KPI Analysis: How We Used Business Analytics to Optimize Our Performance


Industry: Financial Services  

Company: Asset Management Company

Company Description

The company is one of the leading Asset Management Companies of Pakistan managing USD 800 million in investment solutions like open-ended mutual funds, pension funds, and investment advisory portfolios.

Business Objective

The business objective of tracking key performance indicators (KPIs) involves using data analytics to analyze data on business operations and goals in order to identify patterns and trends. This can help to inform decision-making, optimize performance, and achieve business goals. By regularly tracking and analyzing KPIs, businesses can drive growth and success by maximizing the efficiency and effectiveness of their operations.

Business Challenge

The most essential employees in any company are the sales staff. They are primarily responsible for generating new business, retaining existing clients, and building the company’s reputation in the market. Therefore, it is crucial for any company to appropriately measure the performance of Sales Staff and reward them accordingly.

However, the company’s existing performance measurement structure only considered revenue, net sales and assets under management-based target achievement metrics and other factors of performance measurement were not considered. Therefore, the sales staff were not fairly rewarded for their overall performance.

In this regard, the BI team was commissioned to devise a mechanism for measuring sales staff performance based on a determined set of key performance indicators.

Available Data Points

The following key data points were available for analysis captured in the company’s Customer Relationship Management (CRM) system and Performance and Commission system.

Unique Identifiers:

  • Sales Staff Emp ID

Employee Details:

  • Emp Name
  • Designation, Grade
  • Gender, Age, Qualification

Professional Experience Details:

  • Tenure, Experience, Industry

Meeting Details:

  • Meeting ID, Meeting Date,
  • Meeting Details

Remuneration Details:

  • Salary, Commission


  • Sales Performance


The BI team developed a Key Performance Indicators model for determining Sales Staff performance.

Model Approach

To lay out the foundation of the model the following steps were taken:

  • Definitions, rules, and critical factors for performance measurement were laid out and defined
  • The weights assigned to each factor were determined and agreed upon with the stakeholders to calculate the overall performance percentage
  • A rating matrix based on the weight bands was developed to identify the final ratings of the sales staff and reporting managers

Key Performance Indicators

The following key factors were measured and assigned KPI weights to calculate the overall performance percentage and rating for sales staff and their reporting managers.

Sales Staff Key Performance Indicators (KPIs):

  • Direct Revenue Achievement against Target
  • Client Retention
  • Ethics
  • Sales Staff Cost

Reporting Managers’ Key Performance Indicators (KPIs):

  • Team Revenue Achievement against Target
  • Team Retail Revenue Achievement against Target
  • Team Institutional Revenue Achievement against Target
  • Team Growth
  • Team Productivity
  • Ethics
  • Sales Staff Cost

Model Ratings

The following ratings were assigned against each metric and for overall sales staff performance based on the weighted average KPI percentage calculated:

  • Excellent
  • Very Good
  • Good
  • Satisfactory
  • Poor

To implement the above model, the BI team used the published data sources scheduled for daily updates compiling data from multiple database tables accessible for big data analysis using data warehousing (MS SQL Server) and analytical tools (Tableau Server and Tableau Desktop). The team also utilized data obtained from the core HR system.

Sales Staff and Reporting Manager performance reports were disseminated to relevant stakeholders monthly for performance measurement, appreciation or improvement in the performance of sales staff.

Data Analysis for Key Insights

Based on the analysis of data using the implemented model, the following insights were revealed;

  • Monthly and fiscal year-to-date trends of direct revenue achievement
  • Monthly and fiscal year-to-date trends of team revenue achievement
  • Direct and team-wise contribution to revenue
  • Pakistan-wide performance incorporating the performance of all regions for the fiscal year
  • Profiles of individual managers
  • Profiles of individual sales staff

The insights were then shared in a formal report with key stakeholders in the company to take timely action.


As a result of this activity, the company was able to achieve the following outcomes:

  • The revenue contribution from the retail sales team increased
  • The productivity of the sales staff was enhanced as compared to the previous year
  • Regular monitoring and tracking mechanism resulted in increased visibility and transparency of sales staff performance which helped in fair decision making at the time of appraisals
  • Outperformers were identified and rewarded
  • Disciplinary action was taken against underperforming employees

Key Highlights of the Analysis