Call Center KPI Dashboard: Performance & Efficiency Monitoring

OBJECTIVE: Design a KPI dashboard for a call center help desk manager to monitor both team performance and overall operational efficiency. The dashboard provides clear, actionable insights while highlighting how individual agents and the team are performing both in real time and over time.

BACKGROUND: The manager wanted a flexible dashboard to understand:

1. Which agents are excelling or struggling?

2. How quickly calls are answered and resolved?

3. What issues generate the most call volume?

4. When does the call center experience peak demand?

The dashboard was designed around widely used industry KPIs to ensure long-term relevance and adaptability.

KEY QUESTIONS:

1. What is the current call volume, average talk time, and resolution rate?

2. Which agents are the most/least effective in resolving calls?

3. How quickly are calls answered on average by agent?

4. What are the most frequent call topics?

5. When are call volumes highest during the day and week?

6. How are customers rating their support experience?

TECH STACK:

1. Microsoft Excel: Used to preview and inspect raw data structure prior to import

2. Tableau Desktop: Interactive dashboard creation with calculated fields, parameters, and extract filters

3. KPI Logic & Visual Encoding: Conditional formatting applied to visually distinguish agent performance levels

4. Custom Color Coding: Conditional logic and color formatting used to highlight performance variations and distinguish top/low-performing agents

5. Data Transformation Techniques: Duration normalization (e.g., converting talk time to seconds), date parsing using DATEPART, categorical-to-numeric conversion (e.g., "Y" to 1 for resolution tracking), and agent-level aggregations using SUM, COUNT, and IF logic

PROCESS:

1. Data Cleaning:
   ◇ Transformed and structured raw data in Tableau to ensure consistency and enable accurate KPI analysis
   ◇ Mapped agent names, call topics, and time stamps to relevant KPI fields
   ◇ Aggregated metrics by daily, hourly, and monthly frequency

2. Dashboard Design in Tableau:
   ◇ Organized the dashboard into distinct sections: a real-time KPI snapshot (inbound calls and talk duration for the current day, overall monthly resolution rate), Agent KPIs, Volume Trends, and Customer Satisfaction
   ◇ Used color-coded tables to highlight above/below-average performance
   ◇ Implemented filters and auto-refresh to support flexibility in KPI selection
   ◇ Added bar charts to visualize volume by time of day, day of week, and call type

3. KPI Definitions:
   ◇ Avg Speed of Answer: Time in seconds taken to answer a call
   ◇ Resolution Rate: % of calls resolved out of total calls handled
   ◇ Unresolved Calls per Agent: Calls that required escalation or follow-up
   ◇ Customer Satisfaction Score: Distribution of post-call survey scores (1–5)
   ◇ Call Volume by Topic: Categorized by issue type (e.g., Tech, Admin)

KEY INSIGHTS:

1. Inbound Activity: 27 calls were handled for the current day, with an average talk time of ~3.9 minutes

2. Agent Standouts:
   ◇ Martha and Stewart had the highest resolution rates (78.7% and 76.6%)
   ◇ Martha, Greg, and Joe had the slowest answer times

   ◇ Martha and Jim had the highest amount of resolved calls (163 and 157)

   ◇ Dan had the most unresolved calls (80)

3. Call Topic Trends:
   ◇ Technical Support was the most common issue, followed by Admin and Payment

4. Peak Volume Patterns:
   ◇ Highest hourly volumes occurred between 1 PM – 4 PM
   ◇ Monday was the busiest call volume day of the week

5. Customer Feedback:
   ◇ Most users gave scores of 3 to 5, with 4 being the modal rating

CHALLENGES & SOLUTIONS:

⚠️ Challenge 1: The manager wasn’t sure which KPIs mattered most
✅ Solution: Researched standard call center metrics and built a flexible Tableau layout to support multiple KPI types

⚠️ Challenge 2: Raw data wasn't structured for time-based analysis
✅ Solution: Data structuring was handled in Tableau using calculated fields to prepare the dataset for KPI visualization, including time extraction, duration normalization, and categorical conversions.

⚠️ Challenge 3: Identifying underperforming agents visually
✅ Solution: Used Tableau color rules to highlight low-performing agents in red and top performers in green for clarity

DATA SOURCES:

• Dataset: Call Center Data.xlsx

• Source: Internal help desk call log

VIEW THE LIVE DASHBOARD:

Want to explore all the visualizations interactively?

👉 Click here to view the full Tableau dashboard — powered by Tableau and built to help call center managers monitor performance and efficiency in real time.

BEHIND THE DASHBOARD:

Curious how the dashboard was built?

👉 View the Tableau workbook (.twb) and full calculation logic — includes all calculated fields, data transformations, and layout structure used to create the dashboard.