DataSelf Analytics for Sage Enterprise Management (Sage X3)

Good morning everyone. My name is John Egiori. I'm Data Sales founder and CEO. Thanks for joining us. Today we'll be talking about BI and data self analytics for Sage Enterprise Management, formerly X3. Our agenda is pretty packed. We'll talk a little bit about some BI concepts, we'll talk a little bit about Data Self. We'll look at a little bit of a product demo and then we'll talk about pricing and open a Q and A session. So from a very high level, what are the main problems solved by business intelligence solutions? One of the most important one is business people. You know, people who need reports, dashboards, people who need to analyze their data. Typically they don't have time to learn complex reporting tools in most ERP systems out there and CRM systems, they provide good reporting tools and even some BI solutions, but they're usually not designed for business people, they are designed for consultants. So typically you'll have to add a business intelligence solution to allow decision makers anytime, anywhere to access their reports and dashboards to being able to license their data, drill down, export Excel, email information using any device that they might have. You know, computer, web browsers, mobile devices. So user empowerment is one of the most important problems solved by bi. The easier to use, the more successful you'll be when it comes to business intelligence solutions. The second problem that I hear a lot is that reporting is pretty labor intensive. Typically when I hear companies saying that they're spending dozens of hours per month, per week, per day in reporting related tasks, that's a lot. And typically a lot of those tasks can be automated by BI tools. What kind of tasks I'm talking about? Well, sometimes data consolidation, you know, people might have data in different tables in different systems, or maybe it's a multi company system, they have different ERPs for different companies, maybe the same ERP for different companies. And bringing the data together to see consolidated financials or sales or inventory planning can be time consuming. So data consolidation is one area that without a BI solution can be time consuming. And typically BI can automate a lot and sometimes 100% of the labor intensive parts of data consolidation. Data preparation. So many companies spend a lot of time doing data preparation, quite often in Excel, people exporting data to Excel, manipulating, refreshing it, recalculating. I hear stories of companies spending even hundreds of hours every month dealing with data preparation. So again, if your company is spending dozens of hours per month, week or day when data preparation, a BI solution most likely can automate most of those those hours. Finally, distribution and security, you Know, sometimes you need to send reports to ten, fifty, hundred hundreds of users and that can become time consuming. All of these labor intensive attacks can be also error prone. So allowing a BI solution to automate those procedures will make it faster, will make it automatic, and usually will remove error prone human mistakes. Speed is the last factor that people usually move into bi. Some reports take just too long to run. That's a pretty common complaint. And too long can be several minutes, can be hours, and sometimes, sometimes even days. In our experience we have this rule that every single report that you provide to users should run under 10 seconds no matter how much data you have, no matter how complex your reporting needs are. That's our benchmark. Every report should run under 10 seconds. Why? Well, because people are not patient today and if they have to wait a computer for more than 10 seconds, most likely many users will now wait and this report will be useless. So we always tell people should to have reports running in seconds and be sure you have a BI platform that can deliver on that again no matter how much data you have. So those are the typical problems that BI solve. Now if you go with bi, today is a great time because there's so many options out there. In a common question that people ask me is should I go cloud or should I go on premises bi? What are the main differences between the two? Well, it's kind of the same as other on premises versus cloud alternatives. Typically if you go with cloud, one benefit is time to value. Typically when we go with cloud solutions you can start getting benefit from BI very quickly. In Data Self's case, it's from a couple of hours to about a day or so. We can get our system up and running if we use our cloud framework. Time to get your people access to their data easily and quickly is a great benefit by going with the cloud approach. Second benefit is low maintenance by having things in the cloud. There's so many different IT procedures that get out of the picture so easier, faster to keep the system up and running current with, you know, the latest and greatest technology, security wise, functionality wise, so very good benefit as well. And the third and sometimes is one of the most important for some users is business people. Again quite often they're not too tech savvy. And if you're using some kind of, you know, VPN or secured access to have access to their own reports and dashboards, many of these business people will not access these reports because it's kind of complex to go through VPNs and additional logins with cloud offers. Typically, as long as you have the proper URL and credentials and you have Internet, you can easily but still securely access your data anytime, anywhere. Now, why some companies go on premises, there's still many that go on premises. The most critical reason is control. Some people don't want to put their data outside of their premises. They want to have a tight control of their data. And that's definitely a legit concern for many organizations, especially when you look at what kind of data they want to keep. Control number one. And typically when they have strong in house or strong IT resources at their disposal so they can take care of maintaining the BI solution, keeping up to date, secured and everything else. So these are the main considerations when you go cloud or on premises. From a high level standpoint, when it comes to BI users, there's usually different types of BI users. There's usually some kind of IT skill set required, use it for the back end system to maintain security, updates and whatnot. Business analysts is usually the second role. These people are usually responsible for creating reports and dashboards, fine tuning the solution to be sure other users, they are not so tech savvy can take advantage of reports and dashboards. What we call explorers are usually business people that want to become independent when it comes to their own data analysis. So explorers are usually users who have access to a bunch of reports and dashboards, but they can easily, and they've gone through some training, so they can easily slice and dice their data, drill down, even build new reports from scratch. So that's kind of the explorer user. Their job is usually not publishing to other users. That's more for the business analyst, but they are independent business users when it comes to exploring their own data. Then we have the viewers. Viewers are typically users who are not very sophisticated when it comes to BI features. So they will have access to reports and dashboards. They can make simple changes like no changing filters, simple drill downs, but that's it. They're not too savvy to explore beyond what's being preconfigured by, you know, business analysts or explorers, but they still have interactivity with their data. And the last type of users is what we call static report users. These people, they do not need to have interactivity with reports, they just need to receive reports by email, some kind of PDF format or you know, in a portal on a schedule basis. So usually people that only check this information once in a while and they're not interacting, those are static reports. Typically in any BI deployment there are some or all of these type of users. In our experience, usually it is one to people. Business analyst is one to five. Explorer is usually 10 to 20% of the total user. Viewers is usually 20 to 50% of the users. In static report users usually 50% or more depending on the organization. So this varies a lot. Now how can you improve BI user engagement? This is usually a big topic for many organizations investing in bi. In many of them, they have challenges getting people to actually look at the reports. So historically there's two main ways to get or to kind of push engagement. In a way you can have the top down approach versus the grassroots. For a long time the top down approach was the way to go. Pretty much, companies would try to enforce and push users to embrace new reports and dashboards. More recently in the last five, 10 years, the grassroots started to get more traction. And the idea is just give BI tools for the people who really want it. And as these people start to become successful and do better in their job, be more effective, slowly but surely other users will get to know about it and will start to ask to be part of the process. So the grassroots takes a little longer sometimes to get user engagement, but usually it's stronger. You know, you'll have more people actually wanting to use instead of, you know, being told to use. Every organization is different. We see, we continue to see success in both approaches and things in between. And it's exciting to see and help organizations figure it out which approach is more successful for each one of them. The other thing is at the beginning especially keep it simple. Don't push a lot of things to most users, just try to send the broader range of users a small number of actionable key performance indicators. There's so many people out there, there's not so data driven or at least they don't look for data per se. But if you show them something that they care, something that can change their daily activities, that can make them sell better or cut some costs, if you can help them one day to do better, that's when the hook really happens. You'll see, wow, this reporter dashboard can really help me. Then usually they go back to the item and say, what else do you have for me? So keep it simple. Keeping a few reports, actionable information that can help these busy, successful people do better. And slowly but surely as you keep on doing this, you'll have more users. So you know, KISS approach, keep it simple usually is a way to get a strong, steady evolution into getting into more users. Finally is be mindful of individual preferences. If you try to get some people Everyone to adopt the same approach, you know, maybe is go to this web portal to get to reports or open this PDF report or download to Excel. If you only provide one or two options to access these reports and dashboards, I can almost guarantee you that many people will not engage because that's not their preferences. Some people will stick to Excel as long as they can. Some people just want to receive a PDF in their email, some people like to use it in their mobile devices. So having a BI platform that provides you many options for user engagement and then as you go through the training, you show people the options so each one of them will find what option works best for them, is usually an important component to make using user engagement much more solid and growing over time. The funny thing is, as users start to get value from BI through their own preference method, quite often they start to experiment into other methods. And sometimes someone that would always work in Excel, sometimes they drop Excel altogether and they move to something easier and better. So the idea is show them value, show them the KPIs, the metrics, get them more successful and then they'll be more open to see what else can you help, what option you have to provide me with this data. When it comes to accelerating BI return on investment, a lot of companies, they start their BI projects from scratch and I see this a lot, usually takes months to get a little bit of progress and it's exciting as they get progress like maybe like a handful of dashboards. Some of the challenges with the start from scratch is time usually takes a long time to tackle a few of the reporting needs. And the longer it takes to get something done, the more likely other priorities will come to the plate and will delay the project further. Sometimes the people involved in the project, they change and now the whole initiative, you know, go down the tubes and you have to start all over again and you just forget. So start from scratch works for many organizations, but is usually slow and is very prone to interruptions, you know, just failure because it doesn't have continuity. As long as you have a strong team that is dedicated, that is working, you know, focus on bi, it works well, but keep an eye on getting too long to get value. The alternative is finding off the shelf BI solutions out there that can connect to your data sources and quickly give you a much bigger, better head start. There are many companies out there and of course Dataself is one of them that has been building out of the box solutions that on day one you don't have a few reports as a starting point. You have a lot. So it's easier and faster to ask decision makers what would you like to see out of your reports and dashboards? And quite often you don't get a solid answer. They haven't thought really well about it, or they cannot articulate exactly what they want. And if you show samples or some of these reports available out of the box designed by companies that only do this, business people say, oh yeah, yeah, I need to see this. How about you tweak there? Cool. When you show something that is close to what they need, they can engage in the conversation, they can be creative and then help together as a team to fine tune each reporting dashboard to be exactly the way that they want. So off the shelf solutions usually provide a lot of value at the beginning. It provides inspiration and make the whole ROI come much more quickly, sometimes even in days or weeks. The investment BI is paid because business people can start getting value much more quickly than starting one report at a time with the start from scratch approach. So let me talk a little bit about Data Self analytics now. What I covered so far is generic concepts about bi. This is the architecture of data self analytics. So on the far left you would have Sage X3 other data sources. Maybe you have social media data that you want to analyze. Maybe you want to have Salesforce or CRM, Excel spreadsheets, other databases. All of these on the left would be source databases. What we do with Data Self is we bring your source data into a SQL Server data warehouse. This is a little bit of a technical job, but it's something that is done behind the scenes, bringing the data, consolidating. You might have a lot of data, you might have multi company, you might have multiple systems. No matter what your data situation is, the data warehouse is a platform where we can clean the data, optimize the data and make it easier and faster for users to retrieve data from it. The leading way we're using to pull data from the data warehouse is using a product called Tableau. If you haven't heard about Tableau, Tableau has been rewarded as the gold standard for analytics for the past six years in a row by Gartner. You know Gartner is a very reputable company doing technology assessment. And again for the last six, six, five years in a row, Tableau has been considered the easiest to use, the most empowering analytics platform. And we have built more than 5,000 reports, dashboards and KPIs out of the box for Sage X3 and several other ERP and CRM systems. The idea is on day one, once we deploy the out of the box solution, clients benefit from a lot of reports. Looking at financials, looking at sales, inventory, purchasing, projection, budgeting, CRM, social media. There's a lot of things that are out of the box so you don't have to start from scratch one at a time. You have a solution that has been evolving for about 14 years with reports and dashboard that again on day one will give you value. What are the key benefits of Data Self? So ease of use is the most important one. And because we use Tableau as the user interface, this is one of the most empowering reporting platforms. When it comes to empowering business users to take their data anytime, anywhere and run with it. You know, slice and dice it, drill down, export it, creating reports from scratch, it's really impressive. How easy to use is the Data Self analytics framework? Second, again, there's a lot of reports out of the box and we'll talk more about this in the next slide or so. The third is data consolidation. You know, sometimes when you look at, you know, sage enterprise management solution, you need to bring data from different modules inside of the ERP system. And if you don't have a data warehouse like ours, that becomes a complex and time consuming process. Or maybe you have a multi company system or maybe you need to combine X3 with another database like Salesforce or social media. Because of the data warehouse, we can easily bring the data together and when users go to look at their data, it's easy and I'll show that a little bit when we go to the product presentation. Finally we we at Data Self, we have a team that has been working for more than 18 years together doing enterprise analytics. And typically we can help clients by understanding their needs and assessing and helping them to take advantage of the out of the box and more quickly getting their data analysis fulfilled on day one, not six months down the road. So the expertise of knowing the data sources, knowing SQL Server, data warehousing, knowing Tableau, knowing the out of the box and knowing what kind of reports clients usually ask, we can usually help companies get value very, very quickly. Success story that I like to talk is the CFO of one of our clients. He changed to a different business last year. Then one day he called me and he said, you know Johnny, I want, I'm going to go through my second Data Self project and this time I want Data Self to be deployed out of the box on day one instead of like my last project where I asked for some complex customizations and it took you guys months actually five months to get the job done. In my first project when I asked for this complex customizations, I was patiently waiting and when I got those customizations five months down the road, I loved it. It was awesome. Right after I got over this hump of getting my customizations done, I decided to look the out of the box solution from Data Self and what else they have that could be of value. He said that right there as you start to look at the out of the box that was ready five months before, he found a report that showed him some major issues in their inventory processes. If he had seen this report on day one five months before, he would have said forget my complex customizations, we have bigger fishes to fry. So he said I don't know what I don't know and data selves out of the box can give me a lot of insights into things that I don't know. So just put me in the driver's seat on day one. I want to be engaged. I don't understand IT databases, no, but I can look at my data. I can see what's ready to be analyzed and what's not ready yet. But look at my data. I can tell you the BI experts what the real priorities are. I want to be the driver's seat this time. Since this particular story we actually started to tell all of our new prospects. Let's make phase one just deploy the out of the box just as is and start showing a few decision makers how their data is looking today. And those decision makers that are okay looking at data that might not be completely ready but are excited to be part of it because at the end of the day is about what they want. They can help us, the BI people to push out to other users data at the right pace, in the right format and as clean as necessary. So this is an interesting story that has changed our life. And since then most of our projects we start with the out of the box which usually takes again hours or days to deploy. And from there decision makers will drive the process and tell what else they want out of it already. Let's switch into a product presentation. So now I'm going to the data self analytics portal and I using right now our cloud based or AWS based portal. The same framework could be installed on premises but overall once the system is up and running, users will log into the system using web browsers. There's a thick client for those who want to work on Mac and Windows PCs. There are also mobile device native apps for Android and iOS. But the idea is let's say I'm going to play the scenario of being the CEO of this organization and when I log into Data Self Portal, one of the things that you know, C level people want to see is a what we call a 360 degree view of their own area. You know, if you're the CEO would be across the whole organization if you're the cfo, maybe only the financial side of it, if you're the COO would be operations. Anyhow, the idea is to have a dashboard that can be busy. Like this dashboard here particularly is pretty busy, sometimes much simpler, sometimes it's much even busier. But the idea is C level people, they are very unique and typically you have to tailor the dashboard specifically around what they want and allow them to quickly see this information. Let's say every day when you start the morning, if there's anything really good or really bad, they usually want to take an action. If everything is humming, they quick look at this dashboard, they don't need to do anything else, they move on. I have a lot of the C level people in my client base that do exactly that. They open one or a few dashboards early in the morning and if everything is good, they do nothing. If anything is happening, that is they need to act on. They do some drill down, they do some licensed and they email or call someone. They take some action right there at the early in the morning. These dashboards must be easy to use, must be visually informative and interactive. This particular one has this cash flow. Here it has a bunch of other piece of information, financial sales, Google Analytics and on the cash flow, let's say I want to see this is the inbound money coming from receivables, outbound money going for payables, money from payroll, cash on hand today when you add along this 60 days, all the ups and downs of your cash you have the projected cash flow. This example, as long as the most negative amount doesn't cross the line of credit, you don't have a cash flow problem. And we can allow people to do what if scenarios. Hey, what if this customer is disputing this payment? What's going to happen with my cash flow? Well right here I can say excluded particular payment. Right now I remove the payment and I just cross my line of credit, I'm going to have a cash flow issue. So these dashboards must be interactive to allow users to see what would happen in case something changes or maybe hey, there's red bars. Red bars means something is not good. Like in this example, maximum hand for this month is above the threshold. What's going on here? Well, I can click on this bar and the tool will automatically drill into this other tab. I was in the original tab. Now I am in the inventory tab giving more details. And here I have the aha moment. My west warehouse, there's a bunch of these red bars, which is too much inventory on hand. Aha. Now I want to do something about it. I want to call, I want to email the person responsible for this warehouse. In real life, sometimes things get hard. Who is the person? What is their phone number? What's their email address? Maybe this could be a customer that you need to contact. In these dashboards, we can actually create actions where you click on a label and you can, let's say, call or email the person associated to that label. Again, this could be a customer, could be an account manager, could be a vendor. And if you're doing this from a mobile device. So this dashboard is the same as this one that I'm showing. But on a mobile device, it's very simple to click on a label and place a call. You just click, choose, call the person and place the call. So from the inside insight, you know, from the aha moment to take an action, this tool provides different ways for people to take that step quickly, easily, right there on spot. Now, if you were to be, let's say, a person from the finance department and you want to analyze your P and L, your new balance sheets, things of that nature, we also cover financials with a lot of functionality. Like here I have a simple P and L looking for a given year. I can easily drill down from the year to go to the month to the period levels. Or maybe I want to see how I'm doing year over year. So right now I just put, you know, four years side by side. If I want to see a variance, I just add the variance and I see it right there. Very easily, very quickly you get these variations. And if you want to drill down and see more details, you know, let's say I'm looking at 2018 information and look at payroll. Something is good or bad about payroll. I want to drill down all financial reporting tools that I know. When you drill down into details, you go to a different page, you're no longer looking your P and L, you're on a different page in the details. And if you get distracted when you're analyzing those details and when you get back to your analysis, sometimes you forget why I was looking at those details. So we just came up with this. You know, we call single Page analytics, which is a way to keep the main report available and then drill down on the same page. So if I click on payroll here, what happens is I'm still looking the P and L, but now I'm going one level down, looking at debits, credits and posted for all the accounts, all the periods and details for that particular bucket in my P and L. And then if you want to go down even further, I want to see, you know, batch numbers, transaction days and whatnot. You know, this is still at the period level. I can click a button and then the tool can expand and show now transactions one day at a time. All single transactions that were roll up into each number are available. And then, you know, if you're looking at some analysis here, looking why the heck this is going on and you get distracted, you get into a call. When you come back to this analysis, you can remember where you started, you can see where you stopped, you can see what the filters applied. And it's so much easier, so much easier to continue with your line of thinking. If you don't have this whole thing in front of you. Sometimes you have to go back to the beginning of your report, look around, oh yeah, yeah, I was looking at payroll and start all over again. So single page analytics is a way to allow users to quickly and easily don't get lost when they are analyzing the information because everything can be showed on a single page. My last example that I want to show out of the box and everything that I'm showing today is out of the box available for Sage Enterprise Management in other ERP systems is on the sales side. So this is a sales dashboard showing major KPIs that each salesperson is responsible for. You can look at, let's say of opportunity information from your CRM system, like maybe salesforce, sales, CRM sales logic, things of that nature. You can see actual sales and commissions for the last couple of months on a daily basis and how they're accumulating. And you can also have what we call the hot and getting cold performers. The idea here is if you're selling frequently to customers and products you see want to see who is hot or what products are hot or where in the country in the, you know, in the city is hot. And by the same token, what's getting cold? So if I click who's hot here I go to a different tab, the who's hot tab, showing out of the box. Two ways that we show who's hot. One is top customers by sales this period. So these are the Top customers growing the most this period, and this is the period that I'm looking at is. And these are the customers growing the most since last period. So since last year to date to this year to date, these customers grew the most. Maybe they're not big enough to be here, but they're growing very rapidly. Therefore we consider them being hot. We have the same perspective for products, for locations. You can easily change the periods here. You can change different ways to slice the data. You can see a different measure. Maybe you want to see by gross profit. You just change the measure and the report will show right off the bat. Now showing top gross profit and gross profit growth quickly here. If you want to see where it's hot, you can look at maps. If you want to see who's getting cold, maybe some clients are declining in business, maybe there's something wrong about it. And if you get to know that these clients are declining in a timely fashion, you might be able to reverse the trend. So here we have reports showing customers who are getting cold. And as they put the mouse over each customer, it shows in the middle section what products are driving the biggest decline. Now the top right is who's no longer buying at all, they're buying less, period. In this case, again last year to date, but they're no longer buying. Is there something wrong about it? And all of these things are very visual. However, if you want to see numbers by the penny, you can also pick a few customers and click see details. And now you go to report that shows information on a tabular format. Alrighty, let me go back to my PowerPoint now to show some other things from a pricing standpoint. Let me talk about the entry level pricing. So we have a solution called Quick Start that starts at 499 per month. We have a pro edition that is $9.99 per month. We have an enterprise edition that is $1,699 per month. There's a variety of components that play into which one might work for you. We have many clients with hundreds of BI users that started with pretty much with a Quick Start edition. So you don't have to go to the enterprise unless you have a lot of data or a lot of different reporting needs. And it must be covered. User count plays into the picture. Yes, it does. But again, as I mentioned, you can have lots of users and still use Quick Start and Pro. You don't need to go enterprise no matter how many users you have. If you have more questions, of course we can talk on a one on one to assess your needs and see which enterprise edition would work for your needs as next steps. If you want to learn more, I encourage you to go to dataself.com There's a lot of materials if you want to discuss your needs or maybe your clients needs. If you're a reseller, feel free to email to salesataself.com or call this phone number and this is my extension. This webinar is being recorded and we're going to make it available for you. So watch out for an email coming from us in the next day or so that you'll be able to download this webinar or share the recording with other people in our website. This is dataself.com some of the most popular areas here is if you come to our homepage and scroll down all the way to these green buttons, the architecture will show the architecture that I showed you that has our data warehouse and the components. This button which is a 5000 reports KPI's. It's a very I just clicked on it. It's a very popular page because it shows how many reports and dashboards we have for each area like for CRM, for Core Financials, for ERP distribution and if you click on the samples buttons you go into different pages showing some example of the reports available out of the box. So just click on the essays, the sales samples. We have more than 1300 sales reports and dashboards and here you'll find a few dozen available so you can have a taste. You can also click the Try it now fill out the form and you'll be able to also take a peek on how the solution works. This Try it now uses our sample database, but it's a good way to have an idea of the out of the box and how easy it is to customize it. I'm going to open we have a couple of minutes to do questions and answers so if you have any question please use the Zoom meeting panel chatting box and let's see if I have any questions that has been posted already. I have a question here from Laura. So Laura is saying we have a lot of Data in our X3 in our ship to sales reports run very slowly. How do you address such performance issues? Laura, thanks for your question. If you could just put in the chat what tools are you currently using to run your ship to sales reports? Because that can help me elaborate a little further. But yes, we have a lot of clients or prospect that come to us complaining exactly about performance issues and when I showed back then let's just Go back here. When I show back then about this 10 second rule is, you know we do use an enterprise grade BI engine. You know, our solution even though is inexpensive and it's quick to deploy. But our engine, the guts of it, has been designed to work with Fortune 2000 companies. So it doesn't matter how much data you have, it doesn't matter how complex your reporting needs are. We use data warehousing and analytics like in our case so far tableau to look at what you're trying to do and if the out of the box doesn't run quickly, we have the expertise to look at the pieces and tweak them, fine tune them. And rarely this rule doesn't apply very rarely. We guarantee all or almost all of your report will run under 10 seconds no matter how much data you have. By the way, thank you for letting me know that you're using SCI for your reporting tools. I cannot talk much about SCI per se. Actually so far all of our clients that are x3 they came from having SCI and they were complaining that was too complex, it was too slow and we did ourselves, those complaints were gone. I don't know why or how, but it's not uncommon for us to get prospect that were working with SEI and being not too happy with the ease of use and performance. But I guarantee now we can talk more details later to see exactly what you're doing and even potentially give some tips. What potentially you could tweak in your current BI to hopefully address. Sometimes it's using or tweaking the right dial. Sometimes. Yeah, you need something like dataself to really tackle complex and large data volumes. We're running out of time. We have more questions but we'll address them on a one on one basis by email. Let me just put here my last slide. So here's my name again with my contact information. I really appreciate for you joining our session today and as I mentioned the next day or so you should be receiving a copy of this webinar. Feel free to share with your colleagues and peers. Thanks for joining us and have a great day.