** Kreativitet/Creativity **
Practical Purposeful Creativity Constructs
by Tom Gilb,
Independent Consultant and Author,
Iver Holtersvei 2, N-1410
Kolbotn, Norway
Telephones: +47-66-801697, (Agent) +44-81-847-0471

Introduction
This paper is written as an invited contribution to a book “Creativity, Innovation and Cooperation" (Springer) and a special issue of “AI & Society: the Journal of Human-Centred Systems and machine Intelligence". The editor is Robert C. Muller (Fax +44-491-579750).

Definitions

Creativity: accessing ideas to improve some values.

Practical (INDUSTRIAL) Creativity: Systematic Identification of ideas which serve useful human purposes

Purposeful Creativity: Identification and validation of ideas which meet specified objectives

Part One: A Theory of Practical Creativity

Practical Creativity is measurable in practice.

Creativity is judged by speed, cost, accuracy.

The “goodness" of a creative process may be described quantitatively in terms of it's multiple attributes. Some creativity attributes are:

• speed (how fast we solve a defined problem)
• cost (at what cost do we solve the problems, and what does the solution itself cost?)
• accuracy ( to what degree did we solve a problem in relation to its multiple defined quantified objectives and constraints?)

Creativity is a result of the creativity process structure and its particular agent.

A creative process is more or less suitable (or “good") for its purposes as a result of:

• its structure (how the creative process is defined and managed)
• who does it (the individual, the team, the organization).
• its resources (time, money, knowledge base)

Ten fundamental principles of practical creativity.

1. Practical creativity must have a defined purpose which is objectively measurable.
2. Practical creativity must operate in multiple purpose dimensions at the same time.
3. The result of practical creativity depends on the clarity of the stated objectives.
4. The result of practical creativity depends on the nature of the creativity process and the agents employed to do it.
5. Any creativity objectives initially defined, will tend to change as time goes on due to changed perceptions, changed external world and experience with delivering partial results.
6. The practical creative process follows the rules of any similar “design", “planning" or “engineering process": it is merely a higher level generalization of them.
7. The “net value" of an additional idea for solving a defined problem can be estimated in relation to remaining unsatisfied objectives. How far will the idea move us in the direction of our final objectives, from where we are at the moment?
8. The degree of yet unsatisfied objectives for a problem being solved, determines the priority needed for continued creative effort. This (degree of yet unsatisfied objectives) is a function of previously accepted or applied ideas and of any changed objectives since they were originally defined.
9. Seemingly “bureaucratic" idea management processes can stimulate, protect and justify creative effort. Total freedom of thought is not necessarily the best way to get useful creativity.
10. If a creative effort fails to satisfy even a single real, defined or not, critical success factor then it is, in practice, a total failure. It serves no useful purpose.

Part Two: Practical Creativity Devices

Creativity Objectives

If the objectives of a creative effort are unclear or misunderstood by the participants, then even a perfect effort to reach the misunderstood target will fail to solve the problem which was really on the agenda.

Our current culture has not yet learned to specify its objectives in a clear enough language. A language is clear enough, when:

• all participants understand precisely the same thing with all objectives and constraints
• objective observers can test and conclusively determine that the objectives have been reached within stated constraints.
  

In my industrial practice I have concluded that for most objectives the following requirements must be met:

• they must be defined with a scale of measure
• they must have a defined meter or test for practical measurement on that scale
• they must have at least one defined future required level on that scale
• the required date of achieving the required level is vital to specify as well.
• it us quite useful to state the current levels on the scale for the system being improved.
  

I have developed a simple language format to achieve this specification. It has been adopted by many companies for universally recommended use (such as ICL, HP, IBM). Here are some examples and definitions.

Practical trait specification examples.

RELIABILITY	“how often it breaks down"
SCALE	mean time to failure
METER	operator log time notation
PAST	[1992, London] 300 hours
RECORD	[1991, Paris] 1000 hours<-Corp. Quality Monthly Reports Europe Sept91.
MUST	[1999, USA] 2000 hours<- Corp. Mkt. 95
PLAN	[1998, North America] 1500 Hours?

This is a simple example of specification.

	<- insert a name tag at left, and a “gist here"->
SCALE
METER	[ ]
PAST	[ __-199_, ]
RECORD	[ __-199_, ]
MUST	[ __- 199_, ]
PLAN	[ __- 199_, ]

This is an example of a blank form to fill out. Copy it and try to fill it out with some of your goals.

the trait reference tag, in CAPITALS	“the gist of the entire definition, in quote marks, a sort of summary in words of the details in numbers below"
SCALE	this is your definition of the scale of measure to which the numbers below are attached. This is the “kilometers per hour" part of the definition
METER	[ this qualifier allows you to say when a measurement applies ] this is the specification or reference to a specific practical and economic way to measure where your system is along its scale. The “speedometer" or “voltmeter"
PAST	[ day and month data here-1996, <place, project, country, customer>] PAST is one or more existing or past reference points of data for comparison. How bad are things now?
RECORD	[ __-199_, ] RECORD is the best number you know in a given area <country, business, technical sphere>. It lets us know the border for excellence.
MUST	[ defined future, defined place ] MUST “do". MUST is the minimum achievement required in a defined future and place so we avoid system failure ( like breach of contract or the boards expectations)
PLAN	[ defined future, defined place] PLAN is one or more points which are required, desired, “success" levels. People are not expecting nor willing to pay for more (even if more would be nice and is acceptable).

Here are some definitions of what we fill out. Below, some examples.

USER-OPINION	“How good the actual end user of any age feels about using our system"
SCALE	Percentage surveyed actual users of one year or more who “like it a lot"
METER	[ Customers who sent in the card] Postal survey with big prizes for answering.
PAST	[ 1991-3, Western USA, street Gallup] 60% <-- Market Survey 1993 page 33
RECORD	[ 6-1993, Marketing Age July 91, Xerox] 85%<- nearest competitor
MUST	[ 1- 1997, USA Market] 90%<- Corporate Policy and Plans this year.
PLAN	[ 12-1999 , European Market]<- European Sales Plan Page 2.3

BUDGET-LIMITS	“ This is an example of specifying a resource limit"
SCALE	% deviation from final budget amounts, on average
METER	[Europe only ] European Headquarters Financial Accounting reports
PAST	[1993, All development projects average ] +15%<- Corporate Accounting.
RECORD	[ June1992 , Project Omega ] +50% <- Omega post mortem analysis 4.65
MUST	[by 1997 worldwide ]+1% or less <- The Board's new policy
PLAN	[ __- 1999, Texas ] 0% or better <-Trial area for new motivation tactics

Multidimensional Creativity Objectives

Quality objectives are scalar (can be expressed with numbers on a defined scale of measure) traits of a system ( for example project, organization, product). They can be thought of a arrows (the scale) attached (traits) to the mission (the traitless core of the system).

The real world rarely gives us problems to solve with regard to a single dimension. Even if one dimension of improvement is the dominating wish, we must be certain to know the other critical dimensions which must not be ruined by negative side-effects from our new creative ideas. All ideas have potential negative, as well as positive side effects in the areas of the complete set of conditions of successful existence of any system.

Consequently even if we have no intention of changing a satisfactory trait of a system, it must be specified testably so that we can evaluate whether we are helping or hurting it with new ideas.

Creativity Opportunity Sensing

When there is a gap between the current or past levels (PAST) of quality or cost of a system and our new required levels for the future (MUST or PLAN) this effectively defines a “problem" to be solved. It represents an opportunity to apply creativity to close the gap with new ideas.

Creativity Contribution Estimation

The degree to which an idea is useful can be estimated. The precision of this estimate varies depending on many factors:

• the available facts and measurements regarding previous use of the idea
• the degree to which those facts were for relevant environments
• the mixture of other ideas which can impact the effect of a particular idea
• the quality of implementation of the idea in practice
  

In spite of this it can be useful to attempt to make some estimate of idea goodness in a systematic way ( all ideas versus all objectives on a table).

For example:

Practical Idea Evaluation by “Impact estimation “ tables.

IDEA tag---->>>	OMEGA	% way	EVIDEN	Credible?	Adjusted	Who est.?
		to PLAN	-CE for =	(1.0 ->0)	(% x Cred)
GOALS (past->plan)
MTBF (100->200 hrs.)	150 hrs.	50%	All 200 at 150->200	0.8	40%	George
LEARN (3min.->1 m.)	1 min.	100%	Expert estimate	0.6	60%	Wendy
-------------------------	------------	------------	------------	-----------	----------	---------
COST (1 mill budget)	100.000	10%	contract price	0.8	12%	Group
Benefit Impact		150
Benefit/Cost Ratio		150/10

The above table is an example of some of the estimations and documentation which can be made for each idea versus each goal. Not all are always necessary. It depends on how much control you want over an idea. We are intentionally not explaining the detail of this table here, as it would be too lengthy for this article. We hope the reader can deduce the meaning of most of it.

IDEA tags ---->>>	OMEGA	DELTA	ALPHA	BETA	GAMMA	Sum ±	SUM	Worst Case
GOALS(past->plan)
MTBF (100->200)	50%	10±5	30±25	-20		±30	70%	40%
LEARNING(3min->1)	100%	70±50	40±5	80±10		±65	290%	225%
COST (1 mill budget)	10%+30%	5±5	-15	0		+35/-5	0	35%
Benefit Impact	150	80	70	60
Benefit/Cost Ratio	150/10	80/5	70/-15	60/0

This table shows the use of the goal scale-neutral percentage of impact on PLAN level. It can be used compute various useful approximations, such as the best benefit to cost strategy score, the worst case result etc. Key: 0%=no change on objective when idea is used, 100% idea will bring us to the planned level on time. All other numbers are relative to these two.

Creativity Measurement and tracking

The reality, for even apparently small and simple systems, is that they are very complex and defy our ability to predict accurately what will happen.

One customary way to find out things work is to “just do it". If it fails, we try something else. This method may be too costly or risky for some purposes. In this case the ideas are first explored by means of a prototype using the ideas. If it fails to give appropriate results, we are warned away from investing in a full scale application of our ideas.

Unfortunately, prototypes are never fully realistic and may not give us good enough warning that our ideas will fail on a larger scale.

There is a useful compromise available. It is widely used intuitively by many of us, but it seems rarely taught in the literature, nor adopted as a formal project control method by industry. I call it “Evolutionary Result Delivery".

Evolutionary result delivery is a form of process control. It is identical in principle to the currently popular quality ideas of Dr. Shewhart and Dr. W. Edwards Deming, the “Plan-Do-Check-Act" cycle.

This idea evaluation process can be controlled by applying some variation of the following three policy ideas:

1. TIME CONTROL: delivery cycles shall not exceed 2% (average, maximum5%) of the total deadline framework (example weekly for a one year project).
2. BUDGET-CONTROL: development cycles shall not exceed 2% (average, maximum5%) of the initial total budget (example 20.000 per million).
3. PRIORITY: Delivery steps which have the highest value (as estimated by impact estimation table positive traits) over resources (IE table resource traits) ratio on the next step shall have priority to be carried out first.

Here are some ground rules for finding the evolutionary result steps.

1. Use the impact estimation table to identify high value and low cost ideas
2. Assuming those ideas exceed the “2%" requirements, try chopping them up somehow so they do. Often it is the whole idea applied to a small part of the environment which will do the trick.
3. Keep on asking the simple question: "what can we do next week which will impact some of our PLAN level aspirations even just a little bit?
4. Do expect to modify the existing awful system. Do not plan a large project to “replace" the awful old system with your new dream system.
5. Focus on one single high priority trait PLAN at a time.
6. If in doubt (or, in any case!) ask your users and customers what they would most like to fix “next week"
7. Do not worry too much about all the other steps, yet unknown, and the possibility of a dead end street. Focus on high value to low cost accomplishment, in the direction of the long term PLAN levels. You don't even know enough about the real future to worry intelligently. Drive one street at a time.
8. Keep firmly in mind that the ideas you are identifying must include whatever it takes to actually bring home the bacon. That means, when implemented, the ideas must measurably increase our desired traits indicators towards their planned levels. So “normal" planning of preliminary activities (train, decide, design, construct, test) are not valid implementation steps unless they include enough additional activity to install with users and gain measured benefits.

A Planning Form

IDEA tag---->>>	OMEGA	%	OMEG1	OMEG2	OMEG3	<-step names
GOALS (past->plan)		to PLAN
MTBF (100->200)	150 hrs.	50%	130 hours	140hours	150hours
LEARN (3min->1)	1 min.	100%	1 min.	1 min.	1 min.
-------------------------	------------	------------
COST (1 mill budget)	100.000	10%	30.000	50.000	100.000
Increment COST %			3%	2%	5%
Benefit/Cost Ratio		150/10	30/3	10/2	10/5

The point of this planning format is to show the benefit to cost increments for each planned sub-step. In this case the OMEGA idea alone is too costly for our policy guidelines. So we have chopped it up into OMEG1 to OMEG3 (which are defined in detail “elsewhere").

Such planning can be, and often is , done intuitively, with no documentation. Formal guidelines (written planning and formal evaluation of results-actually-gained versus planned-results) are appropriate when tight control must be maintained in a larger project, responsible to many parties.

Why does evolutionary result delivery help the creative process?

The main industrial interest in the evolutionary result delivery method is the tight control it gives over meeting deadlines and budgets while targeting ambitious quality objectives. From a creativity management point of view it can be seen as a method for constantly testing creative ideas in a low risk and controlled way.

If for example 2% steps are used (weekly steps of actual result delivery cumulating through a project year) promising, but risky, ideas can be tried out in a single 2% step. If they work well, they are proven and accepted. If they need adjustment, this can be attempted in the next step. If they are bad, they can be quickly yanked out of the system and replaced with more promising ideas.

It is easy to say “no" to a creative new idea if it is risky and can first be validated at the end of a costly project, which might fail totally, if the risky idea fails. It is much more tempting to say yes to a promising, if risky, idea if it can be tried out in practice, in an early evolutionary delivery step. There is sufficient promise of gain, coupled with limitation of risk (worst case being a 2% loss) to encourage more radical creativity than otherwise allowed.

Creativity Protection

In my industrial practice we can identify a number of mechanisms which protect the creative impulse, some of which have already been discussed. Here is a sample, without any pretense of thorough explanation.

To summarise creativity protection in terms of the methods discussed above:

• using measurable objectives, weird creative ideas can be justified when they demonstrate ability to meet these objectives, even if many people would reject them otherwise.
• the small controlled steps of the evolutionary delivery method encourage more risk-taking when considering new ideas, because the risk is controlled by the step size.
• impact estimation tables stimulate creativity because it become more clear which objectives need some new ideas, and which ideas will in fact probably not work well.
  
  

Creativity Protection in the “Software Inspection" method

Here are some other protection mechanisms, from the idea quality control process known as “Software Inspections" (see References for more detail)

• Inspection teams are asked at a “Kickoff Meeting" (IBM's term) to select a new higher numeric ambition level ( for example “to find 2 more major issues per page than last time") and then to adopt a new idea for their teams work process which will enable the team to perform better ( a “strategy"). This everyday process has the effect of getting constant experimentation, with same week numeric feedback on achievement.
  
• Ideas proven at the team level which were discovered by the Kickoff meeting process described above, will stimulate similar efforts by other team to be creative or to try the new ideas themselves.
  
• IBM (Robert Mays and Carole Jones see IBM Systems Journal No. One 1990) instituted a “Causal Analysis" process where small teams regularly analyze software defects and brainstorm about their causes and ideas for improvement. This process gives regular access to a creative work session for the rank and file.
  
• My own variation of Software Inspection process specifically encourages the logging of suggested improvements to the work process (to Rules and procedures) at any time during the Inspection process itself. The message is sent that we encourage constructive criticism and new ideas at all times by everybody. My clients report that this message is effective in encouraging people to be more active in suggesting improvements to their work process outside of the Inspection process itself. They have learned that such behavior is desired and they have learned the communication channels ( to the “Owners" of the work process description).
  
• IBM feeds the “Causal Analysis" brainstorming session ideas, via a cumulative computer database, to an Action Team ( I prefer to describe them as a “Process Change Management Team"). These people, off-line to deadline pressured projects, are charged with taking the necessary time to come up with new ideas for improving the work process so as to avoid the type of defects which have been occurring. This team represents another level of creativity and of receptiveness to creative ideas.
  

Part Three: Would Computers make a difference to creative thinking?

Not as big a difference as the other above mechanisms. No more than a word processor might have helped Shakespeare.
As a computer professional for 35 years I find little currently available from computers which is as effective and stimulating as the methods described above. I suspect that the notion that computer software can be used to stimulate creative thinking is more wishful thinking on the part of those who would gain by some products, than it is a realistic comparison with the many available methods for stimulating and evaluating creativity by a simpler and more direct means.

References

1. Gilb, T. “Principles of Software Engineering management", Addison-Wesley 1988.
2. Gilb, T. and Graham, D., “Software Inspections", Addison-Wesley 1993 (Summer)
3. Gilb T. , “Idea Management: The Results-Driven Quality Planning Method", Unpublished manuscript in progress (available free to qualified professionals)

Author Biography

Tom Gilb is an independent international consultant in quality and management to industry. He has authored seven published books and many articles. He was born in California, 1940 and resides in Norway. He is currently amusing himself by applying his methods of creative thinking to applications outside industry such as: personal and career life design, planning the use of relief-aid society third-world activities, environmental protection planning, musical production planning, railway expansion planning, army reduction planning and quantifying the quality attributes of office lamps.