The Top 3 Essential Questions for Interviewing a Stakeholder for Their Current Analytic Needs
The first and foremost question to ask is: 'What problem or problems are you trying to solve?' This pivotal inquiry not only sets the stage for your work but also aids in discerning the stakeholder's primary concerns or priorities. Understanding the core issues at hand is essential for aligning your efforts effectively and ensuring that you address the most pressing needs first.
How do you align your analytics strategy with your overall business objectives?
This question delves into how the business integrates analytics into its core strategic planning. The answer can reveal the extent to which the business values data-driven decision-making and whether its analytics initiatives are geared towards solving real business problems or merely exist as isolated projects. Look for insights into how analytics priorities are set, how cross-functional collaboration is fostered to meet those objectives, and examples of strategic outcomes achieved through analytics.
Can you describe a recent challenge your business faced where analytics played a key role in addressing it?
Asking for a specific case where analytics made a difference allows you to assess the practical application and impact of the business's analytics capabilities. It provides a window into the company's problem-solving approach, the sophistication of its analytics solutions (from data collection to analysis and implementation), and how results are measured and evaluated. The response should give you a sense of the company's agility, innovation, and effectiveness in using analytics to overcome obstacles and capitalize on opportunities.
How do you ensure the quality and integrity of your data?
This question is critical because the value of analytics is deeply dependent on the quality of data. Understanding the mechanisms in place for data governance, quality control, and security practices sheds light on the company's maturity in managing its data assets. Look for specifics on data collection processes, validation, cleaning practices, and how they address data privacy and ethical considerations. A strong system for ensuring data quality and integrity indicates a company that takes its analytical capabilities seriously.
