Introduction

In today’s fast-moving digital landscape, businesses must embrace data-driven decision-making to stay competitive. PwC’s Digital Accelerator Programme is designed to equip professionals with cutting-edge skills in automation, machine learning, and data visualization—key components in transforming business operations. As part of this initiative, Power BI plays a crucial role in turning raw data into actionable insights, enabling companies to work smarter, faster, and more innovatively.

I recently completed a job simulation inspired by this program, where I defined key performance indicators (KPIs) and leveraged Power BI to analyze business data across various real-world scenarios for a telecom business. This included evaluating call center staff performance, analyzing customer retention and churn, and assessing diversity and inclusion metrics within the HR department. Through this experience, I had the opportunity to design dynamic dashboards, uncover meaningful insights, and translate data into actionable strategies—enhancing both business efficiency and decision-making.

Implementation

The program consists of three tasks across different business domains, each requiring carefully tailored KPIs to extract meaningful insights. Despite completing the program within two weeks due to time constraints, I noticed significant improvement in the organization and clarity of my visualizations over time. With each task, I reflected on my approach, identified areas for enhancement, and applied those learnings—resulting in more insightful and well-structured dashboards.

Task 1: Call Center Staff Performance Analysis

The above mail is sent from the Call Centre Manager at PhoneNow. You can check the dataset here.

Possible KPIs include:

• Overall customer satisfaction
• Overall calls answered/abandoned
• Calls by time
• Average speed of answer
• Agent’s performance quadrant -> average handle time (talk duration) vs calls answered

Link to the dashboard: here.

Reflection After the Task: While the dashboard effectively presents insights based on the identified KPIs, there is room for improvement in terms of organization and impact. Enhancing chart selection and clarity can make the visualizations more intuitive and actionable. Some charts currently display excessive information, leading to visual clutter and reduced readability. Moving forward, a more focused and structured approach to data visualization will help ensure that key insights are presented in a clear and compelling manner.

Task 2: Customer Retention Analysis

This task focuses on analyzing customer retention trends. You can access the dataset here.

Link to the dashboard: here.

Key Findings

• Overall Churn Rate: Over the past few months, 26.5% of customers (1,869 out of 7,043) have churned.
• Tenure Impact: Customers with longer tenure are less likely to churn. The highest churn rate (54%) was observed among customers with a tenure of 0–6 months.
• Contract Type Influence: Month-to-month contracts had the highest churn rate (42.7%), followed by one-year and two-year contracts, aligning with the tenure trend.
• Service Type Effect: Customers using Streaming TV and Streaming Movies had the highest churn rates (around 30%), while those subscribed to Tech Support and Online Security services had significantly lower churn rates (around 15%).
• Support Ticket Trends: Retained customers predominantly submitted administrative tickets, whereas churned customers frequently reported technical issues—suggesting that technical difficulties were a major driver of churn.
• Payment Method Impact: Customers using Electronic Check had the highest churn rate (45%), significantly higher than other payment methods. -Demographic Factor: Senior customers exhibited a significantly higher churn rate (41%) compared to their younger counterparts (23.6%).

Reflection after the Task: The dashboard this time provides a clearer, more structured narrative around customer retention trends. By reducing clutter and improving data storytelling, the insights are now more actionable and easier to interpret, helping identify key factors driving customer churn.

Task 3: Diversity & Inclusion Analysis

This task requires analysis on diversity and inclusion for an HR department. They’ve been working hard to improve gender balance at the executive management level, but they’re not seeing any progress. You can access the dataset here.

Link to the dashboard: here.

Key Findings:

• Overall, The gender gap has been narrowing in recent years, as seen in the Genders by Tenure Year chart, reflecting HR’s efforts to improve balance. The pie chart also supports this idea where nearly 50% of new hires are woman.
• Despite progress, men still make up nearly 60% of all employees, with no women at all in the 60-69 age group.
• This can be explained by the fact that most important roles within the company (senior, manager, director, executive) are dominated by man, while women are only overrepresented in junior positions.
• Additionally, in FY21, only 35% of women were promoted, despite their performance ratings being nearly equal to men’s (2.26 vs. 2.31). This suggests a potential bias in promotion decisions.
• For these reasons, women leave the company at a much higher rate than men, particularly in the 50-59 age group, where the turnover rate approaches 80%.

Recommendations:

• Increase women’s representation in leadership roles through mentorship, sponsorship, and targeted promotions.
• Ensure fair career advancement by addressing potential biases in promotion decisions.
• Improve retention strategies for female employees, particularly in mid-to-senior roles.

Reflection after the Task: This dashboard effectively uncovers the barriers to gender balance in leadership, combining hiring, promotion, and retention insights. The improved structure and visualization clarity enhanced storytelling and decision-making.

Conclusion

This project provided a comprehensive analysis across multiple business domains, demonstrating the power of data-driven decision-making using Power BI. Through three key tasks—Call Center Performance, Customer Retention, and Diversity & Inclusion Analysis—I gained valuable experience in defining KPIs, building interactive dashboards, and extracting meaningful insights to support strategic decision-making.

Beyond the technical aspects, this project strengthened my problem-solving skills and business acumen, reinforcing how data analytics can drive real impact in various industries. Moving forward, I am excited to further enhance my Power BI expertise and apply these skills to even more complex and dynamic business challenges.