BI for the Masses

KAREN:           Hi and welcome to the webinar “BI for the Masses.” My name is Karen Warner, and I’ll be your moderator today. Before we begin, I’d like to introduce you to our two speakers. First, I’d like to introduce Chris Wintermeyer. Chris is a Senior Director of Enterprise Solutions at Domo and has spent over 20 years in the business intelligence industry. Next off I’d like to introduce Michael Locke. Michael is a Senior Analyst covering business intelligence at Aberdeen. He’s done a considerable amount of end user driven back base research in the area of business analytics. And with that, I’d like to turn things over to Michael.

MICHAEL:        Great, well thanks very much Karen, and welcome to everyone joining us today. I’m delighted to have the chance to speak with you. I firmly believe that business analytics is the single most important activity that one can engage in, in today’s business world, and I think this not because of some business book that I’ve read or any particular blog that I follow but because of the conversations that I’ve had and the data that I’ve collected from folks just like you who are listening today—end users who have experience with business intelligence and analytical activities and have talked about the tangible and measureable business improvement that they’ve seen with effective analytics. What I wanted to do today is share some of the results from a study that I conducted earlier this year into the business impact of analytics.

In today’s business climate more and more line-of-business,, non-technical decision makers are adopting that analytical mind set and leveraging the right tools in order to make faster decisions and ultimately drive substantial performance and progress as a result. So just to take you through a quick agenda for what I’ll be discussing today, I wanted to start by setting the table with some background and discuss some of the most notable trends coming out of our business intelligence research today. Then I’ll take a step back and briefly go over Aberdeen’s research methodology just to put into context the data that I’ll be presenting today. Then I’ll jump into the heart of the research findings and talk about this emerging concept of pervasive BI. Finally, I’ll finish up with a few recommendations and takeaways that have shown to be impactful for organizations leveraging business analytics.

As an analyst covering BI and business analytics, I’ve sort of been hit over the head with three trends that have recently been coming out of the research. Essentially (1) more data, (2) more users, and (3) less time. Let me expound on what I mean by that. Any decision makers who rely on data to help support decisions are typically seeing more of that data, and it’s becoming more complex. The research shows that companies on average are seeing a 40% year over year increase in the volume of data that they use for analysis, which personally I think is conservative. I think it’s actually higher than that. This happens to be a weighted average. And they’re pulling that data from an average of 14 unique different data sources. So there has been a substantial increase in both the volume and complexity of data.

Second, there are more users. When I speak to folks in the end user market place and talk about business analytics, they’re consistently telling me that across the business more functions and more job roles within each function are raising their hands and asking for analytical capability to support better decisions.

And finally, there is less time. We’re consistently asking our community how quickly they need information—what is that decision window or the period of time where information can effectively be used to support a business decision? Whether it’s real time or more likely hourly or daily, that window of time is shrinking for these decision makers. Some key questions that we want to answer with the research is the why, the what, and the how of business analytics. Why does it matter? Why are people investing in BI? What’s in it for me? What’s the performance enhancement potential of BI that I can expect if I’m doing things the right way? And how do I get there? How do I become a “best in class” company when it comes to business analytics? That’s what we want to talk about today.

So what I first want to do is talk a little bit about Aberdeen’s research methodology. The first half of that methodology involves understanding end user behavior and the end user mind-set, and we do this through a framework that we call our P.A.C.E. Framework. We see on the slide up here the different areas of Pressures, Action, Capabilities, and Enablers. Whenever we talk to the end user market place or launch a survey, we’re always asking questions around these areas. What are the top business pressures that are driving them to invest in business analytics? What are the actions that they’re taking from a strategic level to address those pressures? What are, the capabilities and the competencies that they’re building in order to help execute on their strategy? And the enablers—the E of P.A.C.E.— what are the technology categories, the key enablers that help support those capabilities and ultimately help them execute against their strategy.? This helps us understand what keeps the end users up at night and know what they’re doing about it.

The second half of our methodology is what we call our Maturity Class Framework, and this is really all about understanding performance and what they get for their efforts. What we do is we ask them, in addition to asking them questions around those four P.A.C.E. areas, questions around key performance indicators (things like revenue growth, user satisfaction, timeliness of information), and we take our total respondent pool (and in the case of this particular study that pool included 231 end user organizations), and we score them based on their response to those performance questions. The ones that score in the top 20% are we what call “the best in class,” the middle 50% are what we call “the industry average,” and then the bottom 30% are the “laggards.” And really how the research is framed is essentially to help educate end users in the market place to know how they might alter the way that they deliver business analytics and the way that they make decisions in order to move their organization closer to a “best-in-class” company and, more important, achieve that level of “best-in-class” performance.

So let’s start to answer that first question of why, why does BI matter, and what is it that’s driving companies towards business analytics? Here we’re looking at the P of P.A.C.E. that I described before, the pressures. What are the top pressures that are driving companies to invest in BI? The first one comes up all the time—critical decisions rely way too much on gut feel. Companies are increasingly looking to augment their experience and expertise with timely, fact-based insights that can help support their decisions and supplement their expertise.

Second is a concept that we’re going to be talking about a lot today, pervasiveness. As I discussed before, there is a trend of there being more uses— a growing number of decision makers need or want analytical capability. More and more folks across the organization at multiple functions and multiple roles within each function are raising their hands and saying, “I want the ability to make better fact-based decisions. In addition to supporting those decisions with my knowledge and experience, I want to be able to do it with data.” They also feel that they have poor visibility into what’s going on in the operation. They feel like they don’t know what they don’t know. They don’t have the ability to identify and act upon business opportunities, revenue growth, and profitability, etc. They’re looking for business intelligence to help them do that.

The last pressure is this concept of there being less time, so the time window for decision making is shortening. “I need it by the end of the day” has transformed into “I need it within the hour.” “I need it within the hour” is now “I need it within ten minutes.” So this decision time frame is shrinking as well.

This brings us on to the second half of this question of why. What is it that people are using business analytics for? Well, at the end of the day, business analytics has the ability to support improvement in the metrics within our businesses that really matter the most. And when I say the metrics that matter the most, this is not my opinion. This is the opinion of end users. This is a question that I asked in a survey which is essentially, “Of the following 14 or 15 line item financial statement metrics, which are the ones that you care about the most? Which do you feel are most indicative of business performance?” And perhaps, not surprisingly, we see revenue come out on top here by a large margin. But bear in mind, there’s only one (unless we’re being nit-picky here) type or revenue. There’s multiple types of profit and cash flow, and that’s really what we’re seeing here. People are really interested in essentially two buckets. The metrics that we see up here on this slide fall into either the growth bucket or the efficiency bucket, and when we say growth we’re talking about revenue growth and business growth.

But the rest of these are really focused on efficiency: generating more cash flow from operations; EBITDA, earnings before interest tax depreciation amortization; operating cash flow; net income; and operating profit. All of these metrics are geared towards creating a more efficient business. And this is really what matters. This is the business scoreboard, and this is what people are looking to business analytics to help support, performance and improvement across all these metrics. This is really the why and the meat of business analytics.

Which brings us to the what. What is it that they get for their efforts? How are they performing against their desire to improve these metrics? Well, it turns out for “best-in-class” companies (that is the companies that perform in the top 20% based on those metrics that I described before) there is a very, very strong difference in their ability to perform against those metrics. What we see here is that these top performing companies, when it comes to things like organic revenue, operating profit, and operating cash flow, on a year over year basis they’re generating double digit percentage growth across all three areas at a rate that outstrips their peers by more than double in all of these cases: a 27% year over year improvement in organic non-acquisitional related revenue, a 23% year over year increase in operating profit, and a 21% increase in cash generated from operations. That shows an ability to perform against that business scoreboard. What we see here is the “best-in-class,” or top performing companies, are leveraging BI to help support this type of growth and this type of top level, top shelf performance.

So now we start to look at the how. How do “best-in-class” companies get to this level of performance? What separates their strategy, and what are the characteristics? Here we are looking at the A of P.A.C.E., the strategic actions the “best-in-class” companies take. Once again, at the top of this list, we see this concept of more users. “Best-in-class” companies are looking to enable more business decision makers with that analytical capability spread it across the organization to more functions within the organization, more user types, thus making the solutions and, more important, the mind-set more pervasive within the organization. They’re looking to take their operational and their strategic key performance indicators and really align them to the overall corporate goals. So whatever the business has set out as its top priority, whether it’s growth or cost reduction or what have you, they’re looking to align their key performance indicators from an operational basis to those goals so that they can execute against them at the end of the day. They’re more likely to align business analytics as a strategic priority. Something that we see all the time is that “best-in-class” companies are more likely to formalize a strategy for business intelligence within the organization, not just necessarily the deployment of an analytical tool. It’s about that mind-set; it’s about building that desire for data-driven or fact-based information, building that culture within the organization. But they’re also looking to deliver capabilities that best meet the needs of their users, whichever types of users they may be. They’re looking to align the analytical capabilities that they deliver to the people that are going to be using them. So those are some of the top strategies for a “best-in-class” company.

Following on this topic of pervasiveness and how “best-in-class” companies are able to get to that level of performance, we asked our survey respondents to rank the depth of business analytics in each major business function on a scale of one to five , with one being no analytics in place and five being highly pervasive usage of business analytics within that particular function. What we found is that “best-in-class” companies were able to achieve a higher level of engagement and usage of BI across more departments within the organization. So whether we’re talking about corporate management or finance or sales, the “best-in-class” have been able to drive a deeper level of engagement and usage of BI internal to their organization. But the other thing that was interesting that we found is that this concept of pervasive BI really has multiple dimensions to it. What we’re looking at here is the dimension of internal pervasiveness, and we’ve seen how “best-in-class” companies were able to make it more pervasive to the departments within their organization.

An interesting finding that came out of the data was that “best-in-class” companies are also able to equip external elements of their external or extended enterprise, so the second dimension of pervasiveness is a emerging use case for BI, delivering these capabilities external to the core of the organization and again that external or extended enterprise. So whether we’re talking about customers, suppliers, distribution partners, or even in some cases regulators, the research shows that “best-in-class” companies are more likely to share analytical content and capability outside the inner walls of their organization. While “laggard” organizations, as we see in the chart on the right, are much more likely to report no external BI collaboration at all. I’ve always said that there’s an enormous amount of power in business value data, but there’s even more value in the proper interpretation of that data, and this is where we see “best-in-class” companies really have a leg up. By creating these analytical linkages, both internal across multiple departments and externally to the extended enterprise as well, “best-in-class” companies are able to incorporate expertise and perspective from a variety of different leaders within and without their organizations, ultimately leading to stronger analysis and better decisions as a result.

Finally, when it comes to BI and analytical capability, what are some of the tools that “best-in-class” companies use, and how are they getting them into the hands of their key decision makers? There are two technology categories I wanted to highlight here. The first falls into the category of automation. “Best-in-class” companies are more than twice as likely as all other companies to automate the creation and delivery of key reports. This enables them to get that business insight into the hands of decision makers while controlling the frequency and the content of that insight. Ultimately fewer key metrics in the business slip under the radar, and decision makers have better opportunity to decide and act upon business opportunities. Second, “best-in-class” companies are more likely to use data cleansing tools to improve the quality and the usability and the consume-ability of their data, ultimately increasing the value of that data and supporting more trustworthy decisions as a result. “Best-in-class” companies are also using multiple channels to get that BI-driven insight into the hands of decision makers. Embedded BI is increasing in prevalence according to our research.

So essentially when analytical capability is included as a module or extension within other enterprise applications, whether it be ERP, CRM, or other niche industry or job-role focused software products, typically this is an attractive option, because it offers BI the ability to piggy back on top of an existing, already accepted, and hopefully well adopted tool. Software as a service, or Saas, based BI carries similar benefits. As a web based tool, familiarity is higher and therefore supports a higher level of adoption for the tool, but this approach also typically offers shorter deployment times and more flexible cost structures as well. So “best-in-class” companies are judicious and smart about the tools that they use to deliver insights to their organizations as well as the pathways that they’re taking to deliver that insight.

I have just a few recommendations and takeaways to leave you with. As you think about your analytical strategy, whether you’re just starting your journey with business analytics or you’re looking to build upon an existing implementation, these concepts have shown to help improve the pervasiveness of BI and support higher business performance as a result. The first one is, really take stock of your analytical needs and understand who within the organization needs what data, what their requirements are, and what the decision window is across the organization. For some operational decision makers it might be true-real time or near-real time. For other, more strategic decision makers it may be weekly or daily type of latency requirements when it comes to delivery of that actionable information. “Best-in-class” companies use things like formal user polling processes and other ways of understanding what it is those needs are.

Second, I recommend focusing on right time not real time. As I talked about before, this concept of the decision window varies from company to company. It varies from industry to industry. It varies from person to person. So understand that whatever the concept of right time is, it’s important to deliver that information within that time frame whatever it may be. For the users that have the strictest requirements on whether it’s real time or near real time or whether you’re talking about within the hour or within the day, what the research shows is that in “best-in-class” companies, 94% of the time have access to information within that time frame versus only 40% for “laggards.’ So there is a lot of the late information in “laggard” and “average” companies.

Lastly, I recommend empowering the business users. This is a little bit of a fuzzy recommendation here, but the growth of business analytics and business intelligence is coming from those line of business users, whether it’s in some more traditional functions like sales, marketing, and finance, or whether it’s in some of the growing or emerging use cases for analytics such as a backend function like procurement sourcing, inventory management, or even in some cases human capital management. There’s been a lot of movement in the area of HR analytics and talent management, things like that. The ability to deliver self-service capability to the users, make them more self-sufficient within their ability to ask questions of the business and generate meaningful insights, is becoming more and more important. “Best-in-class” companies are much more likely to have their user base, or a larger percentage of their user base, having that self-service capability around BI without having to rely on IT to deliver that insight to their best line of business decision makers.

So that brings me to the end of my portion of the presentation. What I’d like to do now is go ahead and hand things off to Chris Wintermeyer from Domo. Chris.

CHRIS: Thanks Mike that was great information. I was very shocked, but at the same time not surprised, to see on one of your last slides that less than 10% of the “laggard” companies have pervasive self-service BI, and I think that’s very telling. This is all about being able to deliver more data at the right time to more users, to be able to make the right decisions, and I think that message came through loud and clear in your slides. Everyone, thank you for joining and for sticking around to hear my portion. I’m Chris Wintermeyer, Senior Director of Enterprise Solutions at Domo. And what I’d like to do is take the new few minutes to talk to you about how Domo can address the needs of your organization’s business intelligence requirements specific to many of the points that Mike just talked about in his presentation. Domo is based on the premise of delivering a new form of business intelligence so that people can view and manage their business with information coming from all areas of the business, regardless of what device I’m using to actually get there, and do that in a way that is intuitive, informative, and easy to use.

If you look at business intelligence on the market, and if you’re watching this webinar, then you most likely not only use this intelligence but also probably hear from different vendors and different parts in the BI industry in terms of messages that are out there. It seems like most of the folks that I talk to, certainly in the enterprise accounts, ask me this as one of their very first questions, “Why do I need another BI tool? I’ve already got so many.” And that’s really where I want to focus the majority of my effort today, explaining to you where Domo fits into the picture, regardless of whether you’re just getting started in the world of business intelligence or you’ve already got a dozen or more systems already in place today to deliver information to your users.

And if you look at one end of the spectrum we typically look at what I like to call the full stack vendors. These are the folks that provide a little bit of everything, and this can range from data movement in ETL to metadata to master data management (MDM) to the construction of maintenance of data marts and data warehouses on through things around ad hoc and scheduled and broadcasting of reports out to one or more users within the organization. Although these full stacks offer a great deal of functionality, because none of them was architected specifically to do all of that from the ground up (in most cases individual pieces like ETL or visualization was added later), what we find is that the stacks tends to do a lot of things but don’t do any of them exceptionally well, and that’s certainly true from a visualization perspective. In my 20 years in the industry I’ve seen a lot of what folks call dashboard or visualization solutions out there, and while some of them are more compelling than others, one of the biggest challenges is trying to fit that visualization solution into that BI framework that the full stack vendors force you to use to be able to deliver information visually.

And on the other end of the spectrum we tend to focus on the desktop data analysis tools. They do exactly what they say they’re going to do, they are desktop data analysis tools designed for, well, data analysts. They’re built specifically to allow a single user or a small group of users, maybe even a department, to get access to do deep dives into the data, to start exploring the data itself. This solution is excellent for its intended purpose, which is to be able to go in and explore your data and determine what it is that you want to measure and then determine how you actually want to deliver that out to the combined users within your organization. A lot of times I’ve seen shops that will take these departmental solutions and try and push them out to hundreds of users simultaneously, and in almost every case those solutions fail. They just simply fall on their face. And the reason is these departmental solutions were never architected to deliver information to large numbers of their current users, and they also weren’t necessarily designed to deliver information in an intuitive way for the average business user who simply needs to consume information, do a little bit of slicing and dicing, maybe some drilling down the detail. Where these solutions excel is with somebody who understands the data and needs to do a great deal of exploration. But I don’t want to have to train my users to be able to use the dashboard. I should be able to literally hand this off to my mother and say, “Here’s the dashboard,” and have the information inside of it be completely self-explanatory.

And there’s yet another gap that Domo specifically addresses. If you look at the tools that are on the market today, both from the full stack vendors as well as most of the departmental solutions, they weren’t designed specifically for the business needs of today. Having spent 20 years in the business, I know first-hand, especially in a large enterprises with customers, that the needs that customers had ten years ago are certainly not the needs today. For one thing there was explosive data growth—we’re dealing with more information in almost every organization than ever before, and it’s not just information coming from the data warehouse or mart. It’s coming from operational systems; it’s coming from social networks; it’s coming from transaction files and web logs and all kinds of other things. And that information needs to be included so that I can get a full picture of what’s going on in my business and start to understand how different components and facets of operation of my business will link together.

Another gap is the use expectations of the internet generation. Back in my day. I remember being excited when CompuServe was released and just the whole concept of a CompuServe email or a CompuServe group chat was exciting. Although they were very slow dialing in over a 1200 bob modem, it was certainly better than anything we’d ever had before. But that doesn’t apply for users today. Most folks are carrying around an iPad or at least a Smartphone, and they realize that they can get access to any piece of information that they need by simply typing in a Google search or firing up their Smartphone. The same is true of the information inside their business. If folks have to go back to IT and ask for a report and then wait a day or a week or even a month to get the information only to find out that it’s not the information they needed or not in the format that they wanted it in and then have to start over, that’s simply an unacceptable paradigm for many users today. And speaking of powerful mobile devices as it’s mentioned on the screen here (as I just mentioned more folks are carrying around iPads and phones that they use for their daily personal activity), folks want to be able to use those exact same devices to be able to consume business information. They shouldn’t have to go to another system or have to go to a specific piece of hardware or log in to a specific application only from their desktop. Why can’t I get access to my revenue information or my sales figures when I’m on the golf course or on an airplane? I need to be able to get that information on any device and be able to get that wherever I happen to be.

But along with that, that presents an unprecedented demand on security. Because I’ve got users who will be consuming information on all these various devices, I need to be able to control who has access, not just to the system but also to the information within that system so that the right users are getting the right information at the right time. And that’s really what Domo was designed to focus on because that’s what we were architected for. There are five points that you see on the slide here, and this is what we’re going to talk about today. I want to talk to you about what I call “the Domo differentiators,” the first of which is sharing information with everyone in the organization, and I mean everyone. Anyone that needs access to information to be able to make the right decision and to do their job effectively should have access to that, and it should not be a painful process.

Second, along with that, if I’m responsible for information within my organization and the data bases and the files in which it sits, I don’t want to have to build a new data mart or a new data warehouse to be able to give users access to this information. We’re going to talk about how Domo lets you leave your data where it lives.

Third, Domo is built specifically for the web. The web is by far the way the preferred delivery method when it comes to information of all kinds, certainly in most business intelligence applications, and Domo was architected specifically to do that. We’ll talk about that in a little more detail.

Fourth, Domo offers one set of KPIs and one user experience throughout the organization. Even though I’ve got folks who may be coming in on Blackberrys and Androids and Windows phones and iPhones and laptops and desktops, I don’t want to have to build separate versions of my KPIs for all those different devices. I need to be able to stand up one dashboard and have that consumable regardless of what the user is using to get there without me having to go through maintenance, headache, and heartache on the backend.

And, fifth, Domo allows the ability to design and build visualizations with no limits. I don’t want to be locked into only being able to define KPIs in a grid format or only being able to use very limited chart types. I should be able to design a system for my users to consume information that specifically meets their needs, and I should be able to apply any look and feel that I want to, to be able to deliver that without having, again, to go through headache or heartache on the backend. So let’s talk about these in a little bit more detail.

The first one is sharing information with everyone in the organization. Domo was designed specifically to be accessible by business users who may not have access to traditional BI systems, or, more likely, have access to them but don’t use those systems. One of the things that I hear so often when I’m talking to customers and the prospects is, “Yeah we do; we have some self-service BI, but the problem is I don’t know how to use it,” or “The system keeps changing, and they keep wanting to send me to train. All I’m trying to do is generate a sales report or some operational reports or get access to my financial data. I don’t want to have to have a doctorate to do that,” or “I don’t want to have to ask an administrator to be able to get access to that information.” And if you think back to the slides from Mike, one of the things that he talked about was the top strategies for more effective business intelligence. And two of those were  (1) providing access to analytical capabilities for more business users, meaning opening that up to more folks within the organization not just to a limited or select few,  and  (2) providing customable functionality to meet specific department needs. I may have one dashboard, but different users within my own organization may need access to only certain parts of that dashboard, and I need to be able to very easily deploy that information without me having to maintain multiple systems on the backend or multiple versions of KPIs.

And Domo is great if you are in a large shop, just like the companies that I tend to deal with—I’m typically talking about hundreds or thousands of confirmed users at any given time. If I’m a five-person shop, and I’ve got five KPIs that I need to consume, then there are a lot of solutions on the market that would be able to meet your needs. But if I have 20 or 30 or 40 thousand concurrent users, I need a system that scales to be able to do that without making massive investment in infrastructure or resources. As an example, there is a very large retail hardware manufacturer on the West Coast that is a large Domo customer, and at any given time they have about 40 thousand concurrent users in the system, that’s 40 thousand people that are clicking on a dashboard or slicing or dicing or drilling or analyzing information through Domo. And they’re supporting those 40 thousand concurrent users on a 196 CPU course. That’s an extremely low number given the amount of concurrent users that they actually have. And there are no other solutions on the market that can not only deliver as compelling and as useful solutions as Domo but also do it with that little of a hardware investment on the backend.

Another point is leaving the data where it lives. As we release business intelligence to the masses, as we give information out to folks, one of the things that we tend to see happen, specifically in enterprise shops but definitely in customers of all sizes, is that users suddenly demand access to even more data, not just the stuff that may be in a data mart or in a data warehouse or in one transactional system. They want to see how information from different parts of the business relates to each other and how that impacts the organization. So I need to get access to my finance data, my ERP data, my HR data, my sales data, and so on, and I don’t want to have to construct some massive warehouse on the backend, nor do I want to have to worry about data lag. A lot of times I hear from users, “Yeah we’ve got access to a data mart that’s got a lot of information from different sources. The problem is, it’s only updated once a day and the information that I need needs to be much more timely. I actually need to be getting five minute or fifteen minute updates, so the data in my data mart doesn’t allow me to do that.” But wouldn’t it be nice to be able to build a visual information solution that allows me to aggregate this information from all these various sources and deliver that in real time or near-real time to the folks who actually need it so that I get access to the information I need without having to worry about “Well IT hasn’t updated the data base” or “the warehouse load didn’t work last night so I’m still looking at the information from yesterday.” That’s exactly what Domo allows you to do, by only accessing the information needed to populate the KPIs and then cashing that in memory, so that not only am I getting access to everything that I need in real time or near-real time, but I’m also getting extremely fast performance on the dashboard so that users aren’t waiting five or ten seconds just to look at the information that they actually see on the screen.

The third point, and frankly, the one that I think is most important and the main reason that I chose to come to Domo, is the architecture of our solution itself. I did a lot of investigation and a lot of homework into how the software was actually built and how the thing actually works in the real world before I chose to come to Domo, and I was blown away by the architecture. Not only was it architected specifically to support very large numbers of concurrent users in a web environment (again, regardless of what device that you’re actually using), but it’s also designed to do that using open web standards. So I can use things like HTML and CSS and JavaScript. I’m not locked into proprietary code once I get a solution built inside of Domo. It’s all extremely accessible. I don’t have to hire people that have new or different skill sets, and, as an example, if I choose to re-skin my internet for my users within the organization or my extra-net portal for my customers or my suppliers or my partners, it’d be really nice. And this is exactly what Domo does, allowing me to take a copy of my new CSS file and simply lay that over my KPIs so that suddenly everything has a new look and feel that matches what I’m going with from my standard corporate identity without me having to go in and edit each of those KPIs individually.

One other point that Mike had made that I thought was relevant to this is that “best-in-class” companies are broadening their business analytics not just throughout the organization (in other words, giving BI to more people inside the four walls), but they’re also doing this with their customers, their partners, and their suppliers. That’s one of the things that we see most successful organizations are incorporating or plan to incorporate within the next 12 months, to get access to the same information that we’re using internally, and then give the relevant stuff to my partners and my customers and my suppliers. And we do that. Not only do we have robust security to be able to allow those users to come into the information of your organization, but we also allow seamless integration into whatever internet or extranet or portal that you happen to be using so that, again, I don’t have to stand up an entirely new web base to deliver the infrastructure just because I want my users to now get access to information that they need to be able to not only do their jobs but also to improve my relationships with those customers, partners, and suppliers.

As the number of users grows within your organization, and as the number of types of information to which you give your users access grows as well, one of the things that we often find is that users who may have only had access to a limited set of information, or a limited set of KPIs, suddenly want more. They want to be able to see information in a variety of different ways to be able to create those KPIs themselves on the fly over the web and then share those with other users within the organization. It’s very important to keep that in mind as you’re looking at visualization solutions, and one of the things that Domo does better than anybody else is give you the ability to create one set of KPIs and one consistent user experience for your organization as well as your customers, suppliers, and partners, regardless of the device that they’re actually using. There are a lot of solutions on the market that say, “Yeah, we do mobile,” and “Hey, we support iPad natively,” and “Hey, we support Blackberry natively,” and “we support iPhone natively,” yeah, well, Domo does too. But the difference is with Domo I don’t have to build separate KPIs for my iPad users or separate flavors of my KPIs for my Android or my Blackberry users. And that’s extremely important. Again, if I’m a five user shop and I’ve got five KPIs, it’s probably not that big of a deal, but if I suddenly have hundreds or thousands of users consuming hundreds or thousands of KPIs then the last thing I want to do is have to maintain multiple versions of those for my different users with their different devices.

Domo dramatically cuts down on not just what it takes to stand a dashboard up but, more important, what it takes to maintain that dashboard over time, specifically as KPIs change or the information that’s used to feed those KPIs changes behind the scene. And that’s something that you definitely want to keep in your mind as you’re looking at solutions.

So let’s review. I’d like to just very quickly go back over those five points, and you’ll see them building here on the screen as we go. (1) Sharing information with everyone in the organization. Again, even if I’ve got 50 thousand or 100 thousand users that need access to information, Domo’s got you covered. (2) Being able to leave that data where it lives, not having to go out and build a new warehouse or a new mart or a new massive transactional data base just to be able to support that. That’s exactly what Domo does. (3) We were built specifically for the web to allow you, again, regardless of what device you’re coming in on, to get access to that information all from a single infrastructure point on the backend. (4) One set of KPIs. This user experience that you’ve created within your organization or allowed your users to create and share themselves without having to build different versions of those KPIs for the different folks coming in on different devices. And finally, (5) Domo gives you  the ability to design and build visualization with no limits, being able to choose the look, the feel, the style, and the functionality. And if you put this in perspective with a lot of the other tools that are on the market it becomes clear, or at least I hope it does if I’ve done my job here today, that Domo is, in fact, different, and I personally feel much better in being able to provide these visualization solutions that are world class with no user training from a consumption standpoint and be able to do that regardless of the device at which we’re actually looking.

But as opposed to just taking my word for it, what I’d really like is for you to send us an email at info@domo.com . We’ll have somebody like me, if not me directly, come talk to you along with the sales rep about what the needs are within your organization. As opposed to talking about Domo generically, I’d really love to talk with you specifically around what kind of things you are looking to measure, who’s responsible for that stuff within the organization, what kind of data sources you have, and what are you looking for in terms of the solution that you’d like to be able to deliver to your users. And we can have a chat and determine if, in fact, Domo is a good fit, and if so, what the next steps are to take from there. That’s really all I had, so I wanted to thank everyone for joining us today and look forward to hearing from you, thanks.