Design involves choices – not all are equal

Observe>Interpret>DESIGN>Experiment>Whenever we create something to achieve a purpose or objective, we are designing. In the context of Adaptive Iteration we are interested in designs that need to achieve their objectives in situations that are uncertain, unpredictable and emergent. In these situations the scope and complexity of the interactions are such that we cannot predict all the cause and effect relationships in advance. Not only are they complex, but they are also changing dynamically and are likely to change further in response to the introduction of our design.

The types of situations that require this type of emergent design include business plans and strategies, organizational change initiatives, new product development, new market entry, career development and organizational development. In other words, almost any situation that is forward looking and involves interactions of people or groups of people whose decisions will influence the outcome.

Designing involves choices. There is no one right design. The design choices will determine the extent to which the design meet its objectives. If the design context is uncertain, unpredictable and emergent, the best design choices are not at all clear. For example, we cannot be certain how customers or competitors will react to a new set of product features. Can we be confident that our new social media strategy will attract sufficient attention from our target markets? It may not be clear what coaching and training to give to our middle-managers to ensure that they can make the transition to our new project-based organizational structure?

How do we make these choices? If we use the Adaptive Iteration approach we do not have to be ‘right first time’. With Adaptive Iteration, we form hypotheses about the best design choices and then conduct low risk experiments to assess how those choices work in practice. We use the resultant observations and interpretations to refine the design choices (hypotheses) that we again test experimentally, and so on. By starting small with low risk and iterating rapidly, we home in on the best design to meet our objectives in the particular context.

However, in Adaptive Iteration, our initial design choices (hypotheses) are not random. Foundational design choices set the relatively stable core of the design on which choices about the design detail are made and adaptively iterated.  The foundational design choices are not unchangeable during Adaptive Iteration but will change much less frequently than choices about the design details.  A significant shift in any of the foundational design choices should stimulate a major rethink of the overall design. The foundational choices, in general order of significance are:

Objective:  The objective describes the intent of the design, and of the associated Adaptive Iteration, and forms the key anchor for all other design choices.  All other design choices must enable the design to achieve its objective.  The clearer the design objective, the more likely that Adaptive Iteration will proceed efficiently and effectively.  It is important to select an objective that does not implicitly constrain the design options.  In my blog post that summarized the start up stories of HP, Sony and Microsoft we saw that the objective of each of the founders was to create a profitable business based on their particular expertise and interests, rather than create a business in any particular product/market segment.  The founders of each company adaptively iterated the product/market segment until they found one that met their design objective.

Boundaries/Constraints:  The boundaries and constraints can apply to any aspect of the design. They set the scope of design variables (choices) available to the designers.  They also set any limits to or targets for the performance of the design, and they set the context within which the design sits.  In some cases, tight design constraints can stimulate focus and can help challenge the status quo. For example, a design constraint that requires that the manufactured cost of a product design be 20% less than its predecessor is likely stimulate new a search for new perspectives and step-change ideas.  In other cases, widening the design boundaries may create the scope to develop more systemic and more fundamental design improvements.  Roger Martin provides a good example of this in his book Opposable Mind where he describes how IDEO recognized that its design brief from Amtrak (redesign their railcar) was inherently limiting and convinced Amtrak that, to achieve its design objectives, it needed to look at the end-to-end train ride experience.

Architecture/Game plan:  The architecture or framework of a design will usually have a significant impact on our ability to adaptively iterate the design.  Key decisions include how much operating flexibility and how much modularity to build into the design.  For example, an organizational design that is based on a strong and commonly held set of operating values and principles will empower employees to use their discretion to meet customer needs as long as what they do is consistent with those values and principles.  On the other hand, employees in an organization that emphasizes rules and procedures will be constrained to only the situations and responses anticipated by those rules and procedures.  The nature and extent of modularity will influence the ability to adaptively iterate the design.  Coarse-grained modularity will constrain design changes to large steps (changing one or more of the coarse grain modules), whereas fine-grained modularity provides much more flexibility but may lead to costly customization and integration of the design after each adaptive iteration. Ideally we want to align coarse-grained modules with any relative stable aspects of the context and use finer-grained modules for those aspects of the context that are uncertain, unpredictable and emergent.

Metaphor:  Use of a design metaphor can help unify a design by stimulating coherence for the myriad of detailed design choices.  It can help create a distinct personality for the design and stimulate a positive emotional response from the user.  A metaphor can also help identify the mix of design features that will create both functional and emotional coherence for the design.  It can help overcome the tendency to load a design up with all manner of features and capabilities “just because we can”.  For example, a metaphor may assist the redesign of an under performing group or small organization.  Depending on the situation and objectives, the group could use the metaphor of a sporting team, an orchestra, a jazz ensemble, an operating theatre, improvisation theatre, etc.

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