DataSelf Analytics (Tableau) for Multi Company Consolidation

Better reporting from multi company systems. If you're watching this webinar, that's probably you are here today. Typically when companies are trying to do better reporting from consolidation, from multi company consolidation purposes, they're trying to get better, you know, or easier financials, maybe sales analysis, analysis of inventory. Maybe a main challenge is distributing information to the companies, to the individuals at the corporate level in a secured manner. Or maybe even is trying to blend more data. You know, not only the multi company, but maybe people have other data silos, maybe the CRM system, maybe payroll and those things can be complicated. Thank you for joining us today. My name is Johnny Girardi, I'm Data Self founder and CEO. And today this webinar is about data self analytics, powered by tableau and using for multi company consolidation. So what we're going to be talking here today. So first of all I want to be sure to cover some reporting concepts to explain how and why data consolidation can be a challenge and how it can be addressed from a generic standpoint. So just generic concepts about that. Then I want to cover how Data Self can add value to the process. I'll do a demo at the end, we'll have a Q and A. Sorry, it's misspelled here. And throughout the presentation, I'll do three quick surveys to get your input about the content and how well we're doing. So let's get the ball rolling. So first of all, just talking about any reporting process, how does it work? So the first part of any reporting process, you know, when you ask for a new report, one of the most important parts is what is called data preparation. Data preparation means you need or someone that knows the data source, your ERP system, your CRM, whatever data source is someone that knows this data source a lot. This person has to find what tables have the right data. Usually there are several tables. They need to link the tables together and apply rules to get the right data set for your reporting. This task is usually highly technical and people doing it are usually they have extensive knowledge of the data source. So usually very technical people. The second part of the job is, well, now that I have the data that I need for the report, I need to actually present the data in a way that will make sense for the decision maker. So let's say if you're looking at, I don't know, a sales report to show year to date growth, sales from last year. Well, I need to organize the data showing sales, let's say by customer, this year to date, last year to date and show growth so now you're just preparing the data to show in the proper format. Maybe you want to put tabular with rows and columns, maybe to put on a chart. This job usually is by far not as technical as the first one. But depending on the tool you're using, can be very technical. So many companies require consultants to do the data preparation and the in the data presentation. The last part is, hey, now that this report is ready, you know, the person who built it needs to give to other people, distribute by email, PDF, Excel file, maybe to mobile devices, maybe mailed the report, you name it. So data distribution is also another part of the process. Most companies today, they do this job through an expert, a consultant or maybe a few people that are highly trained. And usually it's a fairly time consuming job. Well, this is for any report, even from single company. Now if you look in a multi company framework that you need to do consolidation of reports coming from every single company, then you got to do this over and over. So every individual company like company one has to do their own data preparation, data presentation, data distribution company do the same thing. And if you have 10 companies, all of these companies have to do the job, you know, all the cycle over and over. Once all of these reports have been properly done by these companies, usually they have to be sent to someone at the corporate level. This person will have to take every single report, usually manually with copy and paste in Excel whatnot, and do again a data preparation from all of these individual reports. So a lot of data massage. Eventually when the data has been combined the right way, then they format the data in a certain way to show the multi company reporting. And eventually they do then data distribution. Sometimes the data distribution is only at the headquarters level. Sometimes they send some reports back to the individual companies. Again it's very time consuming and sometimes there are issues. So when you go for a multi company reporting consolidation, some of the common challenges is, well, is a very labor intensive process. Every single company and corporate will spend hours, hours, sometimes even weeks to get the reports together. The other thing is because quite often is a manual process, it's error prone, it is hard to keep track of issues. So sometimes a lot of issues with that. The other thing is if you have a lot of companies and or a lot of data, these reports can run very slowly. So poor performance and finally user access once the reports are ready. Sometimes the only way to access the reports is by email. If people need to change the reports, it's almost impossible. And sometimes having access anytime, anywhere using things like mobile devices. Is just not there. So these are some of the common challenges when it comes to multi company reporting consolidation. So now before we move to the next slide, I would like to quickly ask you to respond what are your main what are your multi company reporting challenges? So I'm going to launch here quickly a poll to ask you that question. If you can, please select all the options that apply to you. The first one here is difficult to use or labor intensive. If it's so, check the box. And by the way, I just made a mistake and you can only choose one option. I'm sorry about that. So the options are difficult to use, labor intensive, poor performance, lack of access anytime anywhere and lack of data silos consolidation. I'm sorry that you know, I incorrectly built this poll to only choose one option. So choose the most important option and please click submit. I'm going to give another minute for you to finish. And I'm going to also change something here. So the next one we don't have the same issue. Five more seconds. All right, I'm going to close the poll. Thank you for voting and let me share it. So the results pretty much we got most people voting for difficult to use and labor intensive and a few people chose others. Okay, thank you very much. Let's move on. So here is a way that typically how you can make this process of chemical solidation much better way, way better. So this is a generic concept. How can you automate as much as possible of this process? So here on the far left I show different company databases. Company one, company two. You may have many companies 5, 10, 20, 50, doesn't matter, many companies. So typically one way to solve this problem is using a data warehouse for the data preparation process. So data preparation, as I mentioned before, is a very technical job. With a data warehouse it's going to be in even more technical. Yes, it's going to be even more technical. However, the big benefit is when you use the proper data warehouse framework, these more technical people will be able to map all of your different source databases, all of your different companies and they can blend the data together the right way, the way that your business needs. And this is a kind of, you know, a kind of a programming approach that once you do that and you do it properly, it becomes completely automated. So all the data from all companies come together the right way. It takes some time to set it up, but once you do it all the error prone, labor intensive, potentially slow process becomes completely automated and it can be done every night. So the data preparation is always consolidated and you're doing your analysis, the data is always there, ready for you to pull the data out of the data warehouse. So a data warehouse is typically the most efficient and automated way to tackle data preparation from multi company systems. Once the data has been properly merged together, consolidated together, then you need to give the data to users and distribute it to users. Well, typically there's so many offers out there to do the data presentation and distribution. My recommendation is try to find the solution that provides the most automated process of, you know, the presentation of your reports and distribution, and most importantly, the easiest to use when it comes to give reports to your decision makers. The easier it is to use, the more likely the decision makers will become empowered by the tool and they'll be able to access the reports anytime, anywhere, using whatever they like, desktop, web, mobile devices. They will be able to slice and dice the data, they'll be able to drill down to download data and even create new reports. So the easier to use the most important, because at the end of the day, decision makers need to make decisions all the time and they need to change the reports, they need to modify the reports. That's my main recommendation, to automate this process. Now some additional ideas here. Data warehousing Many companies do data warehousing. Sometimes they use Access or they use SQL Server, which is the most common ways that we find them in the market for data warehousing. Access databases and SQL Server. So my recommendation is find something that is easy to deploy and easy to maintain. Keep in mind that in a few years you may be upgrading your data sources, your ERP systems, or maybe you have different ERP systems. So if this data warehouse framework is not really easy to maintain, you may have to hire new people or different people to do the job, and that may become a whole new project. So easy to maintain is critical for your data warehouse. Second is it must be high performance. It must allow to crash the data quickly. It must allow the reporting tool to pull data out of it very fast. So typically use something like SQL Server or not to help you with the performance of the system. And very importantly, as I mentioned, the whole process must be as much automated as possible. Data warehouse does not replace human intelligence. It does not, thankfully, we need humans. But it should be able to replicate automatically all the repetitive tasks. So it must be automated on the data presentation. As I mentioned before, ease of use is the most critical component. The second is easy access. People like to access their data in different ways. Maybe they're on their desktop, again, maybe on a web browser, maybe on A mobile device maybe they want to receive on their inbox reports on a scheduled basis. So find a platform that provides you with all of those options, easy access and the last one, again, high performance. I mean nowadays people have no patience whatsoever. And if you can invest a little bit more money to run your report in seconds, to give your decision makers information in seconds instead of minutes and hours is usually worth it. So look for that. These are generic concepts about automating multi company systems. Now there are so many possibilities when you use data warehousing in the right analytics solution. Like in this case this could be a franchisor business where some businesses or some companies are single owned while some of others are a single owner owns several locations. In this case I'm showing company 1 is single owned and 2,3n is the same owner for all locations. So when you have a data warehousing framework, you can have a data warehouse for one of the locations with its own analytics platform. Then you can have a data warehouse for the other locations that belong to the same owner with its own analytics platform. But then corporate may want to have their own data warehouse that consolidates all the data from all individual companies with its own analytics platform. So when you have this kind of framework, as you learn about your needs, you can use the right framework to tackle security, data distribution, data preparation, the right way. Alrighty. When you do that, you pretty much automate the whole process. It's high performance, things will run super quick and users will have access to their data in a secure fashion anytime, anywhere. So there was a little concept overall for all multi company reporting needs. How do we do it, what value we add? So now I'm going to be talking about data Self approach. I'm the company owner and founder. When I founded Data Self 10 years ago, my main vision for the business was well companies in the mid market that are using products like Sage, Microsoft, Infor, Salesforce and whatnot, their decision making process is very critical. But the tools available for reporting are usually not so sophisticated. They are mid market inexpensive but they're not like data warehouse based, they're not the best of the breed. So the vision was very simple. With my team I want to go to the Fortune 2000 world, find the best of the breed reporting tools that can fit the needs and the budget of mid market companies. I want to make this solution simple. I want to make the solution better for mid sized companies, I want to make them affordable and that's pretty much about it. So what we bring to you is the best of the Breed work for you. That's what we do. The best technology made it simple. What we have today is pretty much Tableau and SQL Server and soon I'll talk more about these two upper market vendors and then we add our own secret sauce that simplifies significantly these two upper market technologies and we add a lot of reports out of the box to make the the platform not only the best of the breed, but with a solid foundation for your reporting needs with a ton of reports. So what about Tabloid Microsoft? Well, Gartner is one of the most reputable companies doing technology assessment for Fortune 2000 and they just released every year in February they released their assessment of how these Fortune 2000 companies are doing when it comes to BI and analytics platform Making a long story short, Tableau and Microsoft have been the leaders have been leaders in the garden magic quadrant for many many years and that's what we're bringing to the mid market is the leading design analytics platforms for small and medium sized businesses. So when we look at our technology we do use a data warehouse for data preparation. The way we use this, we use SQL Server and SQL Server as I showed before in the prior slide is one of the most reputable platforms for data warehousing even the Fortune 2000 world. So we bring it to you. However, unlike our competitors that use programming for SQL Server and competitors using programming means it's complicated, is time consuming to deploy and to maintain. Let's say if in a few years you need to do some heavy duty maintenance because you upgrade your ERP and CRM system, good luck, it's going to take a lot of work. We don't do that. Yes we use SQL Server, yes we do. But we have our own ETL tool. ETL means Extraction, Transformation and Loading that sits on top of SQL Server and makes the deployment and maintenance of the data warehouse much easier, much simpler and almost code free. So easy to deploy, easier to maintain even when you upgrade your data sources. On the data presentation side we use Tableau which for the past four years has been considered by Gartner as the gold standard for analytics platform ease of use data discovery, dashboarding for Fortune 2000. So we're bringing this outstanding analytics platform making easy for you take advantage of not only that, but my team we've been working together for 16 years and in these 16 years we have learned how mid sized companies reporting needs are for multi company frameworks. And then every time we see companies using our technology for some kind of report that can be beneficial for all our clients, we build that into our out of the box solution. And today we have more than 5,000 reports available out of the box. So that's what we do. We make best of the breed technology, easy, affordable, with a ton of reports as a starting point. Let me tell you a little bit more from a technical standpoint. An example of data consolidation at a table level. Let's talk about, let's say GL consolidation. So in this example I'm showing three lines for every line of this table I have a different company database, ERP1, your P2, ERP3. And I'm taking their GL detailed posting table and bringing them together into the data warehouse. And I'm adding a new we call Table id. So for the first company we're going to call CO once as company one, company two, company three and we do this data consolidation in the etl. All the individual tables, they go into a target table in the data warehouse with all the data together. How does it look at the end of the day once we have this mapping? Well, when you look at this table in the data warehouse, it will have all the records from each individual company. So company two records, company one records, company three, company one all them together. Now when I need to do reporting across all companies, all the data have been merged at the table level. And when I'm spinning reports, they're all there. I can filter by one company, two companies, all companies of a group of companies. So that's how the basic concept of how the data warehouse can make reporting of multi company so much faster, so much easier once the plumbing, the data has been put together. Now when you're building reports, a lot of the reports that you need, they are rows and columns, just like Excel sheets or kind of crystal reporting services. And when you pull this data using these reporting tools out of the data warehouse that has been consolidated, the data, it's easy, it's fast and all the data is there. And again you can filter by individual companies, group of companies or all companies to have different perspectives of your multi company system. Now let me talk about Tableau that I mentioned before. Tableau is the analytics solution that we have selected five years ago. And one of the things I love the most about Tableau is because unlike their competitors, most of the competing offers out there, people who designed the product, they were mostly geeks, software engineers that came up with flashy ways to show data visualization techniques. But when you are trying to get insights out of your data, you're doing flashy. You want to get it, you want to understand what that data is trying to tell you. And tableau has been pretty much the only vendor that has hired psychologists and graphic designers to help understand how people look at data and have insights from it. And then they created a software engine that helps decision makers to get it to see things quickly and get what's important. Not because it's beautiful, because it's flashy, because it's insightful. So let me show some of the ideas of how tableau works, what the concept behind it. How about this? Do you need to think, what should I do? As humans, if we get in front of this, we don't think, we just jump out of here. We have evolved to react quickly, quickly to visual cues. And if we didn't have this kind of perception, we probably would have not survived this species. Of course, there's a little extreme example as a snake, but that's what tableau tries to do, is quickly give you insight to make a decision and move forward. Let me show some examples of how tableaut makes it. Simple. Suppose this is my problem. I need to find how many nines are in this table. Good luck. It's going to take me a long time. If I'm not a gifted person that can tell just by looking at numbers, Most of us, it will take many minutes to figure out how many nines. With tableau, that's it. Now I take a quick look. In a few seconds, I'm going to say it's about 10. Simple, beautiful, insightful. I got it. I move on. How about this again? If I try to see the trends, which of these territories are selling the most, which of these products are not so profitable? It's going to take me a while, probably several minutes, maybe half an hour to come with a conclusion. Because we humans are not designed to digest information quickly. With tableau, this information can be shown like this. Now, big bars are bigger sales, so I can quickly tell that this territory is doing really well because the totals are pretty big. From a profitability, if it's red, it's losing money. I can quickly tell it apart. I mean, something would maybe take me 15, 20 minutes now. In a minute or so. I get it. That's what tableau does really well, is give you insights quickly. Now, it's not about being fluffy or being flashy. It's about being sightful. Let me Show Another example. 3D pie charts. Beautiful. Are they insightful? They can be deceiving. Which slices are bigger here? Not so clear. Now, if you put in 2D now it's clear. Which slices Are bigger. Tableau makes it harder for people to build 3D pie charts because they are deceiving. People should use 2D pie charts because they're insightful, beautiful insightful. So tableau excels at come up with techniques to quickly help people get it, have insights from your data. All right, let me make the quick another poll and then we're going to go into the product presentation. So if you don't mind, answer the next poll. In this case you can choose all options. What are your main reporting areas? You can choose, you know, CRM, financials, whatever you want. Just pick all the choices that you want and click Submit. Please. Be sure to click submit. 10 more seconds. All right, thank you. Let me share it. So we have a few people CRM, everyone with financials, a lot of people with inventory, a lot of people with sales and other. Okay, really appreciate it. Let's move on. Product demo finally. Sorry about so much PowerPoint. So what I'm going to show you now is a little real case scenario of one of our clients that has a multi company system and every month the CEO has to show to the board some data. One of the data was this month sales by individual company. The other was well they have marketing in their website and they need to compare website visitors from Google Analytics with their sales and see trends to see if they're affecting each other. The other is regional sales by deal size. So they want to see sales in the US and see how big the sales are by state. They want to see a quick summarized income statement in some other sample reports. So let's go for it right now. I switched to data self analytics desktop and most of the things I'm going to be showing you using the desktop client can also be done using web and mobile devices. So overall work the same way in mobile device. I'll be using my finger instead of my mouse. When you go here you have several connectors that are pulling data from the data warehouse. So all the data preparation has already been done by the technical people. Now as a business person, I come here and I can pick what connector I want to work with and I just do my job. So the CEO has to build the first few reports which are revenues oriented. The first one was looking at sales by company and he also wanted to break down by product by invoice number and whatnot because we're going to be analyzing the data with the board every month. So how do we do it? So here I'm looking at the revenues connector and I have customer information invoice Information, product salesperson, whatnot. These are the numbers that I want to analyze. Well, things become pretty much a drag and drop framework. So if I want to see sales by company, I drag company to my report. So these are the four companies that I have in my multi company system. I want to see sales, so I just drag sales to my report. So right now I'm seeing sales by company, the whole company history. Well, I just want to see this month sales. So, so let me drag the invoice date to my column. Right now I see the breakdown by year which is my sample database only has 40 years. Well, I want to see by month. So let me expand year and now I'm seeing quarters. Let me expand quarter and I'm seeing months. I could expand to days, I could expand to weeks, fiscal period, whatever time buckets you, buckets you have. I can expand into them once the data has been properly prepared in the data warehouse. Okay, beautiful. Now I have all my history here by month. Well, I want to see this month sales because it's my monthly meeting. Well, let me drag and drop the invoice date into my filters shelf and then I'm going to select, you know, I could select different type time buckets. I'm going to choose relative date and then I'm going to choose among the buckets month and this month and click. Ok and voila, that's my report. So this month, sales by company. In the board meetings the CEO sometimes has to enter. What about last month, last year, last quarter. Now that the report has been built, I can come here and say previous month. There it is, maybe the last four months or two months or whatever. So very easy to change the report once you have the report prepared. Now typically the CEO had to show sales by company, by customer, by product and invoice information. It's all drag and drop. If you want to see customer information, I go to customers and I drag customer, let's say between the company and the sales. So now by company, by customer, all the data is here. I want to see product information. No problem. I go to product and I just drag and drop. Let's put after customer. So by company, by customer, by product. And I want to see invoice information again, drag and drop. Very intuitive, very simple. Anyone can do this with little training. Let me drag and drop maybe between the customer and the product. And there it is. Many of our clients have learned how to build reports like this just by watching a presentation like this. It's drag and drop, fairly straightforward. And this is all dynamic Maybe I want to put my company as my columns instead. So now what I have is I'm looking the report by customer invoice, product and companies at the top. Or maybe I want to put my companies in my rows. You just drag and drop and you change the order of your report. Very straightforward. All right, that was my first report. This month's sales details, marketing, sales trends. Now I need another report. In this report they needed to show sales coming from the ERP systems crossing with with website visitors from their website. Now the it worked with our team to consolidate the two data silos into a single data source. That was done in the data warehouse. It was technical, it took some time but once it was done, now we have website visitors as part of my revenues connector. Now with this information the CEO just spin the data. Well he needed to see sales, need to break down by invoice date and he needed to see on a monthly basis. So right now I'm looking at sales on a monthly basis, my whole company history. Well I want to combine with website visitors from Google Analytics. Drag and drop. These are website visitors. Let's make bars and the bottom is sales. Let's put them on a dual axis so it's easier to compare. And that's took a few minutes for the CEO being able to combine this data from all companies. Let me show you here. I have all the companies here and seeing how things are going. Oh, maybe I don't want to see ABC company. Maybe I don't want to see XYZ company. So you can pick and choose and see the effect of the multi company data combined with with Google Analytics data. Completely different data silos. So that was the second report. The third is sales by state. So let me go here and quickly build this one. I want to see sales by state, invoice size and sales. Just pick those fields and put on a map. Let's make a little bigger. Oops, bigger. Let's make it centered. Let's make it a little bigger. That's it. Some financials I have already information fairly prepared. So this is a subsection of the financials consolidated for all companies. All the data is here. Hey, I want to break down by company drag and drop, put my companies in my columns. So by company ID I have the financials or maybe I want to put the company ID in my rows. So for every section I have the individual companies. Or maybe I want to see companies for every company their own financials. Drag and drop, point and click and you get the report. Now assume that I want to have these four reports together in a dashboard, that's quick and easy. We create a new dashboard and I want to put the map at the top, I want to put the trend amounts at the bottom. It's all drag and drop, point and click. Business people can do this. They do not need a technical person to build these things for them. And that's what I meant at the beginning. You need to come up with an analytics platform that is really easy to use. If you can get your business people to become more self sufficient, boy, they're going to be more productive. And that's the goal, is to give them a tool. They can anytime, anywhere access these reports, slice and dice them, and even create new ones from scratch. Now how typically people will be consuming this data? Well, quite often using a web portal. They would log on to a web portal like this, it's highly secured and then they're going to have access to their own reports, maybe every person from each individual company. They'll have an access to the sales reports and when they log into the portal, they will only be able to see their own company's data. While let's say if I'm the owner of five companies like the franchisee, when I go to the portal, I can see sales from my five individual locations, while the manager of each location opens the same report, but can only see his own location sales. And that's all controlled by security. How can we do that? Remember, we're using Fortune 2000 technology. It's really robust, it's really secure, it has a lot of functionality to tackle different reporting needs. That's how we do it. Now when you come to this portal and let's say you say financials, I want to find my financial information. There's a lot of reports out of the box. If I click one of them and let's say I want to drill down into more details, in this case, I go to New York, I click on the bar, I can drill down into balance details. For instance, I click on it, I go to the balance details, I see the balance for New York, I see all the monthly balances here. If I choose one particular account segment, it narrows down to that particular account segment and I see more details. Very intuitive, very fast. This data can be accessed anytime, anywhere. Now, when it comes to distributed information, as I mentioned, people can come to this portal using web and mobile devices. It will be highly secured and contextual to their own data, but they can also choose to receive the information in their inbox. They can subscribe to these views and tell show me this every day. Show me this every month. Every week an email will come automatically into their inbox. They click it and they get the insight. So you need to come up with the analytics platform that will help each decision maker to easily have access to data. If you don't make it easy, many of them are not going to be using and we use Tableau because it has many features that make it easy and make it accessible. All right, let's go back to my PowerPoint to wrap it up. So what are the main benefits? Two main benefits of data self analytics. The most important one, it empowers decision makers. How do we do it differently than the competitors in the mid market? First of all, because we use a data warehouse in analytics platform that is powered by leaders in the gardener's magic quadrant. Again we're getting the best of Fortune 2000. We make it easy, we make it affordable for you. That's one of the most important values we provide. Not only that, but there's more than 5,000 reports available out of the box. So it's not only easy fast, it has a ton of reports as a starting point. So that's a great benefit. Second is it reduces reporting labor by more than 80%. How we do it? Well, first of all, it's significantly easier and faster to build and modify reports. That's a big, big advantage. Second, because of the data warehouse we can automate repetitive data manipulation. Error free automatic, just let the computer do it for your team. And third, because we're using this Fortune 2000 platform, there are many ways we can automate the distribution reports to all of your users Using security context. Every person will receive in their own schedule, only their own information. And it's all secured by this platform. You do not need people to control. Once you configure it, it becomes automatic. So those are the two main benefits. Let me open the last poll which is how was this webinar and I would appreciate if you give your feedback because it can help us improve. So is it informative? Was the PowerPoint session too long? And if you met your expectations and if you want to learn more about data self analytics, please choose your options and click Submit. 10 more seconds. Don't forget to click submit. Okay, thank you very much. Just sharing the results. Most people found informative. No one found the PowerPoint session too long. Many expectations and want to learn more about data self. Much appreciated. Folks, we have about a minute to answer questions. Sorry we didn't have a lot of time to answer questions, but let me check if you have any questions. If you have questions, you can Write in the GoToWebinar panel. Chatting panel. Let me see if I have questions here. We have a bunch of questions. Let me address at least one of them. Question from Fred how long does it take to deploy this solution? Fred, thanks for your question. When it comes to multi company systems, it depends how many companies you have and it depends how the data must be consolidated. If it's a fairly straightforward process, maybe you have five, even 10 companies. But the way we can consolidate is just merge them. There is no additional data manipulation. Typically in a month we can get it up and running. But if there's a lot of data massaging, we need to do a lot of tweaking the data warehouse. It can take much longer. I recommend that we can have one on one conversation where we can learn more details about your multi company setup. Then we can let you know in your case how long that would gonna take. Folks, unfortunately we're running out of time. We got a lot of questions here. We're gonna be addressing them on a one on one basis. This webinar is being recorded so we will be sharing the recording shortly with all of you. I really appreciate your time, your interest in our business. I hope you got a lot of value out of this session. You can share the recording with other people. And thank you very much. Hope you have a great Thursday. Thank you.