 Live from the Hilton at Bonnet Creek, Orlando, Florida, extracting the signal from the noise, it's theCUBE, covering Vision 2015. Brought to you by IBM. And now your hosts, Dave Vellante and Jeff Frick. Hi buddy, we're back. This is Dave Vellante with Jeff Frick. Dan Beers here as the director of performance management at IBM. Dan, welcome to theCUBE. Thanks, thanks for having me. So, we were talking about hockey offline. We're all sad that our teams aren't in so I guess we'll just get right into it. We're talking about performance management. So when we talk about performance management, you came from Cognos. Sure did. Through acquisition and then you saw IBM put together this sort of awesome lineup of companies and now, as I was saying off camera, you guys are basically number one in this business but when we talk about performance management, how do you look at that and define performance management? Sure, well I look at performance management or in general financial and operational performance management. I put those two together. As really corporations that are going out and trying to make sure their strategic priorities are aligned with the resources to get them done. So many companies start off with what I would say is the bread and butter of financial performance which is your planning, your budgeting, your forecasting and what I would call more the automation of your transaction processing and your financial processes. But when you talk about true performance management and you graduate up from there, most companies are trying to achieve more alignment than that across the organization. So they're trying to make sure that their operational plans, their marketing campaigns, their sales revenue plans, their demand cycles, all map back to what is the financial plan to get there. And so when you go beyond budgeting and planning, you end up into what we call strategic performance management across the enterprise which is truly bridging operations and other divisions within your corporation back to finance. The business outcome you're trying to achieve is alignment of those. Alignment and adaptability. Versus just executing on reporting alone. Here's a P and L, here's a sales plan, here's a bunch of paper, electronic paper, go. Okay, so you're trying to optimize based on the, you mentioned the cycle, the various parts of the organization, the business process, the whole deal. Yeah, if you look at the industry and the leading companies that we certainly work with, most companies have figured out they have to be good at transaction processing and automate routines, basic financial processes. They have to close their books, they have to do taxation, they have to report those to the SEC and do disclosure filing and things like that. And those things are absolutely necessary in the industry and we also do those by the way in financial operational performance management. But what the leading organizations are doing are they're going beyond that and they're using more what I'll call financial analytics to bridge beyond finance into the operational cycles and using that to strategic advantage. So getting rid of the delays where you have someone in marketing thinking, boy, I'm going to run a campaign to go and make this product triple its sales. Whereas in your financial cycle, you don't even know that product exists or you're not planning for that type of increase. And yet marketing's looking for budget forward, it's going to run a campaign. And in sales, do they have a budget to go and hire folks to actually sell a product and how are they going to be compensated and how does that tie back to finance? So many companies use this whole tying of the enterprise together to truly be more nimble and be aligned across the organization. So you're asking off camera how familiar we are with the space. So I'm going to give you my version and it'll probably show you how unfamiliar I am. But you, of course, correct me. So it seems to me in the early days, I think we used to call this decision support. Lots of names, yes. And yeah, there were lots of names and different marketing things were tried and there was value, no question about it, but it certainly wasn't broad, broadly used throughout the organization. A few gurus used it, very high impact. I'm going to do certain things to drive, turn levers to drive my business, great. And then post-Enron, wow. Big opportunity for this business. You called it close and disclose, right? So companies becoming much more monitored and had to do compliance, legal regulations, and of course this is not just in the U.S., but overseas. Now it seems to have come full circle. You're talking about strategic performance management, you're seeing things like real-time, Watson analytics come in, and it supercharges this business even further. Maybe delivering on the original promise of decision support. So that's my version of the story. Help me course correct and sort of fill in again. Well, I think when people talked about decision support, they mixed up a few things. And of course not everyone, but in general, I think when you looked at the early days of this space, people were doing a process and it's mostly financial. They were looking at planning, they were looking at budgeting, then they had to close the books and account reconciliation, they had to file their taxes, they had to report that stuff to the regulators, whether it's internal stakeholders and shareholder reports and say the SEC, and then they had this process they had to do. And there were software pieces that would fit in each one of those things to help them with that process. And I think they would have many times back then also called that decision support pieces that helped them with these different pieces of the financial process. And I think where we then have evolved to from there was vendors, even ourselves, started putting that process, planning, budgeting, consolidation, right through the disclosure into a package and there was more suites, it was the evolution. Where I think we've evolved to today is it's gone beyond finance and that automation of that process, really. And that's where I see the decision optimization you're talking about is really truly bridging beyond finance to all of the information and divisions across your company and using that aggregated information to truly make insightful decisions using things like Watson, using things like predictive analysis, using things like optimized decision making that are much more advanced technologies today than we've ever had. And really where it ties back is you get an insight but it's not a value to you unless you act on it. So what good is an insight if you can't do anything with it? You know there's a hot stock. Someone just said you're going to make a million dollars to buy that stock but you don't have a way to buy the stock. It's not a much value to you. So the performance systems allow you to act on those insights by bringing it back to those systems. So full decision management as opposed to sort of decision support even of itself doesn't sound like active management. So I wonder if we could talk about sort of linking initiatives. Every company has a set of strategic objectives. It comes down from on high, okay we're going to grow 7% this year and these are the objectives that we have better customer service, faster growth and better profitability, et cetera. And we have initiatives that we're going to run to meet those objectives. And connecting those initiatives to actually the financial performance has always been a challenge. Is that sort of closing that loop? How if I succeed in these initiatives? Well first of all, how do I prioritize those? I can't fund all of them. So help me make some decisions as to which ones are going to help me drive my strategic goals. And maybe I'm using some balance scorecarding and some a little bit of gut feeling there. I'm using now analytics to drive that and connecting that to my performance, my financial performance. Is that loop actually being closed? Can you guys close that loop? Absolutely, that is exactly what our enterprise performance management solution does. So it does strategy management right from the top where you're doing strategic definition of what are your priorities. Takes that through to scorecarding as to what are those and how do you want to track them? What's the highs, what's the lows? How are you going to measure your business? It allows you then through the budgeting, planning and forecasting cycle to apply the right resources to those priorities so you know that you're actually going to achieve them because if you don't have the right human and capital resourcing, they're going nowhere and you can apply that and track it. And then it goes further to tie that to as I say beyond finance so you can roll out planning based solutions and things like profitability analysis and demand planning, marketing campaign management, all in the same solution that also ties back to that in support of those initiatives. So you're basically following down from your strategy, whether it's driver based planning or simply scorecarding to the actual processes and decisions that support that. So you're getting alignment through the organization. So if you think about the initiatives that a company's going to do, they're going to fund in a given year, it's 2015, we're going to do this, you decide in let's say September, October, you finalize it, the ink's drying in January, okay go. Yes. And 100% of the cases, the plan, some things are maybe better or some things are worse, right? Some projects get delayed and so forth. How are organizations dealing with that? Do they just sort of keep feeding on their people and say okay, catch up? Will they adjust? What's best practice? The leading ones are the nimble ones. The leading ones that have these support systems, these performance management solutions in place through the scorecarding and the monitoring and measuring of the business performance, they can see where they're succeeding, where they're failing. They can use technologies like you saw today that are integrating into our solution platform like Watson to do discovery of that data and understand root cause analysis and get to the bottom of what that is. And then they loop back and they take that insight they find to make adjustments to the plan. So what is it? Is this product, are they not profitable because of this product? Is it because something in the supply chain needs to be adjusted? Is it something in the warehouse cost because you have a storage problem? Is it that sales isn't selling it well because they're not trained or their commission plan is wrong? So they use the supporting, I would say, information, the knowledge systems, the discovery systems, advanced analytics to get that insight which they can in turn go and actually modify. On a more rapid basis than you're going to do say if you have a bunch of siloed and disconnected systems and spreadsheets that may not tie out and get updated maybe once a year. So how does it cascade? Because obviously the CEO who's ever setting the top level initiatives, their dashboard, their metrics are at a roll up of a much more granular as you work down between business unit heads and execution and then people on the ground, as you said, making decisions about delivery and sales compensation and all these other things. Is it all tied together? Is it, you have different kind of entries, portals, views into this data in different ways? How does it kind of all work between the guys in mahogany row and the guys down in the unloading trucks? So it's all into the same solution that we roll out and the different views are essentially what you would want to set up for a persona. You know, you use a sign on to understand what it is that you want to see and so obviously if you're an executive you're focused more on the strategy and the score card and where am I going at a 100,000 foot level? If you come down a couple layers and you want to implement something to be corrective well maybe you're an analyst in finance looking at what am I going to tweak what drivers am I going to pull to help correct the performance we're seeing. They have a different interface which is obviously a lot more in depth. You know, in many cases they use Excel still so we embrace and surround Excel but we do that in a way that we add structure to it, we add auditing, we add process flow, those types of things so it's an interface that's obviously different than you'd see in an executive use. And then when you break that out and you get to the operational span we're talking about you want to get out of finance they're not probably going to use Excel, could be someone that's not familiar with that level of even technicality that the complex Excel can bring you so you can get to a mobile interface, a web-based interface, ways that they can see the score card and the results and collaborate all to be in the same core content of what you're dealing with to span your enterprise but different user interfaces for the right audience. How are companies dealing with the data quality? Because I remember when you guys had this initiative to embrace Excel years ago, you realized, okay, there's all this data in Excel, our customers need us to do this. How are companies dealing with the data quality issues and the consistency? Yeah, I don't think that has ever changed. I mean, there's always that upfront step when you're initiating a system where you have to take stock of where you are in your enterprise, what data sources you have, how they intertwine, where they connected and where they linked and there's always going to be that cleansing if you will upfront effort which by the way we also in IBM have many technologies that do that data management and data cleansing, whether it's metadata management, whether it's extracts and transforms, to put that into a form that you can get some sanity out of. Now, many of them start with not that big of a project. I mean, if you're in finance and you have a number of spreadsheets today, they just connect those directly up to a prescribed business model that they use in our performance solution and go from there. So it's about magnitude, I suppose. How far do you want to go? Do you want to cleanse your whole company right away or do you want to start with a chunk you feel you can grab? But I don't think that challenge has gone away. The trustworthiness and the scrubbing of the data is always a prerequisite to having a baseline. Well, and the other thing too, if you elect to execute option A versus option B, both of them are my day job. A is in direct support of the 2015 corporate initiative. B isn't necessarily, it's just my regular day job. How is that kind of communicated back either down so I know to make that option or back up to see that I chose A and that's going to add some positive energy to that corporate initiative? Yeah, I think a lot of what you were saying, you're doing your strategy development upfront and you're setting those initiatives based on the strategy and you're hoping that those are trickling down that's the discipline that companies have to have. No solution's going to replace completely the human factor, which is managers have to manager people. They have to set priorities that are based on these roll downs. The difference is they're all sharing these in the central place right now and they can see their connectedness. They can see the initiatives they're working on. They can see the scorecards. They can see how they're progressing and then they can also contribute to that to see where the needle moves in terms of doing what if analysis planning on those particular metrics that they're monitoring and things like that. But you still obviously have to have a human performance culture that says you're aligning your people along the lines of your strategy with of course the systems that make that easier to do. Make it easier for the next year. It's always people process and the technology they say is the easy part is people in process that are the complicated pieces. But a big part of that, Dan, is the user experience and the UI. What specifically is IBM doing to sort of modernize, map into modern UIs, user experiences to accelerate adoption across the enterprise? Yeah, well our goal is to make solutions from right now that are easy to deploy, fast and simple to use. That's really what we're focused on. And so the way we look at it, starting from Watson and out, which you saw the new Watson technology we've been releasing over the past year, is to essentially take the smartest person in every role and put them in a box. That's the way we think of it. So when you have someone like even just in philosophy you have a deep hardcore data scientist. They know so much in their head about how to manipulate data. They may know statistics. They may know those types of advanced mathematics. Well our goal is to take that kind of knowledge and put it into the product in a way that anyone can use to the same level as that person. And so we believe that to go to this simplicity or this powerful model of spending enterprise you absolutely have to take the UIs and the user interfaces and the experiences and not design it for the lowest common denominator but make it persona ready but allow it to be consumed in a form that anyone in your organization could just intuitively pick it up and use it. Think web browser like. Anyone knows how to search. So that's the aim, is to put that power in the user's hands and put the smarts inside. So it's not just a simplicity of UI. It's a simplicity that has underlying smarts. So it does that manual work for you. Predictive's a great example. You know, not many people know how to make a predictive model and to do statistic modeling. Well our goal is in our performance management solutions to embed predictive technology right in. So if you have a particular forecast you need to make you drop down a menu and say run me a time series prediction. Ta-da, it comes out. Make it statistically accurate. Correct. And so I don't have to worry about that. You got it. You don't need to model it. You need to know how to model that and create the mathematical relations. The software has to do it for you. And that's why we say it has to be easy to deploy, fast and simple to use. How much customization of that type of framework do people do? Do they try to sort of inject their own sort of corporate edicts into that framework and can they do that with your solution? They absolutely can. I think the more often than not that is the norm. Many companies have that choice. They're going to have just a simple out-of-the-box solution that is a box around it that says this is what you can do. Where we are is what I like to call more a platform plus a solution. We have an underlying technology base that pretty much allows you to go as custom as you like but you don't need to. There's solutions that are out of the box that if you want to go and use those we call them blueprints and accelerators that you can say I want to do headcount planning. I want to do profbillion analysis. Well you can go and you can use that. What our experience is is that many companies especially as they get larger aren't willing to wrap their company around the product. They want to wrap the product around their company. So they'll engineer their processes or their systems to be a fit for them. And then our solutions will adapt to that because we are that platform plus solution. Start somewhere with the solution but then the power of that configuration lies underneath. Dan how about the state of visualization? And then we got to run, I'll give you one more question but where do we stand there? Is that what something that Watson's analytics is bringing to the table? You have other organic development? I'd say it's unified, we all leverage it. We have a number of visualization technologies within IBM. Watson exploits several of them and in turn we exploit them and Watson. So it all kind of connects together. What we've gotten way better at is not making six things that are the same. Many companies, certainly IBM is not a small company. You can be accused sometimes of having silos of developers making the same technology. We've gotten much better at doing that and leveraging each other's smarts. And so we have visualization and we all share it. Two other questions. So anything announcing at the show you want to talk about? That you want to tease? Things that you're talking about to the executives here? Yeah, I think the biggest thing we were talking about and we mentioned in our keynote main stage today is what maybe we refer to as TM1 Next and taking the embarrassment of riches we have across IBM and embedding those into our products and our performance solution incrementally over time cloud first. So delivering it quickly and continuously on the cloud and then as they reach the maturity and the adoption we want, putting them back onto on-premise. So it always benefits our on-premise customers too. But that's everything, as I said, from Watson Analytics to predictive technologies to constraint-based decision-making and optimization. All of those embarrassment of riches we have finding their way into what we would call this PM solution around TM1 Next. So last questions. Where do you see this business in three to five years? Kind of midterm view. Where's it headed? Well, a little futuristic question. If I had it my way, I think there'd be a lot more of that, what you call decision support and automation in the business. Where today, even in the predictive side or it's in the decision optimization side, if you look at the trend of where things are going in the industry in general and you think about what we announced today in our TM1 product voice recognition of planning, you're not clicking mouses all over, well, wouldn't it be great if you had more of that cognitive nature where it kind of understood in the underlying support systems of what you're trying to accomplish and was better at recommending for you so that we could have people spend more time on adding value and being productive and continue to eliminate the more mundane things that we have to do to keep our systems up and running. Excellent. Dan Veer, thanks very much for coming on theCUBE, sharing your knowledge, your insights, and good luck. Thanks again. Thanks for having me. All right, keep it right there, everybody. We'll be back. This is IBM Vision. This is theCUBE, right back.