Employability Skills For The Future Part 2: Complex Problem Solving

By Andrew Hopkins

With automation edging its way into the core of many industries there is no denying that AI is a future that awaits us all. In the coming years, machines will be doing increasing amounts of manual and specialised work; and this means that humans will either need to adapt or retrain to find new careers. In fact, it is estimated that 50% of all employees will need reskilling by 2025.

We have already looked at how creativity and creative thinking will be one of the top professional skills sought after by future employers, next up is complex problem solving.

Why is complex problem solving so important for the future?

With the rise in automation comes the ever-increasing necessity for us to develop more soft skills. This means that humans need to develop competencies that machines can’t grasp.

Unlike machines, we have the ability to perceive different implicit factors and think outside the box when it comes to problem solving. We can take into account emotions such as empathy, interpersonal sensitivity, ethics, and morality, and these are elements of decision making that machines are incapable of discerning.

Having an awareness of these factors will make complex problem solving one of the most sought-after employability skills for the future workforce.

What is complex problem solving (CPS)?

Artificial Intelligence has advanced to solve many problems and complexities as well as humans can. AI can recognise some emotions, make predictions, uncover illnesses but, if a problem is not well-defined or set within the parameters that the machine can comprehend, then the efficiency of the system breaks down or fails altogether.

Machines are most effectual in problem-solving situations which involve choosing predetermined actions dictated by standard procedures.

However not all problems can be solved using pre-set patterns or configurations. The majority of problems are intricate scenarios that require detailed and bespoke solutions.

How is complex problem solving different from a simple problem?

A simple problem has a clear cause and effect that is easily identifiable and fixable. A complex problem often has multiple causes, some of which are easy to identify, while others may be hidden. Unravelling this spiderweb of causes to solve a problem is where the complexity lies.

What are the four steps to complex problem solving?

  1. Define the problem: what is the goal you’re trying to achieve? What’s stopping you from getting the result you want?
  2. Identify various solutions: Think outside the box and visualise several possible scenarios on how to tackle the issue. What are the possible outcomes?
  3. Choose a plan: Evaluate your ideas and disregard possible solutions which are unfeasible or don’t match your resources or abilities.
  4. Implement the idea: apply the chosen solution and assess the outcome to see if the results align with your goals. If not, try an alternative scenario.