An Overview of
Design Method

This page has not been revised since January 2001, but
the version on another website has been revised many times
since then, so I strongly recommend that you read
THE REVISED VERSION.

 

 

 

 

 

 

 

 

 

 
 

by Craig Rusbult, Ph.D.

    This page builds on the foundation of An Introduction to Design.  A few ideas from the introductory page are summarized below:
    A problem is "any situation where you have an opportunity to make a difference, to make things better";  design is the process of using creativity and critical thinking to improve a problem situation.  The objective of design can be a product, strategy, and/or theory.  This includes almost everything in life!
    When the intro-page describes a general process of design and illustrates this process with the designing of a minivan, it is using my model of Integrated Design Method (IDM) as a framework (even though it isn't labeled "IDM") so you're already familiar with the general structure of IDM.

    This page takes you further in your exploration of the fascinating adventure of design.  It begins with an overview in which the structure of the design process is described more briefly and in a new way, in terms of seven modes of action: DEFINE OBJECTIVE, DEFINE GOALS, SEARCH, IMAGINE, TEST, EVALUATE, and THEORIZE.  Initially we'll focus on the design of products, although eventually the scope of "design method" will be increased to include theories and strategies.

    A Brief Outline of Integrated Design Method

    DEFINE OBJECTIVE
    Based on known observations (based on everything you already know about "what now is"), define an overall objective by deciding what you want to design.

    DEFINE GOALS
    Based on a knowledge of what is, and inspired by ideas of what could be, define the goals for a product by defining the desired properties -- the composition (what it is), functions (what it does), and performances (how well it does) -- of a satisfactory product.
    These goals are the focus of action during the process of design, because goals guide the generation of ideas for products, and [as shown below] the evaluation of a potential product is done by comparing goals with predictions (from imaginary mental experiments) or observations (from actual physical experiments).

    In common language, "objective" and "goal" usually mean the same thing, but in IDM they are different.  For example, in the "Introduction to Design" page the objective is a minivan, and the goals are the desired properties for a minivan.

a comment
for the reader: Eventually, the
right side of
this page (in the
yellow column)
will contain
interesting supplementary
material:
illustrative
examples,
quotes,
cartoons,...

 

    SEARCH (gather old information)
    Usually the first step in design is to understand the current situation.  Search for old products (those now existing) that are similar to your goal product.  For each old product, gather observations that already are known, and ask "What are this product's properties, and how closely do these properties match my goals?"
    IMAGINE (generate new ideas)
    Think about possibilities for creating new products (by modifying an existing product, or...) and run "thought experiments" to predict how these changes would affect composition, functions, and performances.  Would the predicted properties of any new product more closely match your goals?
    TEST (do "reality checks")
    For each product (old or new) being considered, get the product by acquiring it (if possible) or constructing it (if necessary), design experiments that will show you its actual properties, then compare these properties with your goals.

    EVALUATE (and decide)
    The process of design requires generation and evaluation.  Each potential product (old or new, existing in the mind or in reality) is evaluated by comparing predicted properties with goals (for predictive feedback) or by comparing  observed properties with goals (for empirical feedback).  Eventually, you may find a product that satisfactorily achieves your goals, and you consider the problem solved.  Or you continue searching, or abandon the search.

    THEORIZE
    In an optional mode of action, it may be useful to do a Reality Check by comparing predictions with observations so you can evaluate your theories, to see whether "the way you think it is" matches "the way it really is."

 


 

 

 



    The outline above is intended to quickly show you the general structure of Integrated Design Method (IDM).  Now we'll look more closely at the process of design so you can understand it more thoroughly, so you can improve your ability to teach these methods to others.  To help you understand, at a deeper level, the components of IDM and their integrated relationships, instead of a simplified IDM-diagram (as in the outline above) we'll use the full IDM-diagram that shows more details.  Both diagrams appear below, to let you compare them in order to see their similarities and differences:  

 


 
    In the following overview, the first mode to be discussed is Define Goals, which appears in the top center of both diagrams.  

 

 

 

 
 
  An Overview of Integrated Design Method

    1A. DEFINE OBJECTIVE
    To solve a problem, first you must recognize that a problem exists;  you do this by understanding the actual current situation (the NOW-state), imagining a desirable future situation (the GOAL-state), and deciding that these two states (the actual NOW and the desired GOAL) don't match.
    Notice that DEFINING AN OBJECTIVE (by recognizing a problem/opportunity) involves four of the other six modes of action.  First, you actively SEARCH for information that already exists, in an effort to understand the current state.  Then you creatively IMAGINE how things could be different, critically EVALUATE a variety of potential futures, and DEFINE GOALS for the type of future state you want.  In blending these actions you can quickly shift back and forth between modes, or take some time to thoroughly explore them.
    In the IDM-diagram below, two modes (DEFINE OBJECTIVE and DEFINE GOALS) are highlighted with a white background.  First, based on old observations about product (from the SEARCH mode) you recognize a problem and define an objective.
    The arrow pointing from objective to design could be drawn so it points in both directions, so it also points from goals to design, because a critical evaluation of potential futures will depend on the goal-states that are being imagined.  Nevertheless, it makes sense to think about moving from a general decision about an objective (about what will be designed) to specific decisions about goals. The second aspect of objectives-and-goals is discussed in the following section.

 

 

 


    1B. DEFINE GOALS
    A variety of goal criteria -- based on personal values about what is important and what is good -- are used to judge whether a particular type of goal-state is desirable.
    If the objective is an improved product, one way to define a goal-state (or a class of goal-states) is to specify the desired properties for a product in terms of its composition (what it is), functions (what it does), and performances (how well it performs each function).
    These three general criteria can be split into sub-criteria that are more specific and concrete.  For example, functions might be defined by asking "Can we make it cheaply?" and "Will it be durable?" and "Does it appeal to people?" and "Will they buy it?"   The corresponding questions about performance might be: What level of functioning (for being cheap, durable, appealing, or sellable) are you hoping for in your most optimistic dreams, and what level would you accept as minimally satisfactory?
    If some criteria are in conflict, how will you prioritize their relative importance?  For example, if increased durability requires increased cost, how will you balance these conflicting factors?  { But it may not be worthwhile to invest much effort in thinking about "balancing" until you are evaluating specific competitive options.  At that time, instead of trying to deal with vague generalities, you may be able to make accurate estimates, such as how much more it will cost to get a certain level of increased durability. }

    Problem solving occurs in three stages:  A) recognizing that a problem exists, that something could be improved and you have an opportunity to make it better;  B) deciding to pursue a solution for this problem;  C) trying to solve the problem, which occurs when you have achieved an actual state that is a satisfactory match for the goal state.  Stage A is discussed at the beginning of this section, and Stage C is the main theme of the sections that follow.  Between A and C, however, an important decision must be made in B.  Why?  Because even when a problem has been recognized, this does not guarantee that a solution will be actively pursued.  Since there are many problems, but a limited amount of resources (people, time, money,...) available for solving problems, decisions about "what to do" are necessary.
    Moving from a problem to a project (in which you actively pursue a solution) requires evaluation and decision.  You must weigh the potential benefits of a proposed project, compared with other alternatives, and decide whether this project is likely to be a wise investment of your time and effort.  In making this decision, it is useful to ask "so what" questions (Why should we do it? What are the potential benefits? Is it worth doing?) and practical questions: Is there hope? Are there rational reasons to expect that our actions will lead to a solution, that this problem can be solved using available resources such as people and time, materials and money, technology and knowledge?


    2A. SEARCH (gather old information)
 
  During a problem-solving project, an important part of solving a problem -- of moving from an actual current state to a desired future state -- is to understand the current state more accurately and completely.  A designer does this by searching for useful information, for observations about products.  This is shown with the white highlighting below.  { note: This "isolation diagram" has been simplified and streamlined by omitting the initial step, Defining the Objective. }

 

 

 

     In addition, there is a semi-white background (light gray) behind three elements -- generate product, design experimental system, and do physical experiment -- because when we ask "Are these actions necessary for remembering?", the answer is YES and NO.  Yes, it is necessary that someone did these actions in the past, to produce the observations.  No, a designer doesn't have to do the experiments, if the observations (and a description of the products and experiments) can be found by doing an information search.
    Knowing how to find information is a valuable skill that will become increasingly useful in the future due to the widespread use of modern information technologies.  Learning how to improve this skill -- how to effectively use libraries, the internet, databases, and other sources -- will be a good investment of time.  Here are a few suggestions: be persistent (because a thorough search takes time, and diligence usually is rewarded), knowledgeable (about the "standard sources" for finding particular types of information), creative (to find non-standard sources), and critical (to evaluate the reliability of sources).  Be sociable and ask for help from those who know about a particular field, or from reference librarians who can help you find sources and develop strategies for searching.  Often, libraries offer workshops showing you how to find information, and internet search services have "tips for effective searching."   {Eventually I'll provide links to web-pages that discuss strategies for searching. }
    In the "isolation diagram" above, the aqua-colored highlighting shows that searching generates empirical feedback when you compare old observations (from old experiments on an old product) with the desired goals for a product.  This feedback -- when it is used as the basis for questions about action planning, either long-term or simply "what to do next" -- can stimulate and guide your search.  You can ask:  Has my search been thorough, in breadth and depth?  Does it have enough breadth?  ( Have I checked a wide variety of old products whose compositions and functions are similar, in one or more ways, to my goal product?  Should I continue searching for more old products? )  Is there enough depth?  ( Do I have enough data about compositions, and about the performances of each old product for each function?  Should I continue to search for additional data?  of what types? )
    While you are reviewing what already is known, you may find an old product (perhaps one that previously was unknown to you) that satisfactorily achieves your goals, and you consider the problem to be solved.  If not, you can move into an "imagining" mode of action.

    a comment about colorizing: In these descriptions of IDM, each element of the IDM diagram is highlighted in bold red print.  Each important concept that isn't in the diagram is in non-bold red print.


    2B. IMAGINE (generate and evaluate ideas)

    To design, you must generate and evaluate.
    You can generate ideas for a product in two ways:  by selecting an old product (i.e., a product that already exists, that you have found by searching) or by inventing a new product:

 

 

 

     Think about possibilities for creating new products.  How?  Since a "new idea" is usually a variation of an old idea, invention by revision usually occurs by modifying an old product to generate a new product.
    After imagining a new product you can ask "What properties would it have?"  To begin exploring this question, a common strategy is to make predictions by asking "What would happen if we used the new product in old experiments?"  Based on knowledge from the SEARCH mode, select an experiment that has been done with old products.  Then run this experiment mentally with the new product, using "if..., then..." logicif the modified product was in this experimental situation, then we would observe ___ .   To fill in the blank with a prediction, do a mental experiment:  construct a detailed mental model of the experimental system (of the product in its experimental context) and -- by using everything you know about patterns and principles (that are based on your knowledge of precedents, on what you know has happened with old products in this experiment or in similar experiments) and all you know about the new product -- ask "What will happen?" to produce predictions about the product.  { As explained in An Overview of Scientific Method, predictions involve some combination of theory-based deductive logic and experience-based inductive logic. }
    Now you can evaluate the product by comparing goals with predictions to produce predictive feedback when you ask, "How well does this new product match my goals for the product?"   Predictive feedback can stimulate several types of action.  You may decide that the new product is a satisfactory solution to the problem.  Or you may want to continue your search by doing goal-oriented invention of products, design of experiments, or testing of products.  These three actions require creative-and-critical thinking, as described in the next three subsections.

    Goal-Oriented Invention of Products
    The objective of goal-directed invention is to generate ideas for a product whose properties will match the desired goal-properties.  Whether or not an existing idea seems satisfactory, you can ask, "Could we obtain a better product by continuing the process of inventing?"
    A simple strategy is to invent LOTS of ideas, perhaps in a two-phase "brainstorm and edit" process.  Initially, in the creative brainstorming phase, you minimize critical restraints to encourage a free flow of creative ideas.  In the editing phase these ideas are critically checked for quality and utility.  During the creative phase you can think freely, knowing that any impractical ideas can be modified (or discarded) during the critical phase.  Creativity and criticality both operate, but not always at the same time.
    Typically, the process of invention occurs in cycles of creative revision, with each successive modification being guided by critical thinking that is based on scientific principles and on what has been learned from the predictive feedback in previous cycles.
    The main strategy for goal-oriented invention is the logical process of retroduction.  In contrast with logical deduction that asks, "If this is a true theory, then what will the observations be?", retroduction -- which uses deduction and induction supplemented by imaginative creativity -- asks a reversed question in the past tense, "These were the observations, so what could the true theory be?"  The essence of retroductive inference is doing thought-experiments, over and over, each time "trying out" a different theory that is being proposed (by selection or invention) with the goal of producing predictions that match the known observations.  Basically, the goal is to find a theory that, if true, would explain what has been observed.  This is retroduction in science.  In design, retroduction is similar, except that instead of aiming for predictions that match observations (as in science, where the objective is to design a theory), you aim for predictions that match your goals for the desired characteristics of a product or strategy.  { For a deeper discussion of retroductive logic, check the Detailed Examination of Scientific Method. } 
    A useful sub-strategy is analysis.  While you're in a SEARCHING mode of action, reviewing the properties of old products, think about the different parts of each product's composition, and how changes in these parts affect the product's functions and performances.  Search for cause-effect relationships by asking, "How do changes in what it is affect what it does and how well it does?"  While you're analyzing a variety of products, comparing their compositions and functions and functional performances, thinking about similarities and differences, you can search for correlational patterns and scientific principles.  The motivation for theorizing can be simply to construct new knowledge, or also to construct knowledge that will help you invent a new product.
    Stimulated and guided by these ideas, you can systematically modify an old product in ways that will generate a new product with the properties you want.  Or combine parts from several old products.  Or look for ideas in other areas;  look at old products, parts, or principles that originally were intended to achieve goals different than your own goals, and think creatively about how you can adapt a product that has been "imported from another area" to help you achieve your goals.

    Goal-Oriented Design of Mental Experiments
    The objective of goal-oriented invention of products is to achieve the main goal of obtaining a product that satisfactorily matches your goals.  By contrast, the purpose of goal-oriented invention of experiments is to achieve a sub-goal, to obtain information that will help you achieve the main goal.
    In IDM the definition of "experiment" is intentionally broad, to cover a wide range of situations: a physical experiment is loosely defined as "an opportunity to gather information" whether this occurs in a lab or in the field, whether there is an attempt to control all known variables or to observe a product "as it is" in an uncontrolled real-world setting.  There are many possibilities.  You might want to focus on getting information about only one property -- such as a car's acceleration, gas mileage, consumer appeal, paint durability, or crash safety -- or on testing one component of a multi-component product.  Or you could do an approximation experiment that has some characteristics (but not all) of an experiment that would be more realistic but less practical.  For example, an experiment might be run with a smaller scale-model of a large product, or a medical test might be done with lab animals instead of humans.

    Sometimes a visual organization of information is useful.  For example, the grid below can summarize information (in the 20 yellow-green cells) about five products (in the top row) and four experiments (in the left column):

 

Product A
(old)

Product B
(old)

Product C
(old)

Product D
(new)

Product E
(new)

Experiment 1 (old)

         

Experiment 2 (old)

         

Experiment 3 (new)

         

Experiment 4 (new)

         

    Scanning horizontally across a row shows the information that is generated, in one type of experiment, about five different products.  Or you can scan vertically down a column, to see how the properties of one product are revealed in different experimental contexts.
    This grid shows products that are both old and new, and experiments that are old and new.  Each cell can contain observations (if an experiment has been done already) or predictions, or both.
    For some products it is useful to make several grids, one for each design decision.  For a car, decisions would include the type of body, trunk, seats, doors, colors, engine, and transmission.  One grid could show possibilities for car bodies (with different shapes, sizes, materials,...) and experiments (ways to test each body for aerodynamic efficiency, consumer appeal, manufacturing cost,...) along with predictions and/or observations.  Other grids could show information about trunks, seats,...
    A grid is a useful way to summarize, in a clearly organized way, knowledge about products and experiments.  By scanning horizontally or vertically, you can focus your attention on a particular experiment or product.  By thinking critically and creatively about what you see in one scan -- or in several (horizontal, vertical, or mixed) -- you can search for patterns and principles, and for ways to improve a product.  Or you may notice a knowledge gap when you ask, "Do the experiments provide satisfactory information about all important properties of every product, or is there something else that we want to know but don't know?", and this will inspire the design of new experiments to generate the desired knowledge.

    Goal-Oriented Testing of Products
    But information generated in the mind (by prediction) is usually less reliable than information generated in the real world (by observation).  Therefore, it is often useful to "do a reality check" by converting a mental experiment into a physical experiment, to find out whether the "knowledge" being constructed in your mind is accurate and true, whether it corresponds to reality.
    action decisions:  Each cell in a product-and-experiment grid can be filled with predictions or observations, or neither, or both.  For each cell, for each combination of product and experiment, you can decide what is the best use of your time:  Should you invest the time that is needed to make a quick-and-rough prediction?  to make a careful prediction?  to use a computer simulation for making a careful prediction?  to collect observations by running a simple small-scale experiment, or an elaborate large-scale experiment?
    One important function of mental experiments is to let you explore, quickly and cheaply, a wide variety of experimental possibilities.  One goal of this exploration is to search for tests that seem capable of providing useful information, that may be worth doing as physical experiments in a TESTING mode of action.


    2C. TEST (gather new information)
 
  The modes of TESTING (to produce new experimental information) and SEARCHING (to gather old information that was produced in the past) are similar.  But they always differ in timing, in whether observations are made in the past or present.  Another important difference is that in SEARCHING you can often take advantage of the experimental work done by others.  Here is the TESTING mode:

 

 

    As discussed above, the process of goal-oriented testing begins in the mind, with ideas for products and experiments.  The design of an experimental system (which I'm defining as "a product operating in an experimental context") is the active integration of two activities: generating ideas by selecting an old combination (of experiment and product) or inventing a new combination, and evaluating these ideas.  In this way, action in the IMAGINE mode can lead to decisions about action in the TEST mode.
    After you decide what to do, you must get your hands on a product and whatever else is needed to run the experiment.  If the product is old, if it already exists somewhere, you have the option of acquiring it (if possible) or constructing it (if necessary).  But if the product is truly new, it does not exist and cannot be acquired from other sources, so you must construct it by modifying an old product or building it from scratch.
    After you have assembled everything in the experimental system, you can do a physical experiment and collect observations about the product.  Then you can evaluate the product by comparing goals with observations to produce empirical feedback when you ask, "How well do the observed properties of this product match my goals for the product?"
    Or you can evaluate the experiment.  Based on a careful analysis of your observations, you may want to consider what you have done as a "pilot experiment" whose main function is to guide you toward the design of a modified experiment that is more sophisticated or is done on a larger scale, that will generate information which is more useful because it is more accurate, precise, or complete.  Or perhaps the original intention was for the experiment to be part of a series of experiments that become progressively more sophisticated.


    3. EVALUATE (and decide)
 
  Three modes of action (SEARCH, IMAGINE, and TEST) produce information that is used in the EVALUATION mode:

 

 

     For each option (for each potential product, whether it is old or new, existing in the mind or in reality), designers use all available information (from all experiments, old and new, mental and physical) to evaluate this product by comparing goals with predictions (to produce predictive feedback) and comparing goals with observations (to produce empirical feedback) for the purpose of assigning an intrinsic status that is an estimate of the extent to which this option achieves the desired goals.  Usually there is a competition between different options, so a relative status (an estimate for the quality of a particular option with respect to other options) is also assigned.

    Based on their estimates of status, designers can make several types of decisions.
    solution:  They may decide that one option (or combination of options) is sufficiently satisfactory, so they consider the problem to be solved.  { But a "solution" decision often leads to a new phase of problem solving related to the old problem, such as deciding how to acquire or produce the product(s), or how to market, distribute, and sell. }
    continue:  Or they may try to develop a product that is even more satisfactory, with continuing action in the SEARCH, IMAGINE, and TEST modes.  Perhaps the evaluation process has narrowed the focus of "research and development" to revising a few key aspects of a few products that seem especially promising.  Or there may be an effort to search for new options, or to generate more information about known options.
    abandon:  Maybe things are not going well and they abandon the search for a solution because progress has been slow, or because despite satisfactory progress they decide that working on another project is likely to be more productive.
    delay:  Or they can abandon the process of R & D temporarily, intending to return later, so they can work on other projects for awhile.  Or perhaps a delay will be productive without an investment of their own time and effort.  This could occur, for example, if at a later time they will be able to use information or supplementary technology that in the future will be available due to the work of others.
    settle:  Sometimes, however, an immediate decision is required even though none of the available options is totally satisfactory, so they "settle for less" and choose the best available option, if this is better than a delay.  Or perhaps, even if an immediate decision isn't absolutely necessary, a delay would cause significant disadvantages.   { When it seems wise to make a quick decision, even though evaluation indicates that only a conclusion of "inconclusive" is warranted, maybe they can make the decision in a way that takes into account the uncertainties. }
    re-aim:  Based on what they have learned during the process of R & D, they may decide to modify the goal-state.  Maybe their original goals now seem impractical and too difficult to achieve, so the standards for a satisfactory product are lowered and they are willing to settle for less.  Or the standards can be raised (or changed) if they have recognized or invented new possibilities for a product with characteristics that are better (or just different) than what they initially could imagine.  Or perhaps, based on revised estimates of relative importance, there is a change in the "weighting emphasis" for different types of evaluation criteria, which leads to revised strategies for achieving an optimal balance between conflicting criteria.
    diversify:  But designers aren't limited to only revising old goals.  They can also define new goals that lead to new "spinoff" projects.

    As discussed above, many results of evaluation involve not just the product, but also decisions about action, about "what to do next."  This important aspect of design is discussed later, in The Generation and Evaluation of Actions.


    4. THEORIZE
    In a step that is optional -- that is not necessary when developing a product, but is often helpful -- a designer evaluates a theory by comparing predictions with observations to produce hypothetico-deductive feedback.  This reality check is the key step in theory evaluation, in deciding whether "the way things are according to a theory (and its predictions)" match "the way things really are (as indicated by observations)."

 

 

 
     If what you think should happen (your predictions) is not the same as what actually happens (your observations) there is a mystery to be solved.  A mismatch could be due to a variety of causes, ranging from inaccurate observations to sloppy logic, and including the possibility that a faulty theory is being used to make predictions.  If a designer decides that a theory should be revised, this change can affect any future action in the IMAGINING mode, such as generating ideas for products, designing experiments, and doing mental experiments.   { What follows now is the "under construction" part of this page. }
 
 

 
 

 

 
     A ROUGH-DRAFT SUMMARY BEGINS HERE:
    At this time I've decided to work on other projects, so I'll just describe what eventually will be in this page.  There will be minor revisions (as described later) and six end-of-page sections, briefly outlined below:

    Science and Design:  This will flow naturally from the THEORIZING mode.  And it will be an extension of a discussion that begins on the "Introduction to Design" page, which:  1) makes a distinction between the designing of products or strategies (which I'll call "design") and the designing of theories (which I'll call "science");  2) discusses some similarities and differences between engineering [as one type of design] and science;  3) suggests that it may be useful to consider one type of comparison (of predictions with observations) as being a useful form of feedback in science, while two other comparisons (of predictions with goals, or observations with goals) are useful for feedback in design, as shown below:
 

 

 

    The Design of Strategies:  As described at the beginning of the "Introduction to Design" page, strategies can be designed for a wide variety of situations, ranging from business to basketball, from romance to public policy.  Although in all of the previous descriptions of IDM the focus has been restricted to products in order to increase the clarity and to minimize the need for awkward phrases like "product and/or strategy," most of the action that occurs when designing products also applies to the design of strategies.  Just replace each reference to "product" with "strategy" and you'll see that the design process is very similar for products and strategies.  But there are some differences, such as a shift, when predicting or observing, from characteristics (of products) to consequences (of strategies).  This section will examine the differences and the similarities between a process of design for products and for strategies.

    Generating and Evaluating Actions:  A strategy can be the overall objective of design, as in the previous section.  But strategy planning also occurs within the process of design when -- guided by feedback that enhances their awareness of differences between the current state and goal state, and perhaps constrained by the limitations of deadlines and budgets -- designers generate, evaluate, and execute actions that will help them make progress toward solving their problem.  Strategies for action begin during problem formulation.  Later, during the process of design, these preliminary plans can be modified by improvised planning.

    Modes of Action:  This will expand the earlier discussion about interactions between modes (with problem recognition requiring action in the modes of searching, imagining, evaluating, and defining goals) and will extend it to other interactions.

    Actions and Methods:  This section, which is especially important for education, will explore the relationships between methods for problem solving (such as those summarized in IDM) and the thinking actions (such as various applications of creative and critical thinking) that are used in problem solving.  We'll look at some actions, plus different perspectives on the relationships between methods and actions.

    Enriching IDM:  IDM can be supplemented with ideas from ISM -- such as cultural-personal factors, thought styles, conceptual factors, and more -- to produce an enriched model of IDM.  Even though IDM is simpler than ISM, design is not simpler than science, so enrichment is appropriate and useful.


    Also, there will be minor revisions in Section 3 -- mainly by adding an "evaluation analysis" grid that has options on one axis, criteria [weighted for importance] on another axis, and evaluations in the cells) -- and Section 4 (with miscellaneous comments), and in a few other places.