Our current age seems to be increasingly characterised by an overwhelming preference for getting to an answer QUICKLY. This shows up across the entire spectrum from “thought shower” problem-solving popularised in business, to the relatively more disciplined Minimum Viable Product (MVP) methodology commonly applied to IT product development.
When faced though with truly complex challenges, the ability to systematically work through a problem and come to a well-reasoned answer remains a truly valuable capability.
So how do professional problem-solvers such as designers, engineers and management consultants go about their craft?
The answer lies in the concept of “design thinking” – a paradigm for dealing with the complex problems that increasingly challenge businesses with expanding interactions with clients and customers, suppliers, competitors, stakeholders and regulators.
We can gain some insight into the core of what is itself a rich and complex process with the help of “The core of ‘design thinking’ and its application” by Kees Dorst of UTS Sydney, kindly sent to me by a colleague.
In gaining an understanding of what design thinking is, we can start with three basic ways in which we apply reasoning in logical thought:
- Deductive Reasoning
- Inductive Reasoning; and
- Abductive Reasoning
Let’s consider the following simple equation:
What + How = Result
If we know the What (for instance an object such as a soccer ball) and the How (external energy is required to make it move in a certain direction) we can predict the result when we kick the ball in the right direction (it will end up in the goal!). This thinking process is known as “deduction”.
Alternatively, “inductive” reasoning applies when we know the What and the Result in our equation but not the How. In the case of our soccer example, by observing and experimenting we can determine the process by which the soccer ball might be kicked in order to end up in the goal.
In more scientific language, we apply inductive reasoning in a “discovery” phase when developing a hypothesis for the Result (soccer ball in the goal) and in a “justification” phase we apply deductive reasoning by subjecting the hypothesis to critical tests (such as propelling the soccer ball in the general direction of the goal multiple times) with a view to dis-proving the hypothesis if possible (maybe external factors such as the wind and the goalie’s efforts need to be taken into account?)
Let’s consider what happens when we change the outcome of our simple equation from a Result to the attainment of Value:
What + How = Value
In this circumstance a reasoning pattern known as “abduction” (loosely known as inference) comes into play. Basically, it involves forming a conclusion from known information. Abductive reasoning is applicable to simple as well as complex circumstances.
With simple abduction – as is typically the case with problems that are routinely solved by designers and engineers – the How (the working principle) associated with the problem is understood and the Value is well defined. An experienced goal scorer is hired for an elite soccer team, based on the potential Value (more wins) but without knowing exactly how the new recruit might gel in the team environment.
Complex Problem Solving
But what if the What and the How are unknown and we only loosely know the end Value we want to achieve? This is where more complex abduction applies.
One key creative activity out of a wide array of design practices associated with complex abduction is known as Framing. In essence the problem is considered from a specific viewpoint whilst adopting a given working principle, in determining whether the result generates the desired value.
Framing itself becomes more complex when faced with paradoxical, conflicting requirements. However, judicious application of framing enables systematic analysis of a problem and identification of a range of potentially satisfactory or – better – innovative solutions.
Once a potential solution has been determined via complex abduction, deductive thinking is applied in qualifying/proving the potential approach.
Relatively more inexperienced designers and problem-solvers are tempted to apply adduction in a random manner. More experienced practitioners apply a logical methodology and can draw upon a wider body of experience, in identifying potential options that might solve the problem at hand.
Another key element in complex problem-solving concerns problem definition.
McKinsey alumni Charles Conn and Robert McLean recently published “Bulletproof Problem-solving”. Their book explores the standardised methodology by which McKinsey & Company, as the “go-to” organisation for high-end management consulting services, approach complex problem solving for their clients.
Without divulging the full methodology here, businesses can significantly improve their problem-solving capability just by adopting a more rigorous approach to defining the problem needing to be solved. The diagram below outlines the process McKinsey typically apply in this regard.
Diagram Acknowledgement: Charles Conn & Robert McLean
This one step mitigates the natural tendency of designers, engineers and others with logically oriented thought processes to dive into “problem-solving” mode before fully understanding the problem at hand.