How to automate smart decision making with BI and analytics

Making profitable business decisions faster and with greater agility is both a challenge and a goal for most organizations. Over the last several years, more sophisticated business intelligence technology has helped companies improve their data analysis and reporting capabilities. It has also extended data analysis responsibilities to more end-users within the organization (we've all heard the phrase 'BI for the casual user'). These are remarkable achievements. But forward-thinking companies will need to move from just managing data properly to capitalizing on it.

A number of new trends and best practices can help companies learn more from their data so they can make better business decisions,automatically. To learn more, hosted a webcast with Mark Smith, CEO and SVP of Research, Ventana Research offers a preview of the webcast on In this Q&A with editorial director Kerry Glance, Mark gives us a sneak peek at his webcast session and his thoughts on decision management technology.

Click here to view the webcast:
"How to automate smart decision making with BI and analytics."

Q: Mark, my first question is pretty basic. Where should a company start with a decision management project?

A: They should start by making sure they have a business case for a particular decision management project. And what I mean by that is, a business case that outlines that challenges that the company faces, the benefits that could be achieved to address those challenges. Then they should use some of the best practices that I will outline in my presentation today. They should really start to look at things and start to then look at how they can impact either a line of business area if you're in IT, or if you're in a business area, look at areas where you need to drive improvements. So, areas where you haven't necessarily had the right results in performance is where you should be looking at these kinds of best practices. In my presentation I will talk about decision volumes, workforce decision skills, the need for self service, these are critical areas that you can use for input for driving a business case and better understanding how to start a decision management project.

Q: Where do you think that BI, analytics and decision management technologies will actually evolve to?

A: Well, we're at a very interesting time where we are seeing technologies continue to evolve and integrate into larger platforms and tool sets. In my presentation today I will look at the diff technology "blocks," and many providers are now bringing one, two, three, four, five, but in the majority of cases -- two companies to evaluate. And so the industry and the technology are evolving at a pretty rapid pace, and the requirements for being more integrated into more systems have been driving additional mergers and acquisitions with companies.

And so the BI and analytics base is, beginning to understand the importance of rules and workflow and how the technology they have needs to be more integrated into the operational and real-time elements of decision management. And so we are really at an interesting time in leveraging the last decade of technology evolution and now, we're really looking at how these things become much more integrated into applications and application server platforms.

Q: You have mentioned that decision management is actually a piece of the overall performance management puzzle. Is that how you differentiate from the two?

A: That's true. In most cases companies are trying to actually drive some benefits or outcomes to improve, so we look at decision management as a supporting focus for companies who are trying to manage performance and get better results. In many cases these efforts have been much more focused on looking at historical information than trying to automate some of the actions and decisions that need to be made. So these are linked together, unfortunately a lot of the dialogue has been separate, but in case they are actually not, and we are talking about the same organizational executives and the same IT management trying to achieve some purpose, and the question now is, what is the right technology for trying to achieve those needs?

Q: Fair Isaac is one vendor to consider in decision management technology decisions, but can you mention any others? I realize there are a lot of different pieces of the decision management puzzle.

There are actually a lot, especially since decision management technology can actually span across many different categories. So looking at predictive models -- you can find predictive models coming out of vendors like SAS (SAS Inc.) or SPSS (SPSS Inc.) or Angoss (Angoss Software Corp.). You can find business rules coming out of vendors like ILOG (ILOG, Inc.), Corticon tech,(Corticon Technologies, Inc.) and there are probably a lot more there, too. Pegasystems (Pegasystems Inc.) is in this market as well. And of course then you get into BI and analytics, and those vendors can range from Business Objects to Cognos (Cognos Incorporated) to Hyperion (Hyperion Solutions Corporation ) and there are quite a few other suppliers. Fair Isaac (Fair Isaac Corporation) is one vendor who has brought together a set of technologies to work in a framework, and they have done that through building out their own products and also through acquisitions.

Q: Where do companies typically go wrong with decision management technology and or projects?

A: Great question. I think the answer to that is that they jump in to the technology first without having a good handle on what the business need is and the requirements and then determining what the tech is needed. So in many cases the company fails by not putting forward the right business case. The business case is important because it sets the benefits and the costs that are required to support the business needs. So that is classically where we see companies not really looking at the depth of the business needs, then going to the use case scenarios, and then out to the technology.

Q: Are there specific industries where decision management has been embraced and is more successfully employed more than other industries?

A: We have actually seen that the decision management technology has had the most impact on financial services, in banking and insurance. Of course there is the online world as well. That's what we've seen.

Q: How can you calculate ROI with decision management projects?

A: ROI is an interesting element. ROI is really a calculation of benefits over cost. So we've found companies that have done quite significant improvements at fairly low cost, where you look at things that are automated and some of the decision criteria, reducing risk, reducing fraud, improving the response to customers, etc. The important thing with ROI is to have a baseline of how you're currently operating before you start the project. Because you are going look at the improvements later and say, how do you know you've achieved 1000% ROI if you don't know how it compares to your previous state? So ROI is a lot of times actually misused and misunderstood, compared to actually building an effective cost benefits framework and then looking at what you've improved over a period of time. Then you can measure the result, which is the ROI, or sometimes what we call the total potential of ownership, that can actually reach the goals that your executives have outlined without using any kind of capital to bring people or technology into the business.

Click here to view the webcast:
"How to automate smart decision making with BI and analytics."

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