There are two main problems with BI software.
First, too little thought is put into the post go-live analysis portion of implementing a BI package. All the effort is spent setting up software, gathering reams of data, and cooking up a few canned reports, and at the end of the day, when you’re sitting atop a mountain of data everyone looks around and says “now what?” More thought should be put into what the key drivers of that particular business are (there should be a handful, not a pile), and providing “real people” (i.e. not from IT) the tools and training to mine this pile of data as they see fit.
The second problem is with business reporting as a whole, and the reason why many BI implementations are billed as unsuccessful. By its very nature, BI looks at the past, and it is easy to look at your stack of fancy reports and believe it contains the tools you need to predict the future direction of the business. This is abjectly false, and the best example is the financial industry. Finance always has the highest IT spend in the industry, and a very high penetration of BI tools, yet nearly all the big financial organizations missed the recent financial crisis. You need strong management that realized BI provides clues to the future, but not the future itself. IT often is a partner in crime, overselling this aspect of BI.
Like all software, BI is a tool to be leveraged, it is not a magic potion that will predict the future, despite all the fancy dashboards, reams of data and fancy analytical terms.
any supporting (for your claims) article you can suggest?
Hi Hikmatune,
Not sure what you mean by supporting articles. My “claims” are based on my experience working with companies (primarily large ones) that become disenchanted with their BI implementations after the “magic” wears off and they’re left with yet another cumbersome reporting tool. As I allude to in the above post, BI generally is oversold as being more of a crystal ball than a analytical tool.
The main problem with all reporting tools (IT or otherwise) is that they look at past trends and become too much of a crutch when management should be looking at future events. A fine “case study” is the recent financial crisis. The financial industry has the highest IT spend of any industry, and is heavily invested in BI tools, yet most large institutions missed the signs of the crisis. BI is obviously not the root cause of the crisis by any stretch of the imagination, but this serves as a nice example of the problems with over reliance and overselling BI tools.
Hello Patrick,
Thanks for the elaborated comment. I am doing my dissertation on BI tools and I am looking for resources. I couldn’t find much on the problems with BI tools except for your topic. My topic is “Multi-criteria decision making models for selecting Business Intelligence applications” however, I can change it any time because I have just started it.
Please enlighten me with your knowledge on what direction should I take and what should I base my research on.
I am little bit devastated after reviewing others work on the same topic like the recent one “Wisdom of Crowds Business Intelligence Market Study” by Howard Dresner.
I would appreciate any comment or advise you could provide.
Hello,
I know it doesn’t necessairly fit the academic mindset, but why not blaze a trail and formulate some new work on the problems with BI tools? Ideally if you could get some contact with CIOs who have come away unhappy with the tools in my mind this would be a far more compelling source than a second-hand book.
Hooray!
So true, your central premise.
Business users typically do NOT want more data by the ton.
They want/need informed analysis to tell them what’s the logical next step (of many) they should pursue. Despite IT’s agenda to create their own job security with BI tools, elimination of seasoned business analysts who can distill significance & spot critical exceptions or trends across multiple data platforms will still be a fact of life for quite some time.
Data integration is very hard work & as the world spews forth even more non structured data, BI tools are struggling even harder attempting to keep up.
The real question to be asked, is why even bother?
Great post! 1) More thought should be put into what the key drivers of that particular business are (there should be a handful, not a pile), and providing “real people” (i.e. not from IT) the tools and training to mine this pile of data as they see fit.
I cannot agree more. However, defining the key drivers in your business actually requires people who really understand their own business processes and what does / does not influence performance in an integrated way. Ultimately BI should help business people to make better informed decisions. That requires cross functional reporting and analysis. For example if your DSO (days sales outstanding) increases, I would be most interested in why the DSO has increased. That requires a different way of reporting, which implies I may also want to see sales developments, bad debt ratios, collection ratio’s, changes in payment terms, cash flow forecasts, etc. I hardly see that kind of analysis done in organizations.
The second point: BI looks at the past, and it is easy to look at your stack of fancy reports and believe it contains the tools you need to predict the future direction of the business. True, so that’s why you see some vendors move towards predictive analytics. But predictive analytics doesn’t mean a thing if you have no clear understanding what drives your business.
What we need is a clear set of logical business models, that explain the functional relationships between processes and data, so we can create more useful reporting and analysis. I think that would help businesses most.
Marcel,
You’re exactly right. In essence, like too many things IT-related, we get overly focused on the tool, and no the job the tool is meant to accomplish.