JOE: Hello my name is Joe Venetia, and I’d like to welcome you to today’s webinar, SaaS BI—Moving to Primetime, hosted by the Aberdeen Group and sponsored by Domo Technologies. Our presenters for today’s webinar are Michael Lock, Senior Research Analyst in the business intelligence practice with the Aberdeen Group, and Chris Wintermeyer, Senior Director of Enterprise Solutions at Domo Technologies. If you’d like to read their bios please click on the ‘speaker bios’ tab in the webinar console. To submit a question for the Q & A session at the end of the webinar please click the ‘ask a question’ tab on the lower left corner of your screen then type your question and then click the ‘ask question’ button below. It’s now my pleasure to turn the webcast over to Mike Lock; the floor is yours.
MIKE: Great, well thanks very much Joe and welcome everyone. This is Mike Lock here, I’m filling in for David White. I’m delighted to have the chance to speak with you today because you folks represent our community. Our research is written about end users of technology, and it’s written for end users of technology, and my role at Aberdeen as a BI analyst is to explore and analyze end user behavior when it comes to technology usage, in my case specifically, business intelligence. What I wanted to do today is share some of the key findings around some research that we’ve done into software as a service-based business intelligence, or SaaS BI, and I’m hoping that the findings will help show not only that SaaS BI matters, but, more important, to show why it matters.
So just to run through a quick agenda for the presentation today. I want to start by talking about Aberdeen’s research methodology so that I can put some of the data into context for you. And then I want to understand the why of SaaS BI—why does it matter who’s using it, and what are the key drivers of adoption when it comes to SaaS BI? I also want to talk about the what—what’s in it for me when it comes to SaaS BI, what are the tangible benefits of taking this type of an approach? And then finally finish up with a few conclusions and recommendations that I think are relevant here.
So we will start off by discussing Aberdeen’s methodology. We’re always looking to understand the end user mindset, in other words, what keeps the end user up at night? Specifically, we want to understand the linkage between the business pressures that they’re facing in connection with the technologies and tactics that these companies employ to address those challenges. All of us analyst firms have to have acronym frameworks, the framework that we use is one that we call P.A.C.E., and this stands for pressures, actions, capabilities, and enablers. So whenever we survey our end user community and talk to end users live, we’re consistently asking them questions about these four areas. We want to know what the top pressures are that are driving them towards solutions like BI, what keeps them up at night? We want to understand the actions that they’re taking at a strategic level to address those pressures—the actions they take, the A of P.A.C.E. The C of P.A.C.E. is capabilities; we want to understand what competencies, what aspects of organizational maturity that they employ to help execute against that strategy? And then finally the E of P.A.C.E. stands for enablers. What technology enablers do these companies use to help execute that strategy and put that into place?
The second piece of the methodology revolves around measuring performance. Once we understand the end user mindset and behavior then we want to understand how they’re performing as a result. We do this by developing what we call a maturity class. Companies that perform in the top 20% of respondents to our surveys are what we continuously refer to as the “best-in-class.” The middle 50% are what we call the “industry average,” and the bottom 30% are what we call the “laggards.” The key to our research is that once that we’ve established this maturity class and understand that end user mindset, we make a connection between the two. In other words, we map the activity and the mindset of a “best-in-class” company to the performance that they achieve. That’s really what the research is about, providing a road map for companies to change the way that they think and the way that they act around BI so that they can draw closer to “best-in-class” levels of performance.
So let’s talk about who it is that’s using SaaS BI. Most of the data that I’ll be discussing today was taken from a report that we created earlier this year around agile BI. We surveyed over 300 people and found that 26 were using exclusively SaaS-based business intelligence, another 42 were using a combination of SaaS and other forms of traditional BI, and the rest were not using SaaS BI at all. The data from these findings becomes a little bit more interesting when we compare it to a sample of BI users from the previous year. If we look at this sample collected back in February versus a similar sample collected back in 2010, interestingly enough what we’re seeing is that companies at a relatively slow but noticeable rate are moving away from purely conventional BI and taught either a hybrid approach to BI, where they’re combing SaaS-based business intelligence with traditional methods, or an exclusively SaaS based approach. So they’re moving towards this web-based on-demand approach to business intelligence.
Where is this momentum coming from? What we’re seeing is that this growth is coming from both the SMB segment (small and mid-sized companies) and the larger company sizes. If we start with smaller companies, why is it that these companies turn to SaaS-based business intelligence? Typically lighter-staffed and resourced from an IT perspective, these companies are most used to, of course, the ubiquitous spreadsheet. We all use spreadsheets. They’re wonderful tools, but they certainly have their limitations from an analytical perspective. You can do simple reporting in analytics, but very little is automated, and it’s generally a very manual process which also means that these tools are time consuming and often times prone to errors.
So they have a need to move past more than just a spreadsheet. Typical, traditional BI deployments can be a challenge because they carry two aspects with them that are a particular difficulty to smaller companies. First, of course, is the capital expense of deploying and maintaining these tools; traditional BI tools, can be overwhelming for these companies. And second, most don’t have, nor can they necessarily afford to bring on board, the dedicated IT or BI staff required for implementation and management. Two fairly logical reasons for small companies to gravitate towards SaaS.
But what about on the large company side? Why then do the larger companies leverage SaaS BI? Typically it’s the same kind of reasons flipped on their heads a little bit; in other words, it’s still largely a cost and resource issue but in a slightly different way. Larger companies typically do have that substantial IT presence but that doesn’t necessarily make it easier to earmark the funds and the IT resources to get these projects done. Often times they’ll be turned away by corporate IT, or they’ll be put in the back of a queue where they’ll be waiting months a project to even start, and then they’ll be on the hook for a substantial budget to make that happen. Instead, some larger companies take the SaaS approach because generally they can get up and running with the tools much quicker and typically at a fraction of the cost.
Some of the research shows some of these interesting usage levels for small and mid-sized companies. Perhaps unsurprisingly as we see in the bottom bars there, small companies are more likely to use SaaS-based business intelligence exclusively, more likely than any other company size to do so. And while the usage of exclusive SaaS is not as prevalent for mid-sized and large companies, the overall usage rate through the use of that sort of hybrid approach that we talked about before, is actually quite significant for both mid-size and large organizations.
So let’s talk about what it is that drives SaaS adoption, the why of SaaS. Earlier I had alluded to our P.A.C.E. model, pressures, actions, capabilities, and enablers. And what we’re looking at there in this chart is the P of P.A.C.E., the pressures. For those companies taking a SaaS approach to BI, what are the key drivers of that analytical strategy? These pressures that we’re looking at on this chart are fast becoming the three biggest trends that we’re seeing come out of our BI research, and that really is (1) more data, (2) more users, and (3) less time to put it very simply. So we see there in the largest pressure they’re growing volumes of source data. Data is growing both in terms of volume, as we all can tell on a daily basis, but it’s also growing in terms of complexity and disparity. The different types of data, unstructured data, all of this is becoming unmanageable for organizations, and they’re looking for BI to help them manage those issues. There is an increasing demand for timely business information and analytical capability, so there are more users, there are more potential users, there’s more of a desire for analytical capability. And then finally there’s less time to make these critical business decisions, where the window of time required to make that effective decision is shrinking for a lot of companies. This is a key theme of the research that we’ve flushed out in several surveys and questions over the last year or so. So really, more data, more users, and less time to make critical decisions are the top three pressures.
So what is it they do to help address some of these pressures? This is the A of P.A.C.E., the top actions or strategies that these companies are taking. At the top of the list is the concept of self-service, and we’ll be coming back to this a few times throughout the presentation. But the whole concept of enabling the exploration and discovery of data without relying on the IT department and becoming more self-sufficient with BI, is really a top strategy for these SaaS users, enabling this level of self-sufficiency. On the flip side, on the IT side, they’re looking to prioritize analytical projects so that the activities that can only be handled by the IT department are done so in a timely way. And more to that point, they’re making BI a more formal strategy within the company. They’re centralizing ownership of BI and making it a strategic priority for the company both on the business side and the IT side so that they can execute these BI projects more efficiently and more effectively.
So the final piece of the puzzle involves the what—what’s in it for me when it comes to SaaS BI? What are the benefits that companies can hope to attain through the deployment of these tools and the effective use of them? Earlier I talked about this whole concept of self-service BI; we’re continually asking our survey respondents, “Do your users have a level of self-sufficiency when it comes to BI? Can they explore and drill down into data? Can they create their own reports and dashboards? Can they generally ask questions of the business and get the answers that they need without relying on the IT department?” What the chart here is showing is that because of the nature of SaaS, because of the zero-footprint easily-understood web-based interface, a lot of times what you’re seeing is that these users are more likely to report having that self-service environment when it comes to BI so that they can empower those business users and reduce some of that IT burden to their IT organization.
Earlier I also talked about the value of widespread BI. One of the things that we’ve found is that SaaS helps increase the penetration of analytical capabilities throughout the organization. It promotes a higher level of what we would call “pervasiveness” in the company. One of the questions that I’m always curious about is, “What percentage of the user base are engaged with analytical tools? What percentage of those users that have access to analytical capability are using it on a frequent basis?” And what we’ve found more often than not is that SaaS users and these hybrid SaaS and traditional BI users are simply making more use of the tools. They’re leveraging them more often, they’re using a deeper set of the functionality involved in BI, and they’re broadening the usage of them to more users and to more functions within the organization. So BI is not only a greater strategic priority but also tactically is more pervasive for SaaS-BI users and those hybrid users as well.
We also found that SaaS users typically react faster to changing BI needs. This is also from the agile BI report from earlier this year. When a need arises for a new view of the data or a change of an existing report, which it often does, in fact it’s probably the rule more than it is the exception, companies that are using SaaS are simply making these changes faster, they’re more agile, so that the time required to build a new dashboard, a new view of the data to take a new understanding of what’s going on in the business, is 15 days on average for SaaS users versus 24 days on average for conventional or traditional BI users. Similarly, the time to make a change to a key report that they’re looking at, to add a column, to add a new piece of information to a report that really matters to the organization, tales on average three days for SaaS and hybrid users versus more than double that amount of time for traditional BI users. So SaaS users in general are more agile when it comes to BI.
Sticking with the theme of agility, here we’re looking at the C of P.A.C.E., some of the key capabilities when it comes to BI and in particular agile BI. What we found is that SaaS users (to hearken back to this concept of self-service) are more likely to empower business users to tailor their reports and data views at their own leisure, so to speak, to ask their own questions of the business, to generate their own views of the data, and to understand what’s going on in their companies without having to rely on the IT department. They’re also more likely to share knowledge better through the use of a library of pre-defined metrics, collaborate and disseminate analytical best practices and measures throughout more users within the organizations. So in ways that really matter towards agility, SaaS users are actually typically more organizationally mature than conventional users.
There are, however, a handful of caveats when it comes to SaaS BI, and I want to talk briefly about one of them. When you’re talking about SaaS, because it’s a web based delivery, on demand delivery of these analytical tools, you are subject to the performance limitations of the network that you’re on. At times that can lead to performance challenges. One thing we found is that SaaS users do have a slightly higher rate of late information when it comes to their ability to access what they need in the time that they need it. We’re always asking our users, “How quickly do you need information,” whether it be in real time or within the hour or within the day, and then we also ask them, “How often are you able to access that information within that given time period?” There is a little bit of a discrepancy between SaaS users and conventional users. SaaS users are able to get that information on time 74 % of the time versus 81% of the time for conventional, traditional BI behind the firewall. So that is one of the limitations to SaaS BI.
But perhaps the most important aspect of a SaaS strategy is really the economics, and the last chart I’ll show here is around some of the data that we’ve collected around the economics of SaaS BI. We’re consistently looking to quantify the cost of BI, not just on an absolute basis because that’s really limited in value, but more so on a per user basis. We’re trying to capture the total cost of ownerships, the TCO of business intelligence, in terms of hardware, software, services, training, and maintenance, the whole package, the whole total cost of ownership package of BI over a 12 month period. And what we’ve found is that SaaS users on average are spending about 250 dollars less per user than conventional BI users. So that is some fairly interesting and pretty compelling data on the economics of BI.
Finally, I will close with a few conclusions and recommendations. First off, we are seeing an uptick in the use of SaaS BI, both within the SMB levels and within enterprise segments of organizations, and it really does speak to the viability of software as a service-based BI. And part of the reason is that SaaS does help promote adaptability and therefore agility as well as that self-service, that ability to relieve some of the burden of BI on the IT department and deliver these capabilities to more business users in a meaningful and use friendly way. I have a couple of recommendations to close out with. One is that I’d encourage you to stay on top, stay aware, of the broad aray of information needs within your organizations. If you’re considering BI, it’s important to understand the data and the users. Where is the data within the organization? What are the sources that are absolutely critical for your analytical purposes? How quickly does it need to be accessed? Who are the users who are going to be requiring access to it—is it going to C level executives, is it going to be operational decision makers, is it going to be IT folks? What are their needs, what is their decision window? There are a lot permutations to this, and it’s important to understand what those information needs are.
Second, make sure you track the long term economics of BI. Really it’s not just about that upfront software licensing cost but also the whole total cost of ownership equation: the software costs, the potential hardware requisition costs, and of course the un-ignorable service and ongoing maintenance costs. Ideally it’s really important to keep this whole TCO picture in mind when considering a BI strategy within your organizations. 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 from Domo, Chris.
CHRIS: Thanks David. I got to tell you, those are some great recommendations on that slide. I was listening intently having spent about 20 years in the industry, specifically the part that you mentioned about understanding the needs of the users and the data as you’re evaluating SaaS-based solutions. I think that’s key, and one of the things that I’ve found is that folks tend to focus more on the technology and less on the particular needs of the users and the data and how it’s going to be accessed, and I think it definitely needs to be, as you mentioned, the other way around, focusing on the needs of the users and the data first and let the technology then be driven based on how it’s going to be consumed in the organization.
I also thought the statistics you mentioned were interesting, that it’s 40% faster to build a new dashboard on average and about half the time KPIs and reports for your SaaS-based respondents as opposed to traditional licensed software, I found that very interesting, and frankly one of the reasons I came to Domo is that we offer technology that enables that. But before I get there, what I’d like to do is to spend a couple of minutes talking about how you decide specifics in business intelligence, and what are the things you need to look for to determine if SaaS is right for you. If you’re an executive considering a move to a SaaS BI solution, you need to be asking key questions about cost savings, IT impact, and the promised availability and security so that you can quickly identify whether a SaaS offering is right for your organization. Again, as Mike mentioned, it’s all about understanding the needs of the users as well as that data.
Taking advantage of a SaaS solution for your key business services, specifically around business intelligence, allows you to focus on what your business does best. It removes a lot of the backend infrastructure and maintenance, and we’re going to talk about that here over the next few slides. If you look at the economies of scale and the technology expertise that’s employed by the reputable SaaS providers, the whole purpose of the services is to allow you to enjoy things such as increased cost savings, greater IT, and business agility (which we’ll talk about in more detail), higher system availability, getting access to the right data at the right time, as well an enhanced security. So the four questions that you see on the screen here—around lowering the cost and impact to IT operations, meeting availability needs and having the security needed—are the things that I’d like to focus on here today.
The first and foremost question is one that I certainly get asked most often as I deal with organizations of all sizes, but specifically in the enterprise space where I tend to focus on larger implementations, is, “Will SaaS actually cut my costs based on what it is that I’m trying to do?” I was thinking about this question as I was putting the slides together, and I happened to be doing this late at night. As this slide builds you may realize that I was, in fact, up very late at night when I was working on this. I don’t know if any of these things are going to look familiar to you; I will admit to everyone here on the phone that I have in fact purchased a couple of these products in the past. In the advertisements for these objects, just as they’re nearing the end of explaining what the product can do and why you should buy it, they tell you, “But wait! If you call now we’ll double your order. All you have to do is pay additional processing and handling.” And that in fact is where they actually get you.
And if I liken that to SaaS. I like to say that SaaS eliminates that “shipping and handling.” Those charges that they throw on just to get the second set of the product out the door to you can, in some cases, double the actual cost of you ShamWow or your ThighMaster or your Flex Seal, and it’s not dissimilar to looking at enterprise software. The peripheral costs and the add-ons when you look at traditional licensed software can quickly add up. Operating business-critical systems means significant investments in things around software licenses, computer serving hardware, high performance storage systems, networking, and physical data center space just to house the systems, not to mention that you’re making continual investments in things around updates, improvements, and patching plus the human costs that you have associated with that—so you’ve got to be able to deploy, maintain, repair, program, backup, secure, and update everything on a regular basis. So what does this mean from an enterprise traditionally-licensed software model? Well, it means that the initial periodic and ongoing expenses that are typically associated with maintaining and operating all these business-critical systems like business intelligence, can have a very significant impact on your bottom line.
So if you can shift the maintenance and operations of those key systems to a SaaS provider, the investments and IT infrastructure and personnel can drop, in some cases dramatically. Obviously there’s still going to be a need for investment in personnel to administer the front end and the business facing aspects of the service, but all that investment in the back end—IT, the real estate, the administration and the personnel necessary just to host and maintain those systems—goes away in the SaaS-based solution.
It’s also important to keep in mind that cost is not the only financial benefit. When you’re in a SaaS-based subscription model this can also give you cost agility. With a lot of SaaS solutions it gives you the chance to evaluate the business service, specifically around BI. So I can fire up a SaaS-based BI solution, wire it in to several of my data sources, throw some KPIs and reports on the screen, and instead of having to invest all that infrastructure just to be able to support a pilot or a proof of concept, all you’re doing is buying a few user subscriptions and then ramping it up. If you like what you see, you can continue to roll that out to more users. If you don’t like it, you simply turn the switch off and you’re done. You’re not stuck with a bunch of hardware and software on the back end that turned out not to meet your particular needs.
Another thing I think that’s important to note is, on the slide that Mike was talking about about conventional costs versus SaaS costs, conventional BI costs according to the Aberdeen study averaged out to 658 dollars per user with SaaS coming in at 404 dollars. That’s a savings of 254 dollars, almost 39% per user. And that can be substantial, whether you’re in an evaluation phase or you’re looking to roll out a SaaS-based BI solution to an extremely large number of users.
Another question that comes up a lot, and I would say is second most important right behind costs, is, “What is the impact to my IT operation?” And I was thinking about this as I was putting the slides together, and a few years ago I was living in Dallas, and I had purchased a home and decided that I was going to tackle the bathroom renovation myself. There was a bunch of work that had to be done, and it was all around everything from replacing the tub and the plumbing to the electrical. And I ran into some challenges with the plumbing, specifically as I removed the old copper lines and put in braided lines. Unfortunately, I chose the cheap braided lines, and it was not long, in fact it was the third day after my reno was considered complete in my mind, until I woke up to find water pouring out all over the floor, cabinet doors had started to warp, because the braided lines had actually failed. So I called a plumber, and the plumber came in and instantly shut the water off, removed the cheap braided lines, gave me a very nasty look, and proceeded to replace them with copper. And the problem was solved; that was it. I didn’t have to call the plumber again, it was done.
The same is true if you’re like me and you’re a fan of the home shows, which I guess I need to be watching more closely, things like Holmes on Homes or Ask This Old House, where you’ve got experts coming in in HVAC, electrical, and plumbing, and help people who have put in the wrong wires or they’ve used the wrong lubrication or whatever the case might happen to be. Those experts can come in and fix those things very quickly, and then they’re gone. Well, it’s different in the world of enterprise software, and specifically one of the things that I think is very important from a SaaS-based solution is that SaaS allows you to focus on running the business. They’re the experts behind the scenes and the things that keep everything up and running. Because when it comes to things like enterprise-wide BI, this ain’t your bathroom. This is something that not just requires an immediate fix if something breaks, but a lot of work goes into play into being able to optimize and maintain those systems.
So, in addition to the IT savings that we talked about on the previous slide, there are a lot of other benefits because the complexity of deploying and maintaining a lot of these systems can really create havoc on an IT department’s ability to focus on the needs of the business. Unless you’re going to go out and hire a premium salary specialist, your existing IT folks are going to be struggling in some cases, and they’re certainly going to be forced to maintain the optimization of usage of BI regardless of what’s going on within your organization. So when I’ve got things like end-of-day, end-of-month or end-of-quarter cycles, I have to be able to optimize my system for that. Well, does that require buying a lot more hardware to accommodate that or are there system tweaks that can be made and then modified based on the particular time of day or time of week or time of month? All of that stuff can be very difficult, especially when the IT organization is forced to maintain dozens or even hundreds of applications. And not just that but if you look at things around upgrades and patching, many of you on the phone probably know this, if you haven’t done it yourself I’m sure you’re certainly familiar with folks who have done it, that applying something that should be seemingly simple like a patch or an upgrade can actually dramatically impact your organization, and the last thing you want when you’re in a BI scenario specifically is applying a patch or an upgrade that suddenly eliminates users’ access to data, especially when it’s in a critical time in a business cycle.
And if we look at a study that was completed recently by Gartner, companies found that by introducing internet-based service technologies companies can take 30 to 50% of that infrastructure and operational resources, and reallocate them to business innovation and growth, things that actually matter and have an impact both to the top and bottom lines of the business. As a result they see this as creating a new CIO success cycle, in fact the quote is, “It’s a CIO success cycle that’s based on creating and realizing new sources of value, in addition to the cost effective IT operations.” And if we look at what Mike talked about earlier, SaaS BI allows business users to be more self-sufficient and enables corporate IT to be more responsive. And this is very much true when we look at the impact that SaaS can have on IT operations because we’re focusing on the business not the infrastructure, so SaaS BI lets you tailor the solution to your specific needs without having to worry about what that impact is on the back end. Let the SaaS folks worry about what it takes to maintain the performance that you’ve come to expect in your system. Your users are then getting access to the right information at the right time so that they can continue to do what they need to do to run the business effectively.
A third thing that’s important is availability. This typically falls around time. That’s the most important thing, but performance is also important, so we need to look at both of those things when we look at SaaS business intelligence based solutions. And a big advantage that SaaS brings to the table is a much greater amount of accountability. With a SaaS provider, you get documented SLAs, so uptime has a definable standard against which companies can hold their providers accountable. A reputable SaaS provider not only invests in the proper expertise and infrastructure to ensure availability around the clock so you get that 24 x 7 x 365 availability, but also guarantees in writing through these SLAs that your systems are going to be available, and there are reparations that take place if in fact those SLAs aren’t met. And if you take that even one step further, I recommend to all folks who are looking at SaaS BI that you should definitely do your homework to ensure that the provider that you’re looking at has best practices around things like redundancy and disaster recovery, not just things around system optimization. You need to make sure that the mean time to recovery, to get you back up and running, is acceptable based on your particular business standards.
And one of the things that a lot of folks don’t consider, and frankly it surprises me, that I think is very important, is to make sure that (as an example from an availability standpoint) that your provider is offering redundant hosting service. This just doesn’t mean that I’ve got two down the street from each other; it’s very important that these are in different areas of the country, different time zones, different fault zones, different flood plains, and different power grids so that we can account for all kinds of natural and unnatural disasters that might take place. Again some folks look at this and think “Well, it’s business intelligence. It’s not that big of a deal. As long as I get access to my critical front end systems to be able to enter data, I’m going to be okay even in the event of a major failure.” And that’s not the case. Having worked with thousands of organizations in the last 20 years, I have more than one horror story of organizations who maintained uptime through fault tolerance and redundancy for front end systems, but without access to business intelligence were unable to get the information that they needed to relay to their customers, to their investors, to their suppliers, and to their partners. In some cases it affected the business dramatically. So just something to consider as we go through that.
And last, but certainly not least, is security. This is obviously a question that should be first and foremost on a lot of folks’ minds. This may be obvious to a lot of you on the phone (especially those of you who have done your homework looking at SaaS-based solutions, whether it’s BI or other systems), but a reliable SaaS provider is going to invest in security, and they’re going to invest a lot in security. And one of the things that I find as I talk to a lot of organizations, not just in things like healthcare and financial, but in a variety of industries, is that one of the big misnomers out there is that a lot of folks feel that as long as the data is inside my four walls I’ve got complete security over that data. I don’t know any clearer way to say it other than tjust because you have control over your information or your data does not mean that you’ve got security. It’s very much a false sense of security, which is another reason that I encourage a lot of companies to take advantage of SaaS-based BI solutions and encourage them to look at them in detail.
A lot of times when IT professionals say, “Well if I keep it in house, I can take the efforts to make sure that it’s going to be protected.” But the truth is, there’s a lot of investment that’s got to take place from a security perspective around things like expertise and investment in new technology and making sure that you’re focusing on the right aspects to ensure that the data within your organization and the applications that are using that data are actually being secure. In fact there was a study done recently, the 2010/2011 Computer Crime and Security Survey. This was done by CSI, I’m not sure if that was CSI New York or CSI Miami (wow—that’s weird; it’s a mute-only webinar, and yet I still just heard a groan), but in any event whether it was CSI New York or Miami they found that only 60.4% of the companies surveyed had a formal security policy in place. 60.4%, that’s four out of ten responded, actually admitted, that there was no formal security policy in place. Additionally, only half of the folks that they surveyed used intrusion prevention systems, and less than half of those use log management. And as one example, I thought this was interesting, even though multiple studies indicate that log management delivers compelling value to a company’s security, the CSI survey not only indicated that less than half were using it but that compared to 2009, 7% fewer companies were using log management. It’s actually going down, just in the last two years. And the survey attributed this drop to the belief that companies aren’t able to keep on top of the monitoring and some of the responses included things like, “We’re just not able to do an adequate job of sorting through the ever-growing volume of logs that we have to look through. So it just became so overwhelming that we’re just not going to do it anymore.” So there’s definitely this false sense of security, and frankly I think in most cases, if not all, but certainly most, your data is actually going to be more secure, as well as the access to that, from a SaaS-based provider than it is having that data sitting inside your four walls.
So let’s talk just for a few minutes about Domo, now that we’ve talked about the four questions that, at least, I feel are most important when you’re looking at SaaS-based BI solutions. Domo is a SaaS-based business intelligence solution that’s transformed the way hundreds of executives from organizations of all sizes run their business, not just small shops, but also some very large organizations. By bringing all of the vital data from your various systems, things like finance, sales, ERP, HR, and compliance, and pulling that together inside of a single intuitive visual interface, we’re giving you real time access to the information you need in one place. And this is something that I’d like to talk about in just a little bit more detail before we open the webinar up for Q & A. One of the things that Mike talked about early on was the top practice for BI users including things like increasing and changing demand for information as well as shrinking decision windows. And Domo addresses this specifically by providing an intuitive interface that allows you users to get at the information they need without training. It’s something that a user can sit down and understand instantly what it is that they’re looking at. They can know the state of the business or the particular area or areas of the business that they’re focusing on and then be able to drill and slice and dice that information to get to the root cause, to understand what’s going on. So it’s very consumer friendly, and again, depending on what your particular needs are, the interaction with that data can be real time or near-real time even though it’s being hosted in the cloud. And what’s important to note is that this user experience can be personalized. You can tailor the solution to meet the specific needs of your organization, and it’s important to note that whether that organization is five users or fifty-five thousand users, Domo can handle that particular load for your organization regardless of the volumes of data on the back end. We do that while providing bulletproof security and unparalleled reliability leveraging a lot of the things that we talked about earlier in the slides around the four questions you should be asking when you’re talking to SaaS BI vendors.
So how do we do this? How does Domo accomplish this? Well, we were built from the ground up for the web, that’s how it was architected from the beginning. I have seen that there are some other SaaS BI solutions on the market that have their roots in traditional enterprise software, and they simply slapped that out into a data center or a series of data centers and told folks, “Hey listen we’ll connect to your data, and we’ll allow you to get up and running.” Unfortunately, those systems weren’t built for the cloud; they weren’t built for the web, and what folks find is that if I’ve got five users and a few KPIs on the screen it’s not a big deal. But the minute I start talking about hundreds or thousands of concurrent users or I start talking about tens or hundreds of millions of rows of data, suddenly my reliability goes through the floor. So while my data may be secure and it may be reliable in that when I fire up the dashboard I can get to it, the performance is so bad that users stop using the system or that there’s so much latency in the data that it’s not relevant anymore. So those are things that you definitely want to focus on.
And again Domo was built specifically to be able to access data in a variety of systems: your CRM, your ERP, your HR financials, as well as your traditional data sources—things around data warehouse, data marts, relational databases and cubes—as well as other files and systems that you may have in place, such as XML, HTML, web-based files, and spreadsheets. And we do this without having to replicate your entire mart or your data warehouse or your ERP system or all of your log files. We simply access the information that we need to populate the KPIs on the screen for your users and still allow them to drill and slice and dice that data. So not only does this give you very rapid performance with extremely fast response times, but it allows us to more securely access your data because we’re not transferring every single chunk of data from your in-house systems out into the cloud. And again we were built specifically to do that.
One last thing that I’d like to note, and frankly I think this is one of the biggest benefits that Domo brings to the table, is that when you build a dashboard for your users, for their desktops or their laptops, the exact same dashboard that you build for the folks running Internet Explorer on Windows or Chrome on the Mac, can be accessed by web browsers on a variety of platforms. So if I’ve got users that are using Opera and Firefox and a bunch of other browsers on their desktops and laptops, or they’re using things like Windows 7, Windows Mobile or iPhone or iPad or Android or Blackberry, we allow you to come in either over the web or with a native client application for those platforms and access the exact same dashboard that was built for your desktop or laptop users. And what this means is, I’m no longer replicating or duplicating the work but allowing users to access the dashboard wherever they are from any system without me having to maintain multiple flavors of that behind the scenes. And that’s a really big deal especially as we get into large numbers of users, large amount of concurrency and in situations I’m seeing more and more, especially in enterprise shops, where it’s bring your own IT, where users are allowed to go out and choose the devices that they want to use to access the systems within the organization.
So the last thing before we open it up to Q & A, I’d just like to throw out, if what you’ve heard here today sounds interesting, if you’d like to talk more about this, if you’d like to see a demonstration that’s tailored to your needs, or if you have the invariable questions about things like pricing and licensing, please email us or give us a call. You can also look us up on Facebook and Twitter; we’d love to talk to you in more detail. And with that, Joe, I’m going to turn it back over to you.