Then another question we always think is really important to ask before selecting a BI solution is, why can’t they answer this question today with the analytic tools already in place. Agile BI is not trying to replace traditional reporting systems. It’s trying to complement them. One of those quotes earlier says it’s a new paradigm to enable people to do things in ways they weren’t able to before.
So a key question is not just what they’re trying to do but why haven’t they’ve been able to do it and the derivative would be, what would enable them to do that effectively? And then another key question is, how is change going to happen once the questions are answered because, okay, now we get these answers to questions, somehow this is going to impact strategy.
It’s going to impact organizational design layout on roles, and the management needs to be open once the story starts coming from the data to make effective changes. We have a client for example where we did a lot of work on their marketing campaigns. And we found out that a lot of their mail, phone and even some of their e-mails were largely ineffective, literally 70% of it. Thirty percent was highly effective.
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So you can clearly see that some messaging and some media were working, and we could identify segments and improve yield but a lot of that should have been stopped, but you then get organizational resistance because there’s teams of people whose job it is to create the mailings and do the phone in the traditional way, and they don’t like to change.
So another piece of this if you take this full cycle is management may need help. They certainly need to be empowered and then make the change that Agile BI data has enabled the staff to see. And again, I think there are three pillars of this. The team needs quick and flexible access to data. You saw earlier how it should be days, not weeks, to develop a good analysis.
The intuitive display and easy interaction, there is a lot of new technology found in the market which makes it easy to see the data and interact with it. These visual analysis tools are very flexible, and there are not modeling techniques required. The tools are flexible, and end users don’t need a statistics degree or SAS expertise.
SAS I’m not picking on. It’s a great company and has great software, but it’s not something the typical end user can use. And access from anywhere, anytime is really important. So if you wrap this up there is a lot of buzz out there. There’s also a lot of confusion. I think the summary is that the words that keep coming out of this is faster and more flexible.
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Whether it is on the development side where there are techniques from extreme programming, proven techniques that can be use to do that. I think iteration is really important. We see that a lot that. You can’t really know the end result until you get reaction from the end users. And they have trouble reacting to it until they see something.
So that first point was be faster and more flexible. Iteration is a key word. Then for the end user the keys are easy access to data, intuitive, and being accessible anywhere. On the technology side it is about these kinds of things, and there is a lot of writing on it, scrum extreme programming, iterative, and mobile.
If your organization is not doing these things, there are a bunch of seminars. There are classes. There is a bunch of writing that can bring this up. I know my team here on the software side, we weren’t doing scrum and extreme programming a couple of years ago. We had traditional development cycles. They would take seven to nine months with the testing on the end.
We’ve now moved to a scrum and extreme programming approach which has been far more effective. We get quick cycles, quick turnaround, a lot more ability to iterate because we’re getting feedback as we go along. It’s just been much better. That being said on this side there are projects or capabilities that don’t fit the scrum extreme programming mode.
It might take a year, a year and a half, whole new developments to pan out, but you can still have aspects of them work that way. And obviously the new mobile technologies need to be factored in. On the end user side this concept, or the information per say, is somewhat a philosophy, but it’s also a technique. It’s the philosophy of saying enabling my end users to have access and be able to muck around in the data so that they can make decisions on their own without our help is important.
The counterpoint is they’ll make more mistakes, and we hear that a lot. There is a concern that by empowering people with more information, it will lead to more mistakes. I would say, I’d rather have the end users making 10 decisions and getting eight of them right then being constrained and only making two decisions with data and making eight intuitively.
In an empowered model you make a lot more decisions with data and in the un-empowered model those decisions are still getting made. They’re often just making them on common sense and intuitions and not really seeing the underlying facts. Getting the issues in questions nailed down is key for good insights.
Combining the technical side with end users is really important, and we made that point that it’s a different paradigm than has typically happened. In BI it really is much more important to have that. There are a series of new enabling technologies: in memory management has really been empowering, and interactive visualization. Social networking has created all kinds of new data, and then you have the search capabilities. Once again the key is enabling end users to be much faster, more flexible and more agile in their use of BI information.