, date, salesperson, customer, product, ship to. Every single detail is here. You can download the information if you want to an Excel file and take it offline if you want to. So drilling down to the most detailed level can be in different formats and you can use again different tools or different user interface to get to that point. All right. Finally, people need different ways to access their data. Some people are always sitting on a desktop so they can use the desktop client like I was showing or they can use a web browser. Some people are mobile, they need to gather information on mobile devices. On tablets, on smartphones. This framework has natives iOS and Android apps for mobile devices. So all of the things that I'm showing you here will also be available on mobile devices. And some people simply want to receive on a scheduled basis on their inbox and then you can click and say I want to subscribe and receive this particular dashboard every day, every week, every month. So different ways people can consume the data this framework can deliver. All righty, let's move forward. I hope you have enjoyed the demo. So in a nutshell, what are the main benefits of data self? The most important one is empowering the decision makers, giving them access anytime, anywhere to their data so they can shrink the time to get to the data so they have more time to analyze, to decide and to act on. How do we do it different than other vendors? Well, we have a very easy to deploy maintain data warehouse and we use an analytics platform that is powered by the leaders in the Gardner's magic quadrant. So pretty much there is nothing better overall. It may not be specific for you, but overall it's the best technology available for Fortune2020. And on top of that we have more than 5,000 reports dashboard KPIs as a starting point so you don't have to build everything from scratch. There's a lot of things ready to go. So that's benefit number one. Empowering decision makers. The second is this technology will reduce your reporting labor by more than 80%. A lot of the repetitive tasks will be automated by this framework. How we do it first of all is significantly easier and faster to build and modify reports. As you probably saw, it's much easier and faster. Repetitive data tasks data manipulation tasks can be completely automated by the data Warehouse framework so you don't have to copy and paste and calculate and whatnot. It's going to be all automatic, automatically processed. And finally, the tool has many ways to automatically distribute information to people in different ways. So those are the two main benefits. Before I jump into the Q and A session, I want to open the last poll and I'd like to ask you how was this webinar? Is it being formative? PowerPoint session was too long. Metric expectations and if you want to be contacted asap, so please respond and submit. We're still getting answers, so keep on going please. Wow, I'm surprised with the results here. I'll give five more seconds for the last people to submit. Oops, I'm sorry I accidentally closed it, but I think we got most people. Let me share it. Informative. I really Appreciate. I'm glad that you guys found informative. Zero vote for the PowerPoint session. Too long. Boy, I was afraid about that. I appreciate that you guys found informative and the PowerPoint was educational then a lot of people met the expectations. For those who have not probably will send some emails and I would like to know what we can have done better. And many people also asked to contact asap. Okay, very good. So let's move to the Q and A part right now. So if you have questions, Please use the GoToMeeting Question Panel, the chatting panel actually, and submit questions. Let me see. So we have questions here. Question from Robert. How do you compare your solution with Sage Intelligence? Robert, very good question. So first of all, we use Gardner level Gartner endorsed platforms. Actually nothing but the very leaders. So I can just put here. So technology we use are the leaders for Fortune 2000 sage intelligence. They have two versions, the reporting and the enterprise. They're both very good products, good pricing, but but they're not as refined, as robust and as fast as what we support. So that's kind of more generic comparison. What I usually like to tell people is our solution is more expensive than theirs. Yes, it is. It does not break the bank. No, it does not. The price difference is not that substantial. But at the end of the day, what we tell is you get what you paid for. If your pains are little, they may be a great way to go. If your pains are bigger or if you want to be more empowering, you want to get more value, the extra cost of our solution is usually well worth it. So keep that in mind. Folks, we have more questions here. Unfortunately we're running out of time, so we'll be addressing those questions by email. Let me go back here to my last slide. If you want to talk about BI analytics, about competitors and other options, we've been doing this for a very long, long time. And my goal is not to sell to you, is to educate you. And if our solution is good for you, awesome. We'll work together. If someone else solution is better fit, I'll tell you, hey, those folks can do better for the price that they're asking. So feel free to.