Choosing the Right BI Solution: Overcoming 5 Common Concerns

KAREN: Hi there, on behalf of DOMO and Bright Talk, I’d like to thank you for joining us today. We have a great presentation in store for you and I’m really happy to have you. My name is Karen, and I’ll be your moderator. The topic for the event today is choosing the right BI solution, overcoming five common concerns. We’ve actually designed the discussion today to be highly interactive. So I’d like to ask you a few favors. We have a couple poll questions; if you could answer those for us it would greatly help us mold the discussion. And we also have a Q&A feature that we’d like you to use throughout the presentation. We’ll get to as many of those throughout and also at the end. Lastly, if you are a tweeter, we’d like to use the hashtag today ‘BI Summit’. And as a reminder, the webinar will be recorded, so there is no need to take frantic notes. You’ll be able to access this in an on-demand viewing.

So before we jump in, let’s introduce our expert speakers today. With over two decades’ experience in technology and business process management, Chris Wintermeyer has helped hundreds of organizations develop and deploy business intelligence solutions that improve visibility and increase profitability. He specializes in business intelligence, analytics and data visualization, helping executives make sense of their data to drive better business outcomes. Chris is leveraging his extensive background, now, at DOMO as the chief advocate. On a personal note, Chris is truly a customer favorite. I think you’ll enjoy his ability to connect with both the technical and business professional audience and his deep knowledge on all things BI. So with that, Chris, let’s hand it over to you. [00:02:00]

CHRIS:  Hey Karen, thanks. And by the way, I am so excited that we’re actually getting to do the webinar together. I’m really hoping that this is…that this is beneficial for you. Before we actually dive in, the interactive features that Karen was mentioning about, I’d actually like to kick off with a poll question. I’m going to open up the question in just a second, but this gives you a little hint about the things we’re going to talk about today. Karen and I are going to go back and forth on basically, what are the challenges that people are facing when they’re looking at BI solutions? So the five areas we’re going to cover are mobile BI, cloud security, user adoption, getting people to actually use the thing. The fourth is the cost of ownership, and then finally, is implementation and deployment. These are the five areas we’re going to cover. And so to know where to focus, and I have a gut feeling on how this is going to go, but we’ll see. To know where to focus, I’d kind of like to get your input on what is the biggest challenge, if you had to pick one at the top, what is the biggest challenge that you’re having right now when it comes to looking at BI solutions, or even implementing the one that you’ve got now? So, I’m going to open up the voting, and if you can just give me your indication of mobile cloud security, user adoption, cost of ownership or the just overall implementation and deployment. What’s the pain right now? I will give everyone…what do you say, Karen? Twenty, thirty seconds we’ll give folks just to click a finger?

KAREN:  Yeah that sounds good.

CHRIS:  Yeah, so I think it’s going to be around mobile and around cost of ownership and implementation, but normally when I guess these things, I’m completely wrong. So any thoughts Karen, on what do you think this going to go?

KAREN: You know, mobile BI is something I hear every single day, but also concerns around implementation and deployment. So it will be interesting to see what the audience has to say here.

CHRIS:  I think so too and I’m not peeking [00:04:00]. I’m not cheating. I’m not looking at the results. So, again, we’re going to go ahead and close this now in five, four, three, two, one. Poll is now closed. And see, again, I was totally wrong. Only 6% of people are showing that they’re concerned about mobile BI. 14% around cloud security, that doesn’t surprise me, 26% on user adoption, 14% on cost of ownership, a full 40% on implementation and deployment. So gang, the good news for those of you in the 40%, well the good news for all of you, and we’re going to cover all these topics. The good news for those of you that voted e) implementation and deployment is that the other four basically encompass that fifth topic, and we’re going to be talking about that as we’re going through, so I really appreciate your input on that. And I guess Karen, should we just kick off with the first one?

KAREN:  Yeah, you know, I was just thinking the timing for this event couldn’t be better. This morning, I was just reading a Gartner survey stating the number one priority for CIOs this year is business intelligence and analytics. And every single day, you know, our customers and other professionals are grappling with these topics, and I’m really excited to cover off on these in a candid manner for everyone today. So let’s jump into the first subject here: Mobile BI. So Chris, there is so much hype around this subject. You know, do executives really want to consume their data, their analytics and dashboards and charts, you name it…do they really want to consume it on their iPads and Blackberrys and iPhones? What are your thoughts here?

CHRIS:  Well I guess I have a question for you. What’s a Blackberry? No, I’m just kidding. So without question, the hype around executives [00:06:00] wanting to use BI is that’s not hype at all. That’s actual reality. In fact, you know at DOMO, we maintain statistics on users coming into the system, and we have found that if you have a ‘C’ or a ‘V’ in your title, 75% of the time or more you are going to access your information from DOMO through a mobile device. Typically, it’s an iOS device; we see that as most popular, android is second, Windows Mobile is third. We see very little Blackberrys, but of course, you know, if you’re carrying one, we’ve got you covered too. So from the standpoint of users wanting to get access to mobile, no, there’s no hype. Where there is a ton of hype is all the solutions out there that claim to be able to do mobile. That to me is where the hype really is. You can’t swing a dead cat actually without getting a website that says “oh we do analytics, and yeah it’s available on mobile.” The problem is when you start breaking it down, if you peel back the layers of the onion, what you find is that the mobile solution is secondary. In fact, in a lot of cases it was an afterthought; it was built way after the initial technology was. And so what you end up with, are users who can…yeah I can get a report on my iPhone or I can view a chart on my Blackberry, but I can’t do anything with it. So if there’s a spike or a dip, or some kind of anomaly in the data, I’m back to the status quo, which is now I’ve got to go back and ask somebody else, or I’ve got to send a text or I’ve got to make a phone call so that I can start to understand what’s actually going on.

In fact, one of our customers, a big retail customer, this was her number one driver was I wanted the ability…she wanted the ability; this is what she told me, “I want the ability to be able to consume the information on mobile devices. I want each of my store managers, who are all very comfortable with mobile devices…” because her store managers are all under the age of thirty, so they just grew up with them, and I think they were born with phones in their hands. And then she wanted the ability for them to have a very intuitive interface. To not just see what’s going on from [00:08:00] a sales perspective, where we are dealing with the noon goal or the five o’clock goal, but how are we addressing certain issues that come up? Whether it’s, you know, our POS system is down or sales off on accessories more than X% kind of thing—being able to explore that data. And so I think from a hype standpoint, if you’re looking at global BI, and if you’re not by the way, you should be. Because I promise you, you have constituents, if you’re in IT or BI, that are going to want this. And if you are one of those constituents, chances are there’s somebody right now who’s nodding their head. Mobile BI is critical, and it may not be that users are going to use it right out of the gate, but you need to be able to give them, I believe, the exact same experience on mobile that they get on a desktop or laptop. So if you’re going to give me a bunch of reports that I can filter on, and that I can drill on, and that I can collaborate around, just because I’m carrying it in my pocket doesn’t mean that I should be limited in being able to get access to that information. So that was kind of a long-winded answer, Karen, and you know I’m long winded anyway but is that what you were going for?

KAREN:  Yeah, so what I think I hear you saying is most vendors are saying they can do mobile BI, but the experience is vastly different device by device. And perhaps might require a lot of custom work or hidden costs, is that what I hear you saying?

CHRIS:  Yeah, the experience is different for two different reasons, from two different perspectives. In a lot of cases, the experience is different for the end user. So, what they’re used to being able to do and the way they’re able to do it when they’re at a desktop or a laptop, they have to learn a different paradigm; it’s a different interface. A lot of times it’s very limited in what they can do. The flip side is taking that from the IT and BI perspective, which is yeah, we’ve got an application that will give your end users a very seamless or similar experience, but that’s going to require more work on your part. You’re going to have to go build separate flavors of the dashboard. You’ve got to build one for phones. You’ve got to build one for tablets, or you’ve actually got to build one for each [00:10:00] platform—one for android, one for iOS, one for Blackberry.

So our philosophy at DOMO: that experience should be the same. I should build a report, wherever I build a report, and that report’s available wherever I consume it on whatever device. It should be the same experience.

KAREN:  So are there any cases that you’ve seen that organizations don’t need mobile BI, or let me phrase the question differently. Have any organizations just started with more of a desktop-, laptop-centric solution?

CHRIS:  Without question. I mean the majority of them actually. I mean we have some customers that will buy specific for mobile, right, because that’s what they’re looking for—for example, the retail customer I mentioned earlier. In more traditional shops, people are used to doing things a certain way; they’re used to not being able to get stuff on mobile, so they’re just relegated to not ask for it anymore. They’re just… they’re done. They’re like, “if I can get all my reports in one place, my desktop or my laptop, that’s good enough in a seamless experience.” So they’ll start out not at all focused on what…in fact, there are cases where…in fact, there was one with a health care company when I tried to bring it up, they didn’t want to talk about it. They’re like, “look, it’s just…it’s not important to us. We tried it before. It didn’t work; let’s just focus on what we need to do, which is manage our metrics”.

Well, with them, as with a lot of other folks, is once they realize “hey wait a minute—the same login that I used on my laptop, I can use on a mobile device, and I have the same experience,” suddenly, mobile becomes a lot more important than it used to. But, in my experience, the people who aren’t asking for it—it’s simply because they’re done. They’re just…they’ve tried this before. It hasn’t worked. The promise just was never fulfilled, so it’s one of those pipe dream things that frankly they don’t want to talk about again because they don’t want to get their hopes up, just to have them dashed. And that’s one of the great things I think about an application that provides that same experience—is that you can empower those users if and when they’re ready for mobile, but you’re not having to do any extra work, and you’re not having to force them down a road they don’t want to go down [00:12:00] until they’re ready to go down it. When they’re ready, they just fire up their device, they go to the exact same URL, they put in the login and boom, they’re good to go.

KAREN:  That’s interesting food for thought, Chris. I think we can move on now to cloud security. Something that, you know, a lot of folks are talking about out there in the market place. So many people are moving to the cloud. And it’s been around for years, yet there’s still a lot of trepidation when making the move. So can you tell me a little bit about on premise solutions versus cloud solutions and what people are saying in the market place?

CHRIS:  Yeah, sure, absolutely. And you know, well Karen you know this, I’ve been doing this for almost 25 years, business intelligence. You know, I spent a lot of the time at the big stock vendors and also at a couple of desktop vendors before my three years here at DOMO. And this is something that’s…as you mentioned, cloud’s been around for a long time and by cloud, I’m talking about literally storing it out on the Internet. Something like, for example, salesforce.com or adobe analytics. These are very popular applications where all the data for that particular application is stored in the cloud.

A common misnomer, very common misconception, is well, if I keep my data on premise, it’s more secure, because I can literally hug my server. Or I can hug my virtual machines and so that data’s safe. And in actuality, that’s not the case. I mean, obviously it’s dependent upon the specific organization, but if I had a nickel for every time I went into organization that employed a BI solution where it turned out that ports were exposed or that logins had been shared with users and there was no monitoring going on, seriously, we wouldn’t be having this conversation because I’d be on a beach somewhere. It’s…just because you got the data on premise, doesn’t mean it’s not…it doesn’t require work to be secure. In fact, in a lot of cases, it requires a lot more work. And as an example, you know DOMO is a cloud-based BI [00:14:00] provider, so there are a lot of hoops that we have to jump through because we take data extremely serious when it comes not just to availability, but also to security.

So, you know, we go through quarterly audits, we have third parties that we literally pay them to try and break into this system and expose any vulnerabilities, not just based on known entities but also based on new techniques that may not be widely known, and then any vulnerabilities that are found we correct within a 24-hour period—that’s our philosophy. A lot of organizations, both mature as well as folks just starting out, I don’t tend to see those same regular processes in place. And so you tend to get lulled into this false sense of security that because my data’s on premise, it’s completely secure. And the other thing to keep in mind is that even if you are going through the exact same protocols and procedures and recommendations and requirements that come from third parties for your on premise data, I’ve also seen a lot of cases where IT has gone to great lengths to be able to very securely control who’s got access to the information. But all it takes is one person who has a valid login, who’s approved to get access to data, to go in and run a giant query, pull that information out, dump it into a CSV file, an excel spreadsheet, stick it on their laptop and then jump on an airplane and start working with it. The minute that laptop goes missing, that data is vulnerable. Even though it’s no longer on premise, it’s just as vulnerable because it’s now sitting on a laptop or, god forbid, on a tablet or some other device. And so, you’ve also got to look at security from a standpoint of it’s not just where it’s being stored but also how it’s being consumed, and I think it’s one of those things, and again it’s a case-by-case basis. Different organizations, different industries have different practices and, you know, not all IT and security departments are created equal, but I think it’s time that folks who just claim that there is no security in the cloud—I hear all these breeches [00:16:00] from things, you know like Target and some of these other sites—that it’s not possible to have security in the cloud.

Well, first of all, that exact same breech can happen on premise. Don’t think that it doesn’t. There are hundreds of case studies that actually, you know, demonstrate that thing, but it also depends on what you’re storing in a cloud. And not to make this information from the answer to this question too long winded, but the other thing that’s important to know is that you need to be careful. You need to be prudent about what you’re storing. At DOMO, for example, we won’t take what’s known as PII, or personally identifiable information. We won’t store it. One, it’s…simply there are a lot of industries out there with regulatory compliance—it just simply isn’t allowed, and two, your insurance company and my insurance company certainly wouldn’t like that. The indemnity clauses would look a lot different. So by choosing the information that we’re actually storing in the cloud, you can store information that is useful to your users without giving up or putting yourself into a situation like a Target, where we’ve got credit card members, social security numbers, customer addresses or passwords stored either in an encrypted or unencrypted manner. So it’s one, about being smart about the infrastructure, and you got to know what you’re doing; and two, it’s being smart about the data that you’re actually storing within that infrastructure and making it accessible to your users.

KAREN:  So is there any chance why I would want an on premise solution?

CHRIS:  So, you’re definitely going to want an on premise solution for…well, for example, for PII, or if I’m in health care, it’s typically referred to as PHI or personal health care information—so, images of my x-ray, again, social security numbers, patient IDs, addresses, credit cards, those types of things. Depending on the industry you’re in, there’s most likely government requirements and certainly, I would guess that there are insurance and indemnity requirements that prohibit you from storing that type of information in the cloud. And that’s exactly what on premise data bases [00:18:00] are for among other things, is to be able to store that.

Now the beauty of something like a DOMO is when you can combine the best of both worlds that says, “Alright, I’m going to store, for example, all of my order transaction information in the cloud, but I’m not going to store any PII. I’m going to mask that information or I’m just not even going to stick it up there at all.” But when a user says, “Hey, I need to be able to look up a particular transaction because there’s a problem with credit cards,” or “There was a problem with shipping, so I need to see a particular address,” or “There’s a question about a particular patient record in health care,” being able to drill through to an on premise application, and by that what I mean is, I look at say, for example, a chart, or table, or a map or a graph, in a cloud-based solution like at DOMO. I drill down to whatever level I’ve got inside the cloud, and then if there’s a particular analyst or a particular user who has a one-off question about, you know, Suzy Jones’ credit card transaction on this date, with a single click we can then launch a new window that opens up whatever the application is that’s running on premise.

So just because you’re not storing it in the cloud, doesn’t mean you don’t get access to it; there are ways to do that. That’s something at which I believe DOMO excels compared with solutions that I’ve worked with in the past, but you also need a provider that knows this, that understands 1) what are the limits and what are the benefits? Where do we draw the line, and can help you chose what’s the right stuff to be storing in the cloud and also, by the way, for how long? There are certain industries where there are regulations that require you to pull information from certain places after certain dates and obviously, working with a vendor who has done this hundreds and hundreds of times is going to help you figure out “okay is it possible to securely store information in the cloud that I can make available to my users, but still give them access to the things they need that are on premise, like that personal identifiable information, when they need to get to it? [00:20:00] Does that answer the question or did I just half answer it?

KAREN:  Yeah. No I think that was great, Chris. I think that leads us well into our next section. Something I hear so much out there is user adoption. My biggest fear purchasing a fancy BI or analytics solution is it’s going to become shelf ware. I’ll make a great investment and no one uses it. Can you tell me a little bit about your experience in actually getting these solutions used and making this investment worthwhile?

CHRIS:  Yeah, no, that’s a great question, and I have a lot of experience with this, actually, on both sides of the fence. I spent a long time, almost a decade, at one of the big stack BI vendors, and I typically worked with very large accounts. I was typically involved with accounts that had ten thousand or more seats, and actually the majority of them were fifty thousand or more users that were using the software. The single biggest challenge that you face with user adoption is to forget these three words: change is scary. From a user perspective, when they’re getting access to data that they need, whether it’s through some cumbersome method like asking someone in IT to run a query and then dumping that into excel, and then applying some filters, and then converting that into charts and then cutting and pasting it into PowerPoint. If it gets the job done and they know how to do it, the minute you come along and tell someone they’ve got a better way to do and it’s going to replace that old thing that you’re doing, you’re going to put people back on their heels. So, you need to take the “change is scary” perspective from a couple of different angles.

First and foremost, don’t try and boil the ocean. If you’re looking at a corporate-wide BI solution, don’t roll it out all at once. I’ll repeat that; don’t roll it out all at once. I have lived this many times before. In fact, at DOMO, our philosophy is very simple [00:22:00]. We’re going to target a specific area of the business or a specific champion or specific product, or project, or region, or branch, specific subject area, and we’re going to start with a handful of users. We’re going to start with ten, twenty, fifty, a hundred users, and we’re going to get that into the hands of those users, and also empower them with feedback on what’s working and what’s not. And oh by the way, while we’re doing that, we’re not going to take away their existing solution so that they’ve always got a fall back. You’ve got to give people time to transition into this.

The other thing that’s very important to note about all of this is that if you are going into a scenario, which happens a lot at DOMO, where you’re going to start managing the business to a series of metrics. So we’re now going to get everyone on the same page in terms of this is what we mean by a sale; this is what we mean by a customer; this is what we mean by quarter; this is what we mean by cancelled; this is what we mean by patient, or bed. You’ve got to ensure that you’ve got buy-in from all the people that are going to be consuming that metric, because if I’ve got…for example, this happened at a super regional bank that is now a DOMO customer. We went in from the CFO of the parent organization who wanted to make financial metrics available to three different branches; oh I’m sorry, to three different areas of the business. So there was retail banking; there was commercial banking and then real estate, which was divided separately.

The problem is, the ways that they looked at certain metrics were very, very different in those three different divisions, and then they were rolled up and massaged before they got to the top member. Well, the CFO wanted that process to go away, but he didn’t have any buy-in from the leaders of those two base…of the three divisions. So there was a lot of resistance, and there was a lot of trying to come up with excuses of why DOMO wasn’t going to be a good fit or anything else for that matter. We just happen to be the ones that were selected. It had nothing to do with the technology; it had to do with the fact that the business process was being disrupted, and those people didn’t have any voice [00:24:00] into what was happening. And there are a couple of ways to skin that cat.

One is, you get everybody in a room and you get them to agree, which is exactly what happened at the super regional bank. In fact, we, the DOMO folks, sat there. We didn’t talk for over three hours. There was some red-faced, fist-pounding conversations going on back and forth with the executives. And it was one of those things that we literally worked from breakfast to lunch before there was a consensus, and we guided them through part of that process, but a lot of that they had to work out on their own. But keep in mind there is another solution. As opposed to forcing everyone to row in the same direction with the same series of numbers when they’ve done it a different way for twenty years, give them both. Have the page with all the metrics on it that you’re going to manage to the business, but give them the ability to also look at the information the way that they want to. Give them a period of transition, so they can get used to the new stuff without having to trip over the fact that they’re losing the old stuff. And I think giving those users a voice, choosing the specific subject area, preferably someone who’s a champion or coach or someone who’s got visibility in the organization, and then being smart about what it is that you’re rolling out are the three things that can help guide user adoption. If you don’t give them a voice, if you try and force something down their throat, it doesn’t matter how beautiful it is. If you start making people do something a different way, specifically when it’s the entire organization at once, I’m not going to say it’s guaranteed failure, but I’d be willing to bet a month’s worth of pay check that you are not going to be successful, and certainly not successful in a short amount of time.

KAREN:  So I think that was a great high-level approach to user adoption Chris. Can you maybe share some highly practical examples or something from a recent client deployment that you’ve experienced?

CHRIS:  Well, for example, like the one…the one I was talking about for the bank, for the super regional. The decision was ultimately made because they didn’t have metrics defined they were basically, everyone, [00:26:00] kind of managing their own corner of their store their own way. What they ended up doing was delaying the implementation by a couple of days so that they could literally pow-wow and figure out what those metrics were going to be for the business, and, more importantly, how they were going to be calculated. And of course we were with them every step of the way, because this is something that we do on a regular basis. So, in that particular case, it was a “come to Jesus” right? They literally…the CFO…we saved his bacon. At the end of the day because we got everybody else in line by giving them a voice and then discussing what the right ways were and, ultimately, the single right way to calculate the various metrics.

Another example was actually a health care company that I worked with on the west coast, and they took the opposite approach to the one I was talking about before. They’d done this before. They did it with one of the big stack vendors, and it wasn’t successful partly because of the technology, but mostly because, again, they hadn’t given anyone a voice. So there was a lot of resistance. And I don’t know if folks on the phone will agree with this, but I staunchly defend this statement: you get one shot at user adoption, and if you get users to come into the system and for whatever reason leave, it is almost impossible to get them back to get a second shot at gaining their trust. That first date has got to be a really good one if they’re going to take the call for a second date.

So what the health care company ended up doing was they created multiple views, if you will, of the fifteen metrics that they were using. In their particular case, it was around marketing. So what they actually did was the chief marketing officer of the parent organization said these are the metrics that I want to manage to, and we knew what the calculations were to get there. So she had her own page that was used by her team. Every single one of the region directors; they had access to that exact same page, but then they also had access…each of them had their own private page of additional metrics that were calculated the old fashioned way [00:28:00], if you will. The way they were doing it, in their case, was put this big stack vendor, which in most cases they would then just dump that BI vendor’s data into excel, and then massage it in excel.

So when they were going in for the quarterly reviews or any time there was a question about a spike or a different anomaly, they were talking to the number that the CMO wanted to see, but they also had their number to back it up. So it was…I basically, I call it a safety blanket. It was very much like Linus walking around with his blanket from Peanuts, you know what I mean. Being able to have that comfort of knowing that I’m still able to talk about what the numbers the way I calculate it and how that translates into the overall number. Now, is it more cumbersome? Yes. Is there more data coming into the system and more work to do that? Absolutely, but the CMO knew that if we didn’t give that runway to those users to get the plane up to speed before we take off into the big blue sky of “we’re all going to be looking at the same number,” she was going to lose those users and never get them back, and there was no way that she was going to have a failed investment again. She didn’t want any more shelf ware.

And what we found is over…we thought it was going to be about six months; it took about four, that in about four months, because we have usage statistics on every report and every page the administrator within a DOMO instance can see who’s looking up what and how often, the usage of those individual private pages declined dramatically to the point that we no longer even had to run the queries to populate those particular personal examples. So, how we skin the cat for your organization is going to depend entirely on the culture, on what’s happened in the past, what the history is, and, quite frankly, who’s in charge of rolling out this organization? If it’s the CEO, it’s a lot easier to get everyone rowing on the same page. When it’s somebody farther down in the food chain, you’re going to need to get by it; you’ve got to build a coalition. Again we’ve done this hundreds of times, and a lot of us at DOMO have done it hundreds of times at other places before we came to DOMO, so we’ve really learned the hard way in what the right way is to get user adoption.

KAREN:  That’s some good feedback, Chris.

CHRIS:  Was that too long? That was really long, sorry. You’d think I’m being paid by the [00:30:00] the word here.

KAREN:  That’s fine. I think we could probably spend the entire day talking about customer examples and user adoptions.

CHRIS:   I could. I really could.

KAREN:  So let’s move on to the next area here: cost of ownership. Now, this is almost the polar opposite of user adoption or lack thereof. What if I buy a BI solution and we’re starting to go gang busters with the tool; we’re using it extensively in all departments. There starts to become some unknowns involved, like how many full-time administrators do I need for this? Is there going to be extra hardware involved or extra software? How about custom training and consulting? There are so many different pieces of the pie when it comes to cost of ownership. How do you suggest listeners grapple with this subject?

CHRIS:  Well, it’s a good question. And obviously the vendor that you talk to is going to give you a perspective, right? I mean I, again, I’ve worked for a very long time in on premise solutions, and I’ve spent the last three years focusing specifically on cloud-based BI. The trick with cost of ownership is that there’s no right way to calculate the number, and at the end of the day, I don’t care who you are, what industry you’re in or how long you’ve been doing it, there is no such thing as a concrete number across the board. I mean, obviously there are certain costs that are very easily calculated, right? We know how many servers we’re going to need. We know the cost of the software that we need to actually put on our servers, both from the vendor itself, as well as the operating system that we need to keep those lights on. We know how much a hard drive costs and a cable costs. We know how much we’re paying the IT folks who are keeping those particular lights on.

Then you start getting into some of the more funky costs, some of the stuff that’s a lot softer. And that could be as simple as the actual amount of money spent on something like professional services, where one organization that I worked for, the professional service to drag was literally four to one, and what I mean by that is [00:32:00] for every dollar that the average customer spent on the license for the BI software, they spent an additional $4 turning the thing on and keeping it on over time. That’s a substantial investment, and you’re trusting that the vendor that you’re talking to, that’s going to give you those kind of numbers, is being accurate. And guess what, even if the vendor is not being dishonest, which I would hope that they’re not, there are so many factors internally like, Karen, as you pointed out, suddenly a bunch more people want to use it. Now we’ve got all these other data sources coming in; we’ve got to join all this other stuff; we’ve got to build these new metrics. Things that you hadn’t anticipated that suddenly require additional consultants, or additional consulting skills, that we hire in to be able to support that. It’s almost impossible to accurately forecast that particular number.

And then, of course, there’s the completely fuzzy number around cost of ownership, and that is not just the time it takes…you know, I know it’s going to cost ‘X’ dollars to train ‘X’ number of users at this site over the coming three months, for example. But what about the lost productivity, or the time that it takes for users to learn the new system efficiently? And what’s the impact going to be on the BI team, or the IT team or the analysts in the short term? How do we calculate those kinds of dollars, and oh by the way, like, again, Karen, back to your example, the minute you explode the number of data sources or explode the number of subject areas, that tends to grow exponentially.

So, coming up with an overall number is very difficult to do with traditional BI, not to mention the whole argument of, you know, it’s a good thing when the software you buy takes off like gang busters, but it’s also a bad thing because suddenly we need a lot more servers, and we need more FTDs, and we’ve got to now maintain the security and the infrastructure that goes along with all of that. So when you look at cloud based BI, a lot of that gets eliminated, certainly on the front, from the standpoint of “I don’t have any hardware cost to worry about, right?” It’s just like using Salesforce. It doesn’t matter to [00:34:00] you what hardware Salesforce has to use to keep the lights on for your instance because guess what? That’s their problem. You’ve got a contract that says you’ve got this number of users. This is the performance that you’re going to get; it’s Salesforce’s problem to keep the lights on. Exactly the same at DOMO—if we’ve got a firmware hardware added, we’ve got a firmware hardware added. There’s no impact to you from a pricing perspective. But when you start talking about the consulting, and the training, and the lost productivity and all the things that go along with, “hey we’re bringing in HR and financing and we’re going to join that up,” wow, I wonder how long that’s going to take to actually get that up and running.

Again, you want to look for a vendor that’s not going to nickel and dime you to death, and that’s, quite frankly, is one of the main reasons that I chose to come to DOMO— aside from the fact that I’m a geek and I love the way we’ve implemented the technology, is that we’re not nickeling and diming users. There is no change for the volume of data that’s you’re bringing in or the number of reports that you build. You’ve got at your disposal business consultants and customer success managers who will walk you through what’s the right way to visualize this data? I know how to get the data in, but what’s the right way to look at it? Should it be a heat map? Should it be a bubble chart? Should it be a scatter plot? How do I make this most effective? That should all be included in a license that is basically based on users.

So that I can literally say, “Alright, I’ve got a hundred users today and if this goes the way that I want to, I’m going to have a thousand users in nine months.” You know what the cost is, and certainly from the vendor’s perspective. And that vendor, such as DOMO, can then guide you through what it’s going to take to keep the lights on, on your side of the fence. Because obviously someone’s going to have to write the queries; someone’s going to have to show the users, but if the software is designed in a way that it doesn’t take a team of people to keep those lights on, then it becomes much easier to come up with a relatively accurate forecast on what kind of dollars you’re going to spend to basically do the stuff on your side of the fence, if you will, the stuff that’s not in the cloud. Was that a little fuzzy [00:36:00]? Was that not targeted? I don’t know.

KAREN:  I think that was a great answer, especially as we roll into the next section that really coincides with cost of ownership, and that’s implementation and deployment. Out of the hundreds of folks that are logged in right now, 40% of you named this as your biggest concern when choosing a right BI solution. That’s a massive amount of you and the largest concern out of the five we’ve listed today. So I’m going to shoot a test question at you, Chris. One of the things I’ve heard so commonly is “our ‘go live’ date was off by ninety days,” or even worse, “the implementation is taking a year longer than the sales guy told us.” Wow, those are real concerns that everyone has on the line today. Can you address some of these for us?

CHRIS:   Yes, well the first thing I can tell you is never listen to the sales guy when he tells you how long the deployment’s going to take. That’s what geeks like me are in the room for. And any vendor that you’re talking to where the sales team is literally on their own, telling you how long it’s going to take, you want to be suspect of that. That’s obviously…unless they literally have lots and lots of examples to back it up, I would never trust that number. But really, Karen, the question you asked kind of ties a bow around the things we’ve been talking about. In fact I don’t think it’s a tough question. I think you just threw me a soft ball, because this goes back to exactly what I was talking about; from an adoption standpoint, don’t boil the ocean. The first thing that you want to do is have a very targeted, specific project, preferably with a champion or a coach who will be there to help ra-ra the application within the organization. You need somebody to cheer at the end of the day.

The second thing that’s important is, again if you’re an on…if you’re going after on premise, you’re going to need the technological expertise. That, we feel, is the beauty of a cloud-based BI solution—is all you have to do is know where your data is [00:38:00], install some agents. We start pumping data up into the cloud, securely, and you’re good to go. You aren’t aware of any of the infrastructure, so you can dramatically shorten the time that it takes. But you also need somebody who understands your business. As an example, in fact this just happened, we just were placed on analytics solution at a retail customer, well it’s actually a CPG; it’s a packaged goods company, but they work directly…there’s some retail involved as well. I’m getting off track here. It’s a cool company. But what their problem was, was that they originally bought for the sales team. And so they bought an analytics package that worked with their sales automation software, and it was great.

And the vendor that they had selected knew sales backwards and forwards. They could help them choose all the right metrics, and the reports were really good and stuff was even available on mobile, but the minute they said, “hey wait a minute, we want to bring in HR data, and finance data, and operations data and supply chain data, those were the four additional areas that they wanted to bring in, that vendor told them it was going to be…I think they said it was three months. Whatever the initial estimate was, it ended up being almost nine months, and they went over by almost a million dollars in consulting fees because that vendor didn’t know the other areas of the business. All they knew was sales. And so my point to that long-winded example is, you need expertise not just on your side of the fence, but also on the vendor’s side of the fence, across the board. It can’t be just sales if you are at any time going to roll this information out to people outside of the sales organization, or conversely, give information from other parts of the business to that sales team. If there is no expertise on how to get the data in or what the systems look like on the backend or what kind of metrics should be measured, then you’re in trouble.

Again, I think…in fact, I think the single, most under sold value of DOMO, specifically, is we’ve got expertise across [00:40:00] the board. We’ve got sixteen thousand pre-built metrics. So if you say to me, “I’m a CMO in the automotive industry who’s using Maketo, and Eloqua and Radian6, and I care about campaign effectiveness and social presence,” I can go to that library and pull out thirty or forty metrics that may be of use to you, and we can get you up and running. And oh, by the way, I know what the systems look like behind the scenes. So I think that, from an implementation and deployment standpoint, among all the other things that we talked about today, you need that expertise, and then at the end of the day, some of that’s going to be gut. You should trust your gut, and if there are any questions, you should just talk to that vendor’s customers. Say, “I want three references. I want to talk to these people to find out what did it really take to get this thing up and running?” You wouldn’t hire a contractor without seeing his work, why would you do anything different for a BI vendor?

KAREN:  So Chris, what would you say to someone who’s on the line right now and is stuck in a terrible implementation and deployment? Do you have any advice for them?

CHRIS:  Vodka or Crown Royal is always a good start. Aside from that, I think it’s hard to say. I would love to talk to that person individually to find out specifically, you know, what the challenges are; is it a problem with technology, is it performance, is it adoption, those kind of things. There’s almost always a way to salvage something that you’re working with, and it may end up being, you know, a sub set or just a slice of what you initially envisioned. But, again, I feel like I’m just doing nothing but plugging DOMO here today, but I’m going to sort this out because this happens a lot—is that users have…customers will have big stack vendors or they’ll have desktop applications that claim to do, you know, web-based and mobile BI, that don’t. And we’ll come in and overlay those applications.

Instead of exploding away your business objects, or your microstrategy, or your tablo or your click, those all have great purposes and are used by certain people in the organization, let’s leverage the technology you’ve already invested in but make it available [00:42:00] to more constituents or to different constituents. So that’s one approach. And then the other is sometimes, I hate to say it; sometimes you just got to pull the plug. Sometimes you’ve literally got to stop throwing good money at the bad, again, depending on the situation. And it may be time to say, “we’re going to stop this; we’re going to reevaluate; and we’re going to go in a new direction.” I mean it’s just one of those things that, again, I would love to talk to that person one on one, just to get some more insight, and then see, you know, what the options might be for making some lemonade out of those lemons.

KAREN:  Great, Chris. And we are getting some questions coming in. I encourage you to use that question button at the top of the panel there if you have something specific you’d like me to ask Chris. And as we continue, Chris can you tell us just briefly about DOMO? I know a lot of people are texting in here, in the question section, wanting to know about [inaudible 00:42:56] and how long it can take to deploy? So many questions coming through, so can you spend a few minutes on DOMO for us?

CHRIS:  Sure, absolutely. So, again, for those of you that don’t know, we obviously are a cloud-based BI provider. We were founded just about three years ago by a guy named Josh James, and Josh had formerly found and run a company called Omniture—a web analytics company that he sold to Adobe several years ago for 1.8 billion dollars. And Josh and his team know cloud very well; In fact, they have the second largest cloud-based instance behind Salesforce in the world. And so, again, one of my decisions to come to DOMO was that a lot of vendors had claimed to do cloud, but they had no technological expertise or experience, and you can’t change the engine on the plane in midflight when you go down a path to developing auto cloud infrastructure. So I wanted to go with the best, which is why I chose to come to DOMO.

Our philosophy is, let’s give you access to all your data, regardless of what it’s sitting in, databases, or applications, or spreadsheets, or flat files, or cubes. And let’s bring that [00:44:00] in and put it on a web browser or a mobile device and allow your users to consume it, but we’re going to walk you through every step of the way on how to get there. We’re not going to just give you a license and a login and say good luck to you, and we’re not just going to charge you money for every report or every query or every page that you build inside of a dashboard, but instead roll all of that into a single user base price, and then get you to where you need to be so that you’re…everyone in your organization is looking at the same metrics and is able to then collaborate around those, and that’s really what our philosophy is.

From a deployment perspective, I can’t give you an answer. In fact, if I gave you one, it would be BS. It would depend entirely on the organization, their maturity level, the industry that they’re in, what are the applications that they’re using, who the users are, but I can give you what we know to be the averages based on having done this hundreds and hundreds of times. The shortest deployment time that I’ve ever seen is four hours, and that’s a one-off case. It was one of my favorite examples. All the queries were ready to go; they literally just plugged them into DOMO. We actually did very little work in that case and they had a working dashboard in four hours. That’s definitely the exception, not the rule. On average, it takes between two to six weeks. Again, remember, a lot of times people will hear that number and they’re like, “Are you crazy? Are you already drinking that vodka and Crown you talked about?” And the answer is, well, I’m not going to answer that. The reason that it’s only two to six weeks is that we’re talking specifically about a targeted user group, with targeted subject areas, and because of that we’ve got targeted data sources that we’re going after. So, we will typically phase the approach in. If you say, “I want sales, and I want operations, and I want HR and I want finance, that’s great.” Let’s pick the highest value target first, and then the second highest value, and then the third and so on, and we’ll do that in a phased approach to ensure that user adoption, to keep your implementation costs low on your side of the fence, and also to ensure that we’re getting the best bang for the buck [00:46:00] both in terms of what you’re delivering and what your future is in terms of rolling that out to other users and other groups. That’s what we do.

KAREN:  Okay, and unfortunately we have just two minutes left here. I know that we could spend probably another hour asking and answering questions. Quite a few coming in about product specific questions: “I’d like to set up to DOMO,” “Can you tell me more about pricing?” Go ahead and reach out to us at info@domo, and we can connect you with someone fairly instantaneously to answer those questions. If we haven’t answered your question, we will get back to you today with a personal answer. And I also wanted to encourage you to tweet your questions to us @domotalk, to @chrisatdomo and then or myself @KarenMWarner. Chris would you like to close things out for us today?

CHRIS:   Yeah, I was just going to say guys, one, thank you for letting us go over, two, if you actually stuck with us through this whole presentation, then you deserve a vodka or Crown for putting up with me for that long, but I encourage you to do exactly what Karen said. Get us either through twitter, or just go directly to, send an email to, directly to info@domo, and let’s talk. Let’s talk less about us, and more about you, and figure out is there a fit? And from there we can determine, you know, what is it that you want to look at. We’ll let you take her for a test drive, see what you think and we’ll go from there.

KAREN:  Great, well thank you so much for joining us everyone. We are looking forward to working with you in the future. And, as a reminder, this web cast is available in an on-demand version and that will be available in approximately ten minutes here. So, thank you so much. We look forward to working with you in the future.

CHRIS:  Thank you, Karen.