How have you applied data analytics skills to identify and solve a complex business problem?

This question is asking you to draw on your past experiences where you have utilized data analytics to resolve complex problems within a business context. The interviewer is essentially seeking a demonstration of your problem-solving skills alongside your proficiency in data analytics. Your response should include:

1. The complexity and the importance of the problem you sought to solve.
2. The specific data analytics techniques or tools you employed to address the issue.
3. The process you followed in analyzing the data and implementing the solution.
4. The final outcome and the impact it had on the business.

In my previous role as a business analyst at XYZ Company, we faced issues with increasing customer churn rate. I applied data analytics to identify patterns and reasons behind it. I first gathered data on customer interactions, product usage, engagement levels, and customer feedback. Next, I used data analytics tools like SQL for data extraction and Python libraries like Pandas for data processing and hypothesis testing. Through my analysis, I detected that customers who frequently contacted our customer service were the ones most likely to leave. Based on this insight, we implemented a proactive customer service approach, reaching out to customers before they experienced major issues. Consequently, we were able to decrease the churn rate by 15% within six months.

In my role as a supply chain analyst at ABC Corporation, we were faced with significant inventory management problems leading to stockouts and overstock. To resolve this issue, I initiated a demand forecasting project. The data used included historical sales data, industry trends, and seasonal patterns, which I analyzed using time-series analysis and machine learning methods in R. I also employed visualization tools, like Tableau, to illustrate my findings to the team more clearly. The sophisticated forecast model improved the accuracy of our predictions by about 30% and allowed us to manage our inventory more effectively. As a result, we reduced stockouts by 25% and saved about 10% on inventory holding costs over one year.