- break problem into manageable pieces
- propose solutions to the sub-problems
- evaluate solutions by theory, experiments and prototypes
- select from the set of solutions based on feasibility, cost and other stakeholder interests
- implement the solution, testing for adherence to the design, and the ultimate goal. As tests fail, cycle through the design - implement - test "cycle" until results are acceptible
- as you implement and learn, feed back the knowledge into the original plans, to get improvements into the overall design as soon as possible.
This, or a similar formula, is widely accepted. There is a less widely accepted formula for making decisions. Perhaps decisions are less weighty? Less important ? Less consistent in their nature?
Well, the design process is controlled by decision making ... so decision making must be more fundamental. Design does attempt to pull a solution from an infinity of options, and good design has hallmarks of simplicity, durability, longevity or something more asthetic. But decisions have inifinities all their own, as they too are based in predictions of the future, but often in a domain that is less clear that that of a potential design.
A good desision is not generally known to be a good decision until some time passes, or events unfold that indicate that there is a benefit, or a loss. Often the world changes and events overtake the framework in which a decision is made, and even though the decision might have been correct given the available information, it may passively cease to be correct.
The share markets provide enough examples of this.
So, a good decision must be managed within the framework in which it is made, and it should include ways of checking the validity of the framework. Even better, it should provide a way of telling the duration for which the framework will stay valid.
Unfortunately, this type of decision seems to only exist in the imagination of authors with an eye to intrigue, suspense and climax.
In the real world, people do not have the patience to formulate their decisions correctly ?
I say patience, some might say that people naturally manage their time, providing sufficient time only, as the decisions need to be made. I accept this economisation as true, but I question the accounting. Some decisions are many orders of magniture more important than others, but there is not an appropriately scalled investment in time, advise or research. People will spend as much time researching their next car as researching their next house? Sometimes it's even more apparent.
In business, there would seem to be a pro-rata increase in research before an expenditure. Before embarking on a million euro development over a year, a portion of that money and time would be invested in planning or selecting the best way to achieve the goals. I would guess that the research portion of the funds would indeed be spent, but I wonder what the ratio is comparing the the daily value returned during that "investigative" phase, to the value being generated when the project is under way.
Here are a list of decision support tools that are well known:
- Brainstorming (rarely used, poorly understood! perceived as simply getting heads into a room = discussion / arguement. Brainstorming is about geting as many ideas out in a fixed amount of time without evaluation or criticism )
- Pareto's Law (widely and well used, intuitive and fast)
- Priority (widely used, bur the quantification suffers from opinions which are not qualified)
- Paired Choice Analysis (takes patience to go through the pairs in any meaningful set of options, I've not seen it used widely)
- Decision Trees (rarely used, complex to handle all the possibilities and their probabilies)
- Sensitivity Analysis (never seen this used, people at middle management have little energy for the maths needed to build the models)
- Weighted attribute comparisons (rarely seen used, the result can used, but also less than confidence inspiring)
- Various perspectives / stakeholder review (delegate the decision upwards, widely and smartly used. However, dodges the real issue)
- Forcefield analysis - how strong are the set of forces that act on the decision (never seen used, but seems highly valuable)
- Balanced score card ... perspective grouped goals and measures (used for decision makeing - or status monitoring?)
- Cost / Benefit ( widely considered, but very difficult as both costs and benefits are often estimated with prejudice)
- Risk Analysis (not widely used formally, but intuitively integrated to general decision making
...
