Listen to TIBCO Analytics SVP Brian Gentile share how advanced analytics can quickly enable anyone in an organization to get the right answers from their data and gain better insights for better decision-making.
Ellis: Welcome to the TIBCO podcast. I’m your moderator Ellis Booker. Today, our guest is Brian Gentile, senior vice president and general manager of TIBCO’s analytics products business unit. Hello, Brian.
Brian: Hello, Ellis, thanks for having me.
Ellis: Brian, you’ve been at TIBCO for about a year now following the April 2014 acquisition of Jaspersoft, the commercial open source business analytics software company that you led. You now lead the newly formed TIBCO analytics business unit. What’s the mandate of TIBCO analytics?
Brian: Our mission is to more quickly enable everyone or maybe anyone in an organization to get the right answers from their data to build better insight and make better decisions. So we’re all about quick answers even in complicated data situations.
Ellis: How big is the staff, the footprint of TIBCO analytics?
Brian: We’re proudly a top ten business analytics, business intelligence provider by revenue and employee count. We have more than 500 employees at TIBCO analytics. We would have a leading market share based on the customer base for both Spotfire and Jaspersoft. And we have a third of plans to ensure leadership position in the markets in which we compete going forward.
Ellis: What with big data news, the growing importance of streaming analytics, not to mention of all the mergers and acquisitions in the space, a year in the business analytics world can be a very long time. What’s the biggest event and the biggest trend you’ve seen?
Brian: Twenty five to 30 years of existence of business intelligence tools, the most disappointing element of this market is that only 20 to 25% of an organization really uses analytics or business intelligence against any amount of data today to make business decisions, 20 to 25% of an organization today. So looked at with objectivity, you could say we’ve failed the market in the goal of reaching widespread adoption of putting analytics and business intelligence to work.
So the biggest trend that I see in it, TIBCO analytics is laser focused on solving, is reaching the other 75 to 80% of those who in any organization have had so far no use for a business analytics tool. While at the same time, we want to make the lives of those who are analysts, those who do use tools, to become even more capably analytic, even richer in their use of these tools. So in total, we want to reach a 100% of an organization with a more data-driven environment.
Ellis: You said also that TIBCO’s long-term aim is to re-imagine business analytics, the way it’s designed, developed, delivered, deployed, and consumed. As you said, getting the penetration rate up is obviously an aim, but are there other objectives that are pushing TIBCO and the marketplace in that direction?
Brian: Yeah, there really are. I think our major failing of the past, and by “our” I mean the marketplace and those vendors who, like TIBCO analytics, have created tools, our biggest failing has been that we think we’ve thought about the world as a tool and business analytics as a tools-based approach and a tools-based solution. What we’ve expected, more end users, more business users to come to the tool to analyze data. So we’ve taken this very tools-centric approach when, in fact, looking at the world as a tool has quite a lot of shortcomings.
I’d like to say that the future of analytics is that it becomes a thing that you do [inaudible 00:04:08] a place that you go. And so we have to re-imagine analytics and the way it’s delivered, deployed, and consumed in an organization. We have to re-imagine it as a series of workspaces and, ultimately, as a set of fabric that impacts every person in the organization the right point in the day when a decision needs to be made.
So this is how we will overcome the failings of the last 25 or 30 years in business analytics and find a way to reach and be relevant to everyone in an organization.
Ellis: Let me play devil’s advocate just for a second, and that is, isn’t there a worry, and I’ve heard this worry from some executives, that handing analytic tools to those who may not have been schooled in data design or statistical methods may cause trouble? In other words, you’re going to get business owners reaching wrong conclusions because they’re not schooled in the discipline of data analytics. What would you say to that?
Brian: We have to find ways to bring more skillful guided analytics to a broader base of users. It’s true that today, in an enterprise, only a fraction of the knowledge workers are properly skilled to truly analyze data. There’s the elusive data scientist role, and the scarcity figures you’ve heard around that role are most assuredly accurate. But the truth is is that everyone in an organization at some point of the day must be somewhat capably analytic to make a decision based on some data. So the feeling so far has been that we’ve expected them to go to a tool. Now, what we should do is we should provide them with a guided set of analytics that helps pull them through, helps them make an analytic decision by doing more of the work for them.
And the notion of workspaces, the notion of analytic workspace is our future vision for replacing the concept of a specific tool and, instead, replace it with a personalized, tailored workspace that understands your skill level and that delivers just the right amount of analytic strength and capability within a web-delivered cloud-based or cloud-architected service that learns as you learn, learns about you, and is able to make recommendations for you to help make you a more capable analyst even if your job is very far from being an analyst. It should be able to help you and pull you through into a better analytic outcome. So this is how we’ll get more accurate, more involved personnel at any level in an organization with almost any skill level.
Ellis: Does TIBCO have any customers mapped to that call it the next generation of [inaudible 00:07:09] an enterprise? And what does that look like? Without perhaps giving us names of companies, customers of yours, can you give me a sense of how those companies function differently in this environment?
Brian: Well, the data certainly showed that data driven organizations make sharper, clearer decisions that end up in better business results. So the race to put more information to work inside of an organization is on. And in fact, what I see and talk to more customers about today than ever before is the construction of business models, entire business plans and business models where they’re using information and monetizing it as a way to create new markets and new revenue, not just to save costs and create efficiency, but, literally, to drive new business.
And so today, I would say that any enterprise, every enterprise is an information-based enterprise. And you’ll either be finding ways to put data to work, creating insight and information that you can monetize and create value from, or you’re going to be left in a less than relevant market position because your competitors are doing so.
Ellis: A moment ago, you talked about the elusive data scientist. And I suppose no conversation about business analytics is complete without talking about what organizations are doing vis-a-vis hiring and the difficulty we hear many are having hiring staff with the requisite skills. Do you have any advice for where to look for talented analysts and, more so, how to retain them once they’ve been hired?
Brian: Yes, you’re right. This is one of the most important elements today in building an information-based and data-driven enterprise. Skillful data scientists and data analysts are a critical nucleus of knowledge and insight that can be cascaded when done well. So finding and building a team of data scientists and data analysts must be the goal.
I’m pleased that as I travel, especially to universities, I’m seeing a much greater interest in degree programs, certificates and degrees at both the undergraduate and graduate level where business analytics is the topic and the focus in a major. And so that’s encouraging and even exciting to know that every year we’ll see a higher percentage of graduates leaving with genuine depths of understanding in business analytics.
The other element, though, that’s so important is the concept of putting analytics into the applications that we use every day. So how can a data scientist reach more people? Part of it is by training and skill transfer and modeling and so on. And all those techniques need to be used. The other technique, though, is the concept of analytics fabric, where we are putting just the right amount of analytics inside of the applications and business processes that we use every day, the right context, so that, literally, any level or skill of user of that application will be able to interact with data and make better decisions based on it, yielding new insights and better business outcomes.
So the concept of a data scientist becomes not only important for the skill-building and transfer that it represents, but the modeling and application-building that comes from that person to enable everyone in an organization to touch and be part of the analytic conversation at some point during the day.
Ellis: Brian, let’s talk about the power centers for analytics initiatives inside organizations. It’s the case, isn’t it, that it’s expanding beyond the chief information officer’s office to people like the chief financial officer and the chief marketing officer? Why is that happening and what does that change mean for companies like TIBCO?
Brian: The drive to new executives being involved in analytics is caused by the need to create business models that are based on information or to be more competitive in putting more information to work more quickly. In this regard, some of the IT teams of the last 20 years have not been able to keep pace with the demand and the need within business units and the line of business functions for putting information to work competitively.
So you’re seeing chief marketing officers and chief revenue officers and even G&A functions, like human resources, taking charge of the data that’s at their disposal, wanting to put it to work more quickly, more readily, more broadly so that they can create competitive advantage within their function or within their business unit. And if they don’t do it, they know that the cost is likely irrelevancy versus their competition. So there’s this incredible competitive game stake that’s creating line of business and business unit functional increase in the information- and data-driven world.
Ellis: And have we gotten over the hump of making the case for data analytic projects, investments rather, with top management? Or is that still an ongoing battle?
Brian: I think the need for clear return on investments will always be important. I think the amount of data that we had the data put to work and the possibilities for creating value are so vast that the return on investment equations are becoming more straightforward. That said, they’re still important. And understanding where, when, and how you’re going to put data to work and at what cost to create what valuable outcome is still a valuable exercise to go through.
Ellis: Great answer, Brian. And I’m afraid it’s going to have to be the last one. Thank you so much for joining this podcast. And thanks to our audience for listening.
Brian: My pleasure. Thanks for your time today, too, Ellis.