Collaborative BI key to bringing order to chaotic business environments

Collaborative BI may not carry the same kind of prestige that “big data” or the cloud does, but devotees like Barry Devlin believe it to be a critical game changer.

Collaborative business intelligence (BI) may not foster the kind of hype linked to the terms cloud or “big data,” but tools that enable easier, more efficient ways to discuss data are garnering interest, especially among devotees who believe they could be a game changer for BI and beyond.

Barry Devlin, the founder of 9sight Consulting, is one such supporter. Whereas traditional BI tools encourage what Devlin calls “a personal exercise” that weighs the conclusion above all else, collaborative BI places importance on peer-to-peer problem solving, giving consideration to the end product as well as the process.

Instead of holing up in a cubicle with a BI tool and analyzing data until a conclusion is reached, he said, collaborative BI is more akin to something like Facebook, which emphasizes swapping information and ideas that are significant right now.

Today, Devlin said, vendors recognize the growing interest of a collaborative work environment, but most offer options with too narrow a focus, such as add-ons to the BI tools.

It’s a beginning that will continue to gather momentum, eventually breaking out of BI and stretching across the entire enterprise, he said. SearchBusinessAnalytics.com recently spoke with Devlin about how this kind of a work environment will drive innovation, especially in an increasingly chaotic environment. Here's an edited version of the interview.

What’s the drawback to bolting on collaborative features to your BI tools?

Barry Devlin: Any organization beginning to take on any social networking or collaborative-type work, wants it to be bigger than their BI environment. Having a standalone collaboration environment built around your BI tool, which is separate from any strategic or enterprise-level work you’re doing around social networking or Enterprise 2.0 in your organization, is a bit of a problem.

That’s one of the issues that’s going to come up, because I believe social networking, Enterprise 2.0 -- whatever you’d like to call it -- that way of doing business is going to become the norm. And I think it’s going to become the norm because whatever you want to call them -- Generation Y, the Millennials, or these young people coming into the business in their 20s and 30s -- they’re getting to the stage where they’re in positions of power and they’re used to doing things in a social networking environment outside of their work. I think it’s natural to want to do it inside of the work environment as well.

How are vendors selling collaborative BI these days?

Devlin: The current way most vendors are doing it sort of makes this a silo of collaborative BI, and yet I think collaboration and interaction is key to real innovative decision making. Most research around it suggests that one of the most effective ways to get innovation within an organization is through an effective team-based building of whatever solution you want to do. So rather than sending someone off with their BI tool, getting people into a team and allowing them to work together on a problem is seen, relatively widely, as the way to go forward in terms of innovation. That’s where we’re going to look at a very substantial change in the market from -- let’s call it decision support to decision-making support.

What do you mean by decision-making support?

Devlin: When you think about decision making in a team, you have, if you like, a set of base information that people bring in with them: their knowledge, their documents, the research they’ve done. You get a set of documents or a set of information along with the people, and that’s going to be the context of this decision. Now you have to manage that information, not just the standard old-fashioned data that came from your internal system, but a wide set of information from all sources. And you’ve got to make that interaction make sense. In other words: How do I know who has spoken to whom on the team about this particular idea? How can I track the progress of meetings, the progress of conference calls, the progress of ideas? How do I make that available in a more interesting and more open way? And there I think you get to see the full potential of collaborative BI. It’s much more than sharing the results from a particular BI tool; it’s about sharing the set of information that is being gathered within a team.

Why does collaboration seem so much more philosophical than other aspects of BI?

Devlin: It’s not that it’s philosophical; it is more on the edge of what’s emerging. I was there at the very beginning of data warehousing in the mid-’80s, and the focus was simple: We have all of this data scattered around the organization, it doesn’t match well and it doesn’t have good history. How can we bring it together in order to get a good, accurate, historical view of what goes on in our business? That’s a practical and pragmatic thing that most large companies have struggled with for years. And it has continued to be at the heart of traditional BI.

But in the last couple of years, the whole business environment has changed dramatically. When I think about the people who want to make decisions instantly, it becomes much more about joining all of the different pieces together. I’ve started using the phrase the bus-tech ecosystem as a sort of flavor of that. It’s almost impossible to do business today without having significant amounts of technology underneath and built into it. Indeed, technology influences what you can do in the business environment and vice versa. If you want to really be on the leading edge of an industry, I don’t think you can simply talk about doing raw analytics or basic level analytics. You’ve got to figure out how to get this embedded into your organization, how to get the cultural change to happen, how to behave differently in the outside world.

How does collaboration help businesses achieve that kind of maturity?

Devlin: Organizations make decisions in a very unstructured, almost irrational way. What happens, I believe, is that we post-rationalize those decisions in order to come up with something that makes sense. BI is one of the things we use to do it. It’s all very useful and lovely to have a BI tool that, at the end of the day, says, “Oh yes, this particular peak in sales meant we took the decision to move into that market.” But an awful lot happens behind that, which is related to some of the data but is not entirely based on it. That’s where collaborative BI begins to expose some of this stuff.

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