I recently read a discussion from the CIOs.com: Chief Information Officer Network group on LinkedIn called What’s missing from Business Intelligence? (Please note you will need to have a LinkedIn account and be a member of this group to view the discussion for yourself)

The conversation was kicked off with a claim that 54% of organizations do not realize the desired benefits from the Business Intelligence (BI) solutions they have implemented. The community was polled for their plans to overcome the common business and technical challenges of BI implementation and their thoughts on what’s missing from BI.

Having been a part of several large IT initiatives that have both succeeded and failed, I had my own ideas about the cause of BI failures. I have found it is easy for people to get so caught up in the features and functionality of the system being implemented, that they lose sight of the purpose for which the system is being implemented in the first place.

What Are You Trying to Accomplish?

A perfect example of this can be seen in this blog post where the author was approached by several different people at a conference asking for his advice on choosing a vendor for a Master Data Management (MDM) solution. In his words (paraphrased a bit), each request went something like this:

Which MDM vendor should I choose?

What are you trying to accomplish?

<Some conversation about features and functionality>

So, what are your priorities?

We know we need MDM, but our company hasn’t really decided what MDM is. Since we’re already a [Microsoft/IBM/SAP/Oracle/SAS] shop, we just thought we’d buy their product…so what do you think of their product?

This scenario perfectly illustrates what I have seen in IT failures. There seems to be a sincere belief that success can be achieved with the right vendor or set of technological features without first figuring out what you’re doing or why you’re doing it or what it really means to the company’s mission, purpose, and strategy.

Now, back to our LinkedIn discussion.

I felt the topic of “What’s Missing From Business Intelligence” was a perfect opportunity for a technology-centric conversation. I was sure there would be lots of comments about the must-have features and cutting-edge technology. I wondered how many comments there would be before anyone spoke to the business purpose and strategy side.

Intelligence First

To my surprise (and much to my pleasure I might add) it wasn’t long before I saw comments that spoke about the need to understand what you’re trying to accomplish from a business perspective before you can hope to be successful with BI technology. One comment by Carol Rizzo came early in the discussion and really set the tone for future comments. Here is what she had to say:

In my opinion, there are no tools that can provide insight if you do not know which questions to ask, and cannot identify which information/data is relevant to getting you the answers, or what you might do differently if you had the information. This may today be called BI, but the same issues exist in CRM and previously in EIS (Executive Information Systems).

Call me old fashioned, but I have built realtime information systems for traders. They don’t know the answer but they generally have a good idea of what data is in the mix and what patterns or ranges or contrarian behavior they need to see in order to make good decisions and change their strategy or know when their strategy is beginning to fail.

Sometimes, I think we fail to look at the obvious. If you don’t know the question and which data is key, how can you possibly get the benefit of any business information system. As anyone who has built an expert system will tell you, you model how people make decisions… what information they use and what are the triggers for either gathering additional information or making a decision. YOU NEED THE INTELLIGENCE FIRST!

Respectfully…

“Intelligence first”…I like that!

It’s BI…not AI

Another excellent comment came from Patrick Walker , who explained how some business users may have unrealistic expectations of what BI is and what it can do. Here is what he had to say:

I have worked fairly intensely with corporations on creating “Business Intelligence” systems from the old DSS environments through ERP and CRM into Knowledge Management and differing hybrids.

From this understanding, the problem that I most often face is that the Business seems to have a differing perspective to BI than the technology industry. The business user’s perspective is closer to the perception of “Artificial Intelligence” being BI than just the ability of a system to crunch numbers, scenarios and what-if statements.

Quote from Dr. Mark Humphrys, University of Edinburgh

What is AI? In some sense it is engineering inspired by biology. We look at animals, we look at humans and we want to be able to build machines that do what they do. We want machines to be able to learn in the way that they learn, to speak, to reason and eventually to have consciousness.

Therefore the business user is looking for BI to be informative about what does the business need to know, rather than the business asking the question.

BI for the business seems to mean “Tell me something”, I shouldn’t have to ask, where my profit losers are, and the systems should tell me when it happens and why.

The business seems to want a system where it, the business, doesn’t have to programme the information or knowledge, just the raw data and the knowledge and information and how to use them are magically produced by the system. We dot think, the machine does it for us.

Therefore, until we can explain to the business that BI is a co-operative, symbiotic relationship where business needs to provide as much intelligence and the system will produce improved intelligence,there will never be a happy understanding of BI and it will always fall short from a business perspective.

Summary

So, how do you succeed at Business Intelligence? Start with the business (purpose, mission, strategy, etch.), add intelligence and stir. Seriously though, if you are considering implementing BI, consider the following before discussing tools and technology:

• Define your questions – What are the strategic decisions in your business that you need to be smarter about? What questions, if answered, would make those decisions better?
• Define your action – What would you do differently if you had the answer to your question? You can’t expect to gain business value from a BI initiative if you don’t plan to take action based on the knowledge you gain.
• Identify the data needed to answer questions – Resist the temptation to begin a BI initiative data-first. Start with the questions and then identify the data that will be helpful in finding the answers because…
• “Business Intelligence” is not “Artificial Intelligence” – Don’t expect to simply throw raw data at BI tools and have them “tell me something”. Manage business user expectations accordingly.

Now it’s your turn. What has been your experience in implementing Business Intelligence? What helped your success? What was the cause of failure? What would you do differently if you had to do it over? Please share your experience and reactions in the comments area.

In a recent blog post, Andrew McAfee suggests a model for developing superior business processes may have been discovered in the world of chess.

In 1997, IBM created a computer that was able to beat the world champion Garry Kasparov for the first time and it only cost them $10 million to do it! Today, because of computing advances, commercially available chess programs running on standard hardware can consistently beat even the best human players. The cold, calculating precision of the machine is just too much for the human player.

Our deep-rooted mistrust of the coldness of machines prohibits us from turning over our most trusted decision-making to them. In the 2004 movie I, Robot, Will Smith’s character, Detective Del Spooner expresses this sentiment while describing an incident where he was rescued from a sinking automobile by a robot. The robot decided to save the detective instead of a young girl in the same situation based on a calculation of chance of survival. Regarding the girl’s low chance of survival compared to his own, Spooner says:

11% is more than enough. A human being would have known that.

Is there any reconciliation between man and machine? Surprisingly, McAfee points to recent research that a partnership between man and machine is not only possible, but may be the most powerful combination available. In chess competitions allowing any combination of humans and machines, it was found that a human plus a weak laptop were able to consistently beat even the strongest computers.

McAfee’s post is fascinating and worth a read. I encourage you to check it out.

Did Garry Kasparov Stumble Into a New Business Process Model?

So what do you think? Is it possible for humans to embrace a partnership with computers?