Solution space is abstract, multi-dimensional and non-convex. The space contains known and partially explored optimum solutions, which are illustrated here as hilltops. Areas of solution space are inaccessible to us, either because someone else have established the Intellectual Property Rights to it or because it represents a ‘void’ in our own design or production capabilities – i.e. the solution depends on a materials or technique that is outside our organisation’s skills set.
An optimum, and the space around it, can move, grow or shrink in ways that are not always easy to predict. For example, customer desires can change, and thereby reduce the value of an optimum. A new related discovery or a sudden safety concern can completely destroy an otherwise established optimum.
In our design process, we set our eyes on a partially optimised solution that we judge to be effective in meeting market needs and is within our capabilities. Once we have committed to our solution, we start a metaphorical hill-climb to get us as high up the optimum as we can get, within the project time and resources that we have available to us. Invariably, as project time progresses and new learning emerges, we will experience the hilltop to have evolved or moved slightly before we get to it. The direction of the design optimisation hill-climb is therefore likely to occasionally require a compensating directional change.
Choosing a static, well-known optimum solution may represent an easier climb, but it would typically also represent a static or declining commercial potential. An emerging, moving or growing optimum can have significantly more potential, but will also require greater climbing efforts and risk.
We have to be mindful about a number of wasteful navigational errors that can be made in solution space:
- Choosing a wrong target solution that has less commercial potential than another optimum in the same space. Once we have started the hill-climb and made investment in a solution, it then becomes difficult to abandon it again. Sometimes, if we are unsure about our options, it can be justified to spend a little time wandering the solution space and make a few smaller exploratory climbs at different optima, to better appreciate their individual potential or difficulty. The learning from failures is often transferable.
- Choosing and developing a target solution, only to find out late that someone else has already claimed the rights to it. It is important to keep up to date with the patent situation in the field.
- Rigid early design specification, which does not allow the adaptable tracking of a moving optimum. When combined with a long project timeline, our final product may thereby completely miss its commercial potential – because the market moved on. Project plans need flexibility in accommodating unforeseen changes in the market and product functional requirements; but without making the project never-ending.
- Wandering into uncharted space and picking an optimum solution that stands within a knowledge or competencies void. To a commercial enterprise these voids are unpredictable ‘black holes’ sucking in excessive time and cost.
- Being too early in wandering into an emerging space. Picking an optimum that stands within a yet ‘demand void’ and producing something that customers are not yet ready for. Remember, what customers need and what they want are not always the same thing. Customers in the mass-market tend to have a short horizon-span, where they see their needs mainly in terms of what they already know.
- Inappropriate assumptions about the designer and production system capabilities. Make sure you are realistic about the prospect for attaining the necessary production capabilities for new technologies or fine design tolerances.
Successful navigation of solution space favours a systematic approach, such as Quality Function Deployment.