- General
These techniques are applicable to any type of problem, and therefore can be used in advance of, in conjunction with, or independent of heuristic and technological techniques.
- Public Solution.
Publicly posting a request for help on a problem to coworkers, associates, friends, teachers, etc. can get several minds with fresh perspectives working on it independently, in discussion with others, and/or in conjunction with you.
- “Phillips 66".
This is a form of the Public Solution technique which is useful for simultaneously engaging the minds of a large group in a problem. In its original form, the large group was divided into smaller groups of six people each, and each of those subgroups discussed the problem for six minutes, followed by formulating a single question or proposed solution by agreement.
There were several inadequacies in this approach, but the main one was the unreasonably short time allowed for discussion. (In six minutes not much can happen because just settling the group down and focusing take some time, and discussing and agreeing typically require much more.) So the revised procedure is now as follows:
- Each subgroup should consist of 3 to 8 people, with an ideal size of about 5.
- The assigned task must be made clear and explicit, requesting a decision or conclusion. (Otherwise the output will likely be just feelings, opinions, or questions.)
- Each subgroup should be allowed at least 20 to 30 minutes to work on the problem.
- The Method of Contradiction.
Pretend to assume the opposite of what you want to prove and then look for facts that contradict that assumption. By disproving all of the alternative explanations you automatically highlight (and “justify”) the sought after solution, but (unfortunately) you don’t necessarily prove it. (That would only be possible in the relatively rare case in which the two competing explanations were true diametrical opposites.)
- The Method of Outrageous Provocation.
Begin with a statement that is known to be absolutely incorrect, and then use it as a bridge to a new solution approach. (This is a variant of the Method of Contradiction.)
- The Random Word Technique.
Select a random word from the dictionary and juxtapose it with the problem statement, then brainstorm about possible relationships.
- Incubation.
If you’re not making progress toward a solution at an acceptable rate, put the problem aside for a while (overnight, a day or two, several weeks or months, or...) and allow your subconscious mind to work on it. This doesn’t always succeed, but it is sometimes the only path to the solution.
- Case Analysis.
Research similar cases to see what insights their solutions can offer.
- Heuristic Search Methods
A heuristic is an empirical, learn-as-you-go procedure which can’t guarantee finding a solution, but which will increase the probability of finding a solution over what would be possible using a purely random or ad hoc approach.
- Trial and error.
Different possible configurations are generated, and after a test of their "fitness" the good ones are retained and the bad ones eliminated.
The search for a solution proceeds without any sense of choice or calculation of the likelihood that any path will be superior to another. This technique can be made as efficient as possible by being systematic and keeping a record of attempts and their outcomes, so that no path or solution is tried more than once.
- Proximity.
- Hill climbing.
In this strategy, the searcher looks one step ahead to see what next action will best move him toward the goal.
- Means-ends analysis.
This is a set of procedures designed to reduce the distance from the problem state to the goal state through a sequence of carefully identified steps, taking into consideration all of the many different dimensions of difference between those states. It involves creating subgoals (the ends) to eliminate the differences between the current state and the condition for applying a desired operator (the means).
- Fractionation.
These methods involve breaking the problem into parts and solving each part separately.
- Mixed Scanning.
This strategy involves alternating between a general overview of the situation and a close-up, detailed, precise examination of a subset of it. The first gives the solver a quick sense of the overall situation, even though that may be somewhat vague and general. Then, given that context, it allows attention to individual parts in exact detail, permitting a close knowledge of pertinent areas to provide information about both potential or actual trouble spots, as well as a better basis for generalizing about the whole.
- The split-half method.
This method involves starting at the halfway point in a more or less linear system, and checking to see if the problem (or its symptoms) already appears there. If it does, the problem is in the first half of the system. If it doesn't, the problem lies in the second half. Next, the investigator goes to the half of the system where the problem is now known to occur and checks at its halfway point to see if the problem or symptom appears there. Each such iteration successively eliminates another half of what remains of the system as the source of the problem, and the process continues until the problem is located. This is much faster than random checking or simply starting at one end of the system and then proceeding consistently toward the other end.
- Pattern Search
In selected situations, the presence of patterns may either suggest solutions themselves or remind you of prior cases in which useable solutions were found.
- Hill climbing.
- Solution Selection Procedure:
- Develop possible solution alternatives.
Using as many of the techniques discussed below as are appropriate to the problem being worked on, create solution alternatives over the entire range of options, without concern for feasibility. Enough time should be spent on this activity to ensure that all plausible solutions are uncovered, including non-standard and creative ones.
Relevant questions to be asked include:- What constraints exist on the solution?
- What are the available resources for implementation? Are they adequate?
- Who is the decision-maker, and what are his/her sources of power in the situation?
- What are possible leverage points for implementation ?
- Are others involved? If so, are they favorable? If not, is their opposition serious? And if so, can it be changed?
- Evaluate the proposed alternative solutions using the pre-established criteria.
Techniques like PMI and Cost/Benefit Analysis will come into play here, and alternatives should be directly compared:
- Eliminate the alternatives which fail to meet essential criteria.
- Collect Risk/Benefit information for the remaining alternative solutions.
- Assess the degree of satisfaction each alternative provides.
- Ensure that the benefits provided are in the areas of high importance.
- Ensure that high risks and low benefits are not in the areas of high importance.
- Question if the risks identified are serious enough for an alternative to be eliminated, or whether it’s possible to develop a plan which could remove risk or minimize its effect.
- Select the best scoring/most promising alternative that meets these criteria as the proposed problem solution.
- If no proposed Solution provides sufficient satisfaction, recycle through the entire process again to look for more options!
- When a Solution alternative is finally selected, review and evaluate the potential problems that may arise when this “solution” is implemented, and proceed only if that review is favorable.
- Relevant questions to be asked include:
- Does the proposed solution:
- Adequately address the critical aspects of the problem?
- Satisfy the stated objectives?
- Is it consistent with organizational and/or other situational realities?
- Who would be the solution implementation "change agent"?
- You? Or someone else?
- Does he/she have the power, skills, knowledge to be successful?
- What is the probability of success?
- What are the risks if the plan fails?
- Is resistance to this change likely?
- From whom?
- How strong/serious is this likely to be?
- Can it be overcome?
- Are there any sources of support?
- From whom?
- How important is this likely to be?
- Does the proposed solution:
- Develop possible solution alternatives.
- Solution Implementation Procedure:
- Determine the efficacy and completeness of implementation.
Omission or improper completion of this step is a common reason for the failure of the problem-solving/decision-making process, because ineffective implementation hasn’t been detected and therefore can’t be corrected.
- Evaluate the effectiveness of the Solution.
It is particularly important to evaluate the proposed solution in light of the problem statement generated at the beginning of the process. In addition to the expected technical considerations, affective, cognitive, and behavioral outcomes (the impact on the people involved) should be considered.
- Modify the Solution as required by the problems revealed in the evaluation process.
- Repeat the evaluation cycle to be sure that those problems previously identified and any new ones generated by the changes have all been satisfactorily resolved.
- Determine the efficacy and completeness of implementation.
What we’ve done up to now has been to confirm that:
- We are attempting to solve the right problem
- Solving it will pay off sufficiently well to be worth the effort expended.
- We have identified and incorporated all important problem aspects and parameters.
These steps are essential to arriving at a viable solution, but are insufficient in and of themselves because they are too general to be implementable. What we must do now to achieve the desired payoff is to actually delve into the specifics of the problem, and then go about developing a detailed solution which will allow us to realize that payoff.
CAVEAT!
The techniques that follow are methods for turning what would otherwise be a completely subjective, basically “gut feel” decision-making process into one which has at least a semblance of objectivity. The problem with it is that, as earlier noted, unlike pure mathematical processes (e.g. addition) which always yield precisely accurate and repeatable results, when a value is generated by one of these methods it is essential to recognize that result is heavily dependent upon the initial assumptions made, and therefore might be quite different, even diametrically reversed, if those initial assumptions are even slightly changed.
Not only does this mean that it is possible for the analyst to subconsciously influence the decision while maintaining a facade of objectivity, but that any decision reached as a result of such an analysis must be viewed with great caution and even skepticism.
The ways to counter this problem are to:
- discuss and validate the values assigned to the key parameters with other persons who know the situation but have no stake in its outcome.
- repeat the analysis using a range of each of the subjective input parameters, and then compare the indicated decisions. In this way, you can determine the sensitivity of the analysis to those input assumptions, and then treat the reliability (or non-reliability) of the resulting decisions accordingly.
In the examples that follow, for the sake of simplicity in describing these techniques, only one “pass” is made.
- PMI = Plus/Minus/Interesting of Edward de Bono
This is an adaptation of the simple “pros and cons” analysis that has almost universally been used for centuries.
To apply it:- Construct a table with colimns headed “Plus”, “Minus”, and “Interesting”
- In the respective columns list the appropriate factors influencing the desired action together with their expected effects
- Assign a subjective (estimated) positive or negative score for each.effect
- Add up the scores.
A strongly positive score indicates that action is probably justified, a strongly negative score that it should be avoided. In between scores are ambiguous, and allow moving in either direction as desired.
Example: Deciding whether to relocate from Long Island to New York City.
Plus Minus Interesting More Social Activity
In The City (+5)Have To Sell My House (-6) Easier To Find A New Job (+1) Much Shorter Commute (+5) More Pollution (-3) Meet New People (+2) More Interesting Places To Go (+3) Less Living Space (-3) More Difficult To Get Work Done (-4) - High Rent (-5) More Crime (-3) +13 -17 -4
Total = 13 -17 - 4 = -8 => Decision: Stay on Long Island.
- SWOT ANALYSIS. In this process you analyze a situation by identifying its Strengths, Weaknesses, Opportunities, and Threats.
In its simplest adaptation, a table similar to that for PMI can be created, with 4 columns but in every other way identical. The same problem with the subjectivity of the values assigned to the relevant factors exists, with the same solution.
The questions that are appropriate for assessing each of the four SWOT factors will vary depending upon the type and context of the problem being analyzed, and will necessarily be very different for (say) a personal problem as opposed to one that is societal, technical, business or political, but certain common themes will exist.
Typical questions that will reveal the required information are:
- Strengths (always positive)
- What assets does your entity (person, organization) possess?
- Physical
- Intellectual
- Temporal
- Capital
- Other
- What things does it do well?
- What assets does your entity (person, organization) possess?
- Weaknesses (always negative)
- What assets does your entity lack?
- What things doesn’t it do well? (i.e. What needs improvement?)
- What weaknesses do others perceive that you don’t?
- Opportunities (always positive)
- In what immediate and long term ways can your strengths be used effectively?
- external factors
- technological and/or social trends
- the economy
- relationships
- competition
- etc.
- What are the longer range opportunities, and what must be done to take advantage of them?
- Can you improve the things you don’t do well?
- In what immediate and long term ways can your strengths be used effectively?
- Threats (always negative)
- What obstacles do you face?
- What things should be avoided?
- What is your competition doing?
- Are the required specifications for your job, products or services changing?
- Is the current economy, changing societal trends, and/or technology threatening your position and/or prospects? (Are you in an economic bind?)
The strictly qualitative output of the SWOT analysis can be quantified and analyzed in precisely the same manner as that of both the PMI and Force Field techniques, so they all really represent slightly different (and complementary) ways of achieving the same result.
- Strengths (always positive)
- FORCE FIELD ANALYSIS
This method is conceptually very similar to both SWOT and PMI, especially the latter, with the important difference that rather than focusing on factors internal to the success or failure of a proposed solution it describes the external forces arrayed for or against it, so that a decision can be made which takes into account all interests. As with the other methods, this is really nothing more than a specialized and highly refined way of comparing pros and cons.
Where a plan has been decided on, Force Field Analysis allows you to appropriately act to reduce the impact of the opposing forces and strengthen/reinforce the supporting forces, as well as to implement changes that may make success more likely .
To carry out a Force Field Analysis:- List all forces for change in one column, all forces against in another.
- Assign a score to each force, from 1 (weak) to 5 (strong).
- Draw a diagram showing the forces for and against, and their size.
The same caveat earlier noted in applying the other techniques regarding the subjectivity of the assigned scores again applies here.
An example of a Force Field Analysis applied to the same decision regarding whether or not to relocate to the city used earlier in the PMI analysis is shown below:
The result of this analysis is only slightly negative, so any decision regarding whether or not to proceed with the proposed move probably shouldn’t be made on the basis of it alone, but rather on the totality of this and any other forms of analysis performed.
The preferred decision making process consists of a meta-analysis in which each of the various techniques presented herein is applied (as appropriate), and then the final decision summarizes their overall effect. For example, if each of the PMI, SWOT, and Force Field analyses were also slightly negative, then the overall conclusion would be fairly strongly negative. But if one or more was positive, then the overall result would be ambiguous at best. In most cases, because of the considerable impact on the system that would follow from a major change, an ambiguous result will almost always result in continuance of the status quo (= no change). In this problem, both PMI and Force Field analyses are in agreement, so the proposed move to the City is counter-indicated! (But remember again the caveat regarding the subjectivity of the weights assigned to each of the decision criteria!)
- Trial and error.
- Paired Option Comparison Analysis
Many real life problems contain several plausible alternative solution options, but little or no objective hard data which will allow you to objectively choose between them. In such cases, a purely subjective technique such as Paired Option Comparison Analysis can still enable the rational selection of the most important problem to solve first, and/or reaching the best solution attainable once that choice has been made.
Paired Option Comparison Analysis Procedure:- List the Solution options. (Letter designators are usually assigned for convenience.)
- Build a table in which each option appears as both a row and a column header.
- Zero out the table diagonal in which each option is compared with itself, as well as all cells below that diagonal (= the converse duplicates of the above-diagonal cells).
- Use this table to compare each option with every other option, one-by-one.
For each such comparison:- Decide which of the two options is the more important.
- Enter the letter designator of the more important option.
- Assign a score to show the size of their difference. ( Since this is purely subjective, any convenient scheme may be used: Most common is: 0 = no difference, 1 = small difference, 2 = modest difference, 3 = major difference.)
- Total the scores for each option.
- Convert these scores into percentages (if desired).
- Select the highest scoring option.
Example: A local community college student is trying to decide which of the options listed below will be in her best interest to pursue after she receives her Associate’s degree. There’s no good way to accurately quantify their value, but by applying this technique it should still be possible to make a rational decision.
As she sees the situation, her options are:
- Continue on full time to obtain a Bachelor’s degree immediately (A)
- Obtain some kind of (temporary) employment, while continuing on in night school. (B)
- Begin a full time career in teaching (C)
- Use her musical skills to try to “make it” with a Rock band. (D)
To solve her problem, our hypothetical student creates a Paired Option Comparison Table as follows:
| Paired Option Comparison Table Example | ||||
| College (A) | Night School (B) |
Teach (C) | Music (D) | |
| College (A) | - | A,2 | A,1 | A,1 |
| Night School (B) | C,1 | D,2 | ||
| Teach (C) | D,2 | |||
| Music (D) | ||||
In this case, the analysis has failed to provide a clear decision because our student is equally desirous of continuing on to obtain her Bachelor’s degree immediately or trying to begin a career with a Rock band. But what is painfully apparent is that any thought of attending night school is out, and that teaching is also not really an option worth further consideration!
This is not the kind of nice, neat answer we would prefer, but the real world is often messy so we shouldn’t really be surprised. But given this ambiguity, the student decides that perhaps the key direct comparison she made between the two dominant options of continuing on in college (A) and trying to establish a career in Rock music (D) should be used as a tie breaker - in effect giving that comparison more weight!
Checking the table, we see that this direct comparison favored the College (A) option by the slimmest of margins. But we also note that the college option was preferred over each of the other alternatives, so on balance a clear if narrow margin in favor of College (A) emerges as the student’s final decision!
