A lot of observers, myself included, were quick to blame the U.S. government's IT infrastructure a few days back, when information emerged that data on the recent "underwear bomber" had been readily available to government sources who failed to connect the dots.
When it comes to business intelligence, it's not easy to define where IT's role begins -- or ends.
A primary issue is that no matter what technology is applied by IT, there will always be a need for talented decision-makers. "Good data, bad decisions remain BI's biggest problem," wrote Cindi Howson, founder of BI evaluation site BIScorecard, in a blog this week.
Which brings up another problem: To what extent should the smart human factor be provided by IT, and to what extend is it a line of business (LOB) responsibility?
There's no single guideline here. "I'm a consultant, so you'll get the standard consultant's response: It depends," quips BI analyst Seth Grimes in an email today. "IT should get business analysts the tools they need and get out of the way, and if business analysts need specialized tools -- say, a hosted social-media analysis service or software... for statistical programming and modeling -- they should be free to arrange for what they need. (Of course, IT will always be responsible for hardware and network support, security, backups, and all that essential stuff that end users typically
overlook.)"
But if Grimes advocates LOB specialists for many analytics projects, he says there are analytics that only IT can do best: "When we're talking enterprise-wide analytics, mainstream tasks, and production deployments, that's when IT's experience and capabilities are invaluable and their assistance is indispensible."
Another expert says that, realistically, IT will always be involved in analytics of any kind. "I think much of analytics is a challenge because it fills the 'white space' between accounting and IT, or between marketing and IT or between any line department and IT," writes David Silversmith, vice president for information technology at FirstBook.org and former CTO at Carfax. "Business analysts need to be expert in the subject matter area (sales numbers, Website visitors, financial data); understand the basic concepts of relational databases and be comfortable using analytical software/reporting tools. The problem is finding these folks.
"I think the best folks start with subject matter expertise and tack on the IT skills, I don’t think that IT has to be the interpreter -- I think it is best when the interpreter is in the line department, but all too often it is in IT where the person starts with the IT skills and you try and tack on the subject matter knowledge."
Clearly, all analytics roads lead back in some fashion to IT. But whether IT will be looked to for the smarts or whether it will work with the smart folks in departments or LOBs depends on the structure of each organization. Still, it's best to define the perimeters of responsibility up front, if fingerpointing and problems like the ones that surfaced in the government last month are to be avoided.
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Great article, Mary. And I agree with SeanfromIT. The real problem is the flow of information that is stopped by individuals, department silos, egos, budgets, etc.
Which is your point, Mary. Adding more technology will not stop the problem but only clutter it further. What truly is needed is a better corporate architecture of what data is needed, how it is to be used, and who has accountability.
That is just sound business and good organization. Until we put that in place, with good workflow analysis, we will provide a screen that will permit individuals to sidestep responsibility and perpetuate the territorial battles.
BI is just the latest buzzword cooked up by Oracle. I've yet to work for a company that has any idea what they're doing with it. The larger the company, the less connected each department gets and pretty soon one arm has no idea what the other is doing. In the end it still requires talented people to put the dots together - no matter what BI software they're using. And when you're talking about global intelligence, it isn't going to happen. DHS can hire 1000 new cyber "experts" but without meaningful data pouring in from the CIA, NSA, etc, they still won't be able to do it. It's just like in companies where various departments fight for funding - they keep their cards close. It's going to take a really big shakeup and reorganization for real security to happen.
Great stuff, rjacksix. It's interesting that the users -- by which I think you mean the LOB users -- actually chose too many variables or dimensions for their data.
As to the analysis, it is a joint effort. With us basically training the user in the idea of dimensions, attributes, and measurements. Our tool is robust enough that it can support 70 dimensions, but the user are now realizing that they may have over used them ;)
First, we are a State agency so ROI, DCRR, or any kind of payback methodology is hard. The reality is that the data is being used to revamp and analyze data that will ultimately result in efficiencies, but not efficiencies that we will be rewarded by directly (the carriers, hospitals and others will though).
While I understand the other remark about understanding the requirements well enough to build the system (which is the argument for accurate requirements analysis), the system that we have built is designed to transcend a classic reporting system application development and to be an open frame work that allows the LOB users to explore and do analysis w/o us.
It really is a win/win situation (sorry for the cliche). We free the resources that are typically used to do static reporting, and the LOB users get to traverse their data and do what if analysis at the speed of thought, instead of having to take a timeout to ask IT to create a new view, report, dashboard, etc.
We are using data fusion techniques and data cube analysis tools to accomplish this w/ typically subsecond response times. It's the future. And while I will concede that we don't have a huge store (1.5 million records), the cost of computing and the technology is getting better every day.
I think this is a larger problem than 'misunderstanding BI".
There was an IBM commercial 'back in the day' that was meant to disparage the manner in which other computer companies were selling their services to clients... the scene was around a conference room table, where 3-4 members of a client firm were posing a list of issues they were trying to resolve and seeking assistance form an IT firm to do that.
The IT 'sales guy' had a tech guy from his firm sitting next to him, and the client was listing off a number of sizeable issues they were seeking solutions for and whatever they asked for, the sales guy said "we can do that!" (and the tech guy cast him a glance) after 5 or 6 of these responses (and more ferverent glances), hands were shaken, the client said we'll sign the contract and send it back, and the IT guys walked out of the room. As they got to the car, the Tech guy looked at the sales guy and said "HOW are we gonna do THAT?"
IT knows that tools exist that can accomplish much of anything with regard to manipulating data and producing reports anyone wants, providing the data exists and it is described/defined well enough to allow them to work with it.
Where the problems typically occur, is they fail to get a clear scope of what needs to be done, whath the 'organizational landscape/environment' is, what th eculture regarding the access to the data is, how the data is curently structured, what the architecture of the aspects of the organization they will be obtainign and providing data to are, and what the timing is to do this.
Much of the data is either uinstructured or not adequately described (by metadata or other forms of indexing) to allow for searches to return the level of information analytics seek to provide. The result is many end users feel the efforts fall short and "ITdidn't do their job" or "ITdidn't provide what they said they could"... but as mentioned and it's not intended as a an excuse for IT, they weren't aware (in most cases) that the data wasn't 'rich enough' to provide what was required when they said they could do something.
In this case, it's a shared responsibility... the data owners need to knwo what the existing data sources contain and consist of, and IT needs to knwo th elimitations of thre tools they're supplying and if the data contains the 'features' they need for the tools to provide the results.
Great input, rjacksix. I'm curious about the project: Did you have sufficient payback on your investment? Did the issue ever come up as whether the analysis should fall to IT or to the department/LOB?
Data sitting in a repository is of no value to an organization. The "traditional" IT person thinks there job is done when the data quality, integrity and reporting are done.
We have invested less than $250,000 all in over the course of 3 years to free the data and allow business to do what they will with it.
This sounds great, rjacksix. But I'm not sure many organizations have the means or personnel to achieve it. In many instances, IT will be limited in its resources.
One thing: Your analysis indicates that IT will be responsible for supplying the analytical "smarts" needed to furnish the kind of information the business requires. That too puts added burden and expense on IT.
so then it all comes down to the human touch? this reminds me of a cartoon that was published in a daily where they mocked the idea of smart bombs, the pilot in the cartoon was shown to have dropped a smart bomb over a tribal household in Afghanistan and he's wondering to himself if there are indeed terrorist inside the mud hut. and then he consoles himself by saying "naaaaaaah smart bomb would know"
I think more than BI its all about inference guided by common sense
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