Executives are still dissatisfied
According to the latest surveys, executive dissatisfaction with the information available to them to make decisions is just as bad as when I started working in BI 20 years ago.
How can this be? Have the billions invested in BI and information systems proved to be worthless? Will computers ever help with decisions? I believe the bottom line is no, they won’t — but with a big caveat.
Model: Yolande Elliott
What is a decision?
Of course, technology constantly advances, providing more data and more support for people faced with ever-more-complex choices. But the definition of “decision” automatically moves beyond what computers can do.
Let’s take the simplest form of decision we can imagine, a yes/no choice, and assume that computers have provided all the information currently available to make that decision. There are two possibilities:
- The answer is obvious, and choosing yes or no is a mere formality
- There’s some need for reflection before choosing an answer
Choice 2 necessarily means that there are some extra factors that must be weighed that the computers cannot or have not provided.
Out of sight, out of mind
Over time, as technology becomes more sophisticated, more and more choices are automated and put into the first category, and are no longer thought of as “decisions”.
- People used to “decide” airline pricing; now computers do, and it’s just become part of the revenue optimizing application.
- Amazon’s systems choose what books to recommend to me, but do they really “decide” ?
- UPS drivers used to decide what route to take, now the system just tells them where to go, without any left-hand turns
- Or to take it to an extreme: automatic chokes replaced a “decision” that drivers used to have to make about the fuel/air mixture — are they part of a “decision system”?
In other words, the bar is constantly being raised, and anything that is automated just disappears into the mass of everything else that has already been automated.
Decision=not enough information
A decision is a situation where information is lacking by definition. Many executives define their jobs as “making decisions” — i.e. tasks that can’t be automated. As computers take on the lower-level tasks, they’re free to move on to more complicated choices.
Is this just a pointless debate about semantics? No: there are real world impacts on IT organizations and the BI industry. It means that business people will always want more information than is available, and will therefore be disappointed by the systems and people that provide it to them.
- IT organizations must realize that people have short memories, and plan their communications accordingly. The pain of the decisions that they’re currently wrestling with have greater weight that the choices that you’ve helped them automate. As you implement new systems, write down quotes of how business people express their current pains and send them in an email. After the systems have been used for some time, show them that email again to remind them just how far they’ve come.
- Business people may never be happy with their information systems, but you can make sure that they at least feel better off than their counterparts. Seek out benchmarking information that compares what you provide compared to other organizations. If it’s worse, you’ll have a good claim for more investment. If it’s better, you can take the credit.
- Marketing claims that BI can “help decision-making” are likely to be viewed with some skepticism, because every information system since 1958 has made the same claims, and the perception is that people are no better off today.
To decide is human
So, in conclusion: of course computers can help make ever-more sophisticated choices, and there can be real competitive advantages to automating decisions that are currently carried out by people (see Smart Enough Systems by John Taylor and Neil Radon for a good overview of approaches to Enterprise Decision Management).
But to decide (and err) is human. Recognizing this and setting expectations appropriately can help smooth the relationship between the people that consume information and the groups that provide it.