Copyright © 2009 James Taylor. Visit the original article at Make Better Decisions.
Tom Davenport published a new article recently in the Harvard Business Review titled Make Better Decisions. In it he gives some examples of bad decisions and asks why this decision-making disorder?
First, because decisions have generally been viewed as the prerogative of individuals—usually senior executives. The process employed, the information used, the logic relied on, have been left up to them, in something of a black box. Information goes in, decisions come out—and who knows what happens in between?
This is, of course, a critical issue and one of the reasons I push organizations to adopt decisioning technology. The ability to log exactly how a decision was made, the steps that were taken, the analytic models considered is something that comes with the use of technology like business rules management systems. Beginning to create a history of how and why decisions were made puts you in a dramatically improved position when it comes to conducting systematic analysis. Tom’s focus in the article is on ways in which organizations can make manual decision making more explicit, but the …
Copyright © 2009 James Taylor. Visit the original article at Make Better Decisions.
Tom Davenport published a new article recently in the Harvard Business Review titled Make Better Decisions. In it he gives some examples of bad decisions and asks why this decision-making disorder?
First, because decisions have generally been viewed as the prerogative of individuals—usually senior executives. The process employed, the information used, the logic relied on, have been left up to them, in something of a black box. Information goes in, decisions come out—and who knows what happens in between?
This is, of course, a critical issue and one of the reasons I push organizations to adopt decisioning technology. The ability to log exactly how a decision was made, the steps that were taken, the analytic models considered is something that comes with the use of technology like business rules management systems. Beginning to create a history of how and why decisions were made puts you in a dramatically improved position when it comes to conducting systematic analysis. Tom’s focus in the article is on ways in which organizations can make manual decision making more explicit, but the potential for decisioning systems to play a role should not be forgotten.
Second, unlike other business processes, decision making has rarely been the focus of systematic analysis inside the firm. Very few organizations have “reengineered” their decisions. Yet there are just as many opportunities to improve decision making as to improve any other process.
Absolutely. Like Tom, I believe organizations should conduct some kind of decision discovery – indeed this is the first step in my Decision Management methodology. Decision Discovery helps organizations to identify decisions and see how they impact strategy, balanced scorecards, KPIs or other operational measures. Identifying the decisions that will make the most difference and then classifying, understanding and prioritizing them puts organizations in a better position when it comes to improving manual decision making as well as adopting decisioning technology. And just like other re-engineering opportunities the power of technology to maximize the value of re-engineering is real with organizations that adopt decisioning technologies as well as a thoughtful approach to decision making seeing tremendous results.
It’s a great article and there’s lots I agree with. For instance several times in the article Tom talks about institutionalizing better decisions. One way to do this is to embed these decisions in decisioning technology so that it the right decision is available to everyone – right down to front line staff – and yet still determined by those with the relevant expertise and experience. He also talks about formalizing the consideration of decision alternatives and the use of adaptive control techniques – part of a phase I call Decision Analysis – is critical in both designing and then executing and learning from experiments. His warnings to ensure that the assumptions behind models are understood and his push for managers to have enough analytic/mathematical understanding to use such models are equally valid. Finally, I really like his closing comment to the effect that if you are not measuring the impact of your decisions, of your choices, you are most unlikely to get any better at it. And you need to.
Tom is a little too negative on automated decisioning for my taste. He describes automated decisioning systems as hard to develop and implies they can be hard to change. My experience is that it is getting easier and easier to develop automated decisioning – easier than Tom thinks – and that the use of flexible business-centric technologies like a Business Rules Management System makes it easy to change and evolve the decision criteria even when these are embedded in automated decisioning systems. I also happen to think the book Neil and I wrote, Smart (Enough) Systems, has some good stuff about decisioning in it – though I like all the books he lists too (Competing on Analytics, Blink and Super Crunchers are all ones I have reviewed).
I recommend the article both as a general one on decisioning and for those of you thinking about how to improve decision making in your executive and management teams.
