Business intelligence (BI) professionals face complex and dynamic problems that require effective and efficient solutions. How can they approach these problems in a systematic and structured way? In this article, we will explore some of the best problem solving methodologies for BI professionals, and how they can help them achieve better results and insights.
The first step in any problem solving process is to clearly define the problem and its scope. This means identifying the root cause, the desired outcome, the stakeholders, the constraints, and the assumptions of the problem. A well-defined problem helps to focus the analysis, avoid unnecessary work, and communicate the problem to others. Some tools that can help to define the problem are the 5 Whys, the problem statement, and the fishbone diagram.
The best problem-solving methodologies for BI professionals include defining clear objectives, gathering and analyzing relevant data, utilizing statistical and data visualization techniques, and collaborating with stakeholders to ensure actionable insights.
Often while defining a problem it is always beneficial to categorize the nature of the problem like business vs technical and evaluate the value addition to the problem being addressed.
The next step is to gather and prepare the data that is relevant and reliable for the problem. This means finding the data sources, accessing and extracting the data, cleaning and validating the data, and transforming and integrating the data. Data quality and completeness are crucial for the accuracy and validity of the analysis. Some tools that can help to gather and prepare data are the data inventory, the data dictionary, the ETL process, and the data quality checklist.
The third step is to analyze the data and generate insights that can help to solve the problem. This means applying various techniques and methods to explore, visualize, model, and test the data, and finding patterns, trends, correlations, and anomalies that can answer the problem questions. Data analysis requires creativity, critical thinking, and domain knowledge. Some tools that can help to analyze data are the analytical framework, the dashboard, the statistical model, and the hypothesis test.
The final step is to communicate the results and recommendations that can help to solve the problem. This means presenting the findings, the evidence, the implications, and the actions in a clear, concise, and compelling way, and engaging the audience, the decision makers, and the stakeholders. Communication skills and storytelling are essential for the impact and influence of the analysis. Some tools that can help to communicate results are the report, the slide deck, the infographic, and the story.
A problem solving process is not a one-time event, but a continuous cycle that requires adaptation and improvement based on feedback and evaluation. This means monitoring and measuring the outcomes, the performance, and the satisfaction of the solution, and identifying and addressing any gaps, issues, or opportunities that arise. Feedback helps to refine the problem definition, the data quality, the analysis methods, and the communication strategies. Some tools that can help to adapt to feedback are the KPIs, the feedback survey, the A/B test, and the SWOT analysis.
When problem solving in BI, there is no single methodology that fits all, but there are several frameworks and models to guide and support the process. Popular methodologies include the CRISP-DM, a six-phase iterative process for data mining projects; the DMAIC, a five-phase structured process based on Six Sigma principles; and the OODA, a four-phase loop process for decision making in complex and uncertain situations. Each has its own advantages and disadvantages, so it is important to choose one that is consistent, transparent, and effective for the problem at hand.
In addition to these, there are also other frameworks and models that can be useful for BI professionals when problem solving. For instance, the Kepner-Tregoe method is a problem-solving framework that helps to break down complex problems into smaller, more manageable parts. The 5 Whys technique is another approach that involves asking "why" five times to identify the root cause of a problem.