Business Problem Solving Process

The first challenge in problem-solving is engaging a team to be interested in someone else’s problem. A curious team will dissect the problem, separating actual issues from noise. However, not everyone recognises or is interested in all problems, necessitating motivation to foster problem-solving efforts.

Three psychosocial risks—anxiety, conformity, and ambiguity—impair interest. Anxious individuals focus on their issues, not the team’s problem. Conformity leads people to feign interest, possibly applying their skills half-heartedly or misidentifying problems, diverting efforts in the wrong direction. Ambiguity through poor communication obscures genuine interest, potentially placing the wrong people on the problem-solving team.

Effective leaders mitigate these risks, ensuring their teams are genuinely interested and motivated. This requires creating an environment where individuals feel secure, are encouraged to voice genuine concerns, and have clear communication channels.

The third step of effective problem-solving is knowledge. Epistemology, the study of knowledge and its acquisition, underscores the significance of selecting the appropriate systems for problem understanding. Qualitative methods value descriptive data in research, while quantitative methods value numerical data. Choosing the right system for the situation is crucial in accurate problem-solving, much like using the right tool for a specific task.

A significant challenge lies in navigating the "knowns and unknowns," a concept used by NASA and represented in the Johari Window and Rumsfeld Matrix. Businesses face four categories: known-knowns, Information the business is aware it possesses; unknown-knowns, Information individuals have, but the business is unaware of; known-unknowns, Information the business knows it lacks; and Unknown-unknowns, Information the business is unaware it lacks, uncovered by exploring the other categories.

Ambiguity and anxiety are significant psychosocial risks to knowledge. Ambiguity blurs the lines between known and unknown, while anxiety shifts focus away from relevant knowns to worrying about unknowns. These risks reduce the clarity and accuracy of knowledge, leading to poor solutions and outcomes.

Effective leaders minimise ambiguity and anxiety and enhance their team's ability to operate on accurate knowledge, leading to better problem-solving and commercial success.

The fifth step in effective business problem-solving and the first step in the solution-choosing process is discussion. Effective teams create a safe space for differing opinions, which is essential for healthy debate. This open debate allows for a thorough exploration of the various options generated from understanding the problem. Key questions to consider include: How was this option developed? What are its pros and cons? Who benefits or is disadvantaged? What if we do the opposite? What evidence supports this option as the best choice?

Three major risks to effective discussion are anxiety, ambiguity, and conformity. Anxious teams may focus on options that lower their anxiety rather than solving the problem, akin to rearranging deck chairs on the Titanic. Ambiguity disrupts discussions by creating unclear questions and risky unknowns. Conformity stifles honest debate due to fear of retribution or reputational damage, preventing team members from voicing concerns or advocating for better options. Recognizing and addressing these risks is key to maintaining a healthy decision-making process.

Effective leaders mitigate these risks to ensure robust discussions. This enables the team to explore all options thoroughly and select the most effective solution based on comprehensive knowledge and diverse perspectives. This approach fosters innovation and leads to better problem-solving outcomes.

The seventh step in effective business problem-solving is planning. Effective planning begins with setting clear objectives and targets for inputs and outputs. Input planning determines the required activities, time, money, resources, and personnel. Output planning develops a balanced scorecard with metrics like revenue, profit, market share, customer satisfaction, employee engagement, and risk tolerance.

With these elements defined, a comprehensive plan outlines what will be done, who will do it, how, where, when, and how often. Considerations include potential conflicts with existing projects and scenarios based on market conditions, customer confidence, and supply-chain dynamics.

Planning methods vary: decisions might be democratic, leader-driven, or involve inter-team coordination. The key is to ensure all teams work with the same assumptions, fostering a sense of unity and collaboration, as illustrated by NASA’s metric-imperial measurement mix-up.

Psychosocial risks to effective planning include ambiguity, anxiety, and conformity. Ambiguity leads to poor execution; thus, clarity is essential. Anxiety about deadlines or capabilities diverts focus from execution to worry. Conformity results in false agreement, leading to uncoordinated execution.

An effective leader addresses these risks and allows for precise, coordinated, and effective plan execution by ensuring genuine agreement and understanding within the team.

Evaluating something means measuring it. The 'something' you measure can vary - the share price, purchases, or profit. You can measure nearly anything, but measuring and validity are different. Accurately measuring means constantly comparing - even if you are only measuring one thing, you are still comparing it to something else, which is where it gets complicated. You need to know which one you are using. Otherwise, you might crash a spaceship into Mars if one team uses centimetres and another uses inches (as NASA once discovered, fortunately, before any catastrophic consequences came to pass).

Ambiguity and conformity are significant psychosocial risks at the evaluation stage of problem-solving. Suppose there is ambiguity on what is being evaluated, how it is being evaluated, or what counts as success or failure. In that case, it is nearly impossible to give an accurate evaluation. Similarly, suppose stakeholders agree it worked or is okay when it is not. In that case, the evaluation stage becomes meaningless, and it remains to be seen if success is achieved or if further iteration would be valuable.

Getting the evaluation right is critical, primarily because getting it wrong has compounding negative consequences. Evaluation guides the next iteration of the problem-solving process. Is it the original solution to the problem that needs more work? Or has the original problem been solved, and now it’s about scaling the solution? If the wrong measures and tools have been chosen to evaluate the process, and the result is meaningless, then the next iteration will likely compound the meaninglessness. This is why the question “Did it work?” is critical to businesses, which are at their core iterative problem-solving machines.