The 7 steps to problem-solving is a disciplined and methodical approach to identifying and then addressing the root cause of problems. Instead, a more robust approach involves working through a problem using the hypothesis-driven framework of the scientific method. Each viable hypothesis is tested using a range of specific diagnostics and then recommendations are made.
- Understanding the 7 steps to problem-solving
- Moving through the 7 steps to problem-solving
- Key takeaways
- Connected Decision-Making Frameworks
Understanding the 7 steps to problem-solving
The core argument of this approach is that the most obvious solutions to a problem are often not the best solutions.
Good problem-solving in business is a skill that must be learned. Businesses that are adept at problem-solving take responsibility for their own decisions and have courage and confidence in their convictions. Ultimately, this removes doubt which can impede the growth of businesses and indeed employees alike.
Moving through the 7 steps to problem-solving
Although many versions of the 7-step approach exist, the McKinsey approach is the most widely used in business settings. Here is how decision makers can move through each of the steps systematically.
Step 1 – Define the problem
First, the scope and extent of the problem must be identified. Actions and behaviors of individuals must be the focus – instead of a focus on the individuals themselves. Whatever the case, the problem must be clearly defined and be universally accepted by all relevant parties.
Step 2 – Disaggregate the problem
In the second step, break down the problem (challenge) into smaller parts using logic trees and develop an early hypothesis. Here, economic and scientific principles can be useful in brainstorming potential solutions. Avoid cognitive biases, such as deciding that a previous solution should be used again because it worked last time.
Step 3 – Prioritize issues
Which constituent parts could be key driving factors of the problem? Prioritize each according to those which have the biggest impact on the problem. Eliminate parts that have negligible impact. This step helps businesses use their resources wisely.
Step 4 – Plan the analyses
Before testing each hypothesis, develop a work and process plan for each. Staff should be assigned to analytical tasks with unique output and completion dates. Hypothesis testing should also be reviewed at regular intervals to measure viability and adjust strategies accordingly.
Step 5 – Conduct the analyses
In step five, gather the critical data required to accept or reject each hypothesis. Data analysis methods will vary according to the nature of the project, but each business must understand the reasons for implementing specific methods. In question-based problem solving, the Five Whys or Fishbone method may be used. More complicated problems may require the use of statistical analysis. In any case, this is often the longest and most complex step of the process.
Step 6 – Synthesise the results
Once the results have been determined, they must be synthesized in such a way that they can be tested for validity and logic. In a business context, assess the implications of the findings for a business moving forward. Does it solve the problem?
Step 7 – Communicate
In the final step, the business must present the solutions in such a way that they link back to the original problem statement. When presenting to clients, this is vital. It shows that the business understands the problem and has a solution supported by facts or hard data. Above all, the data should be woven into a convincing story that ends with recommendations for future action.
- 7 steps to problem-solving is a methodical approach to problem-solving based on the scientific method.
- Although a somewhat rigorous approach, the strategy can be learned by any business willing to devote the time and resources.
- Fundamentally, the 7 steps to problem-solving method involves formulating and then testing hypotheses. Through the process of elimination, a business can narrow its focus to the likely root cause of a problem.
Connected Decision-Making Frameworks
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