Effort Time Tracking & Workload Visibility Case Study

Effort Time Tracking & Workload Visibility Enhancement for Subhasree

Effort Time Tracking & Workload Visibility Enhancement for Subhasree

About the Client

Subhasree is a growing organization where multiple users manage operational responsibilities across various task modules. As the team expanded, leadership needed clearer visibility into how time and effort were being distributed across users.

While tasks were being assigned regularly, there was no measurable framework to evaluate actual engagement levels, workload balance, or resource utilization.

The Visibility Gap in Workload Management

Although task execution was structured, effort measurement was not standardized. This created operational blind spots:

  • No clear view of how much time each user was engaged
  • Difficulty identifying overloaded team members
  • Underutilized users were not easily visible
  • Task distribution relied on assumptions rather than data
  • Resource planning lacked measurable benchmarks

Most importantly, there was no consolidated report showing total effort allocation per user.

What Subhasree Needed

The leadership team wanted a system that could instantly answer:

“How much effort time is assigned to each user, and is the workload balanced?”

Their core requirements included:

  • Defining expected effort time during task creation
  • User-wise total effort calculation
  • Visibility of task types assigned to each user
  • A centralized report showing overall workload distribution
  • A measurable approach to evaluate engagement and capacity

They needed clarity, structure, and data-driven control.

Designing an Effort-Based Workload Tracking System

To address this need, an effort tracking enhancement was developed and implemented within MIDAP (MI Digital Autopilot).

The solution focused on three principles:

  • Simplicity
  • Measurability
  • Managerial visibility

Effort Time Defined at Task Creation

Users can now enter the expected effort time while creating tasks.

For example:

  • A daily task may require 30 minutes
  • A review task may require 1 hour
  • A project milestone may require multiple hours

Each task now carries a defined time estimate, introducing structure into workload planning.

Centralized Effort Reporting

A comprehensive report was introduced to provide:

  • Total effort time assigned per user
  • Task-type breakdown per user
  • Overall workload distribution across the team

This converts scattered task assignments into meaningful engagement insights.

Clear User-Level Visibility

The report displays:

  • User Name
  • Total Assigned Effort Time
  • Task Category Breakdown
  • Overall Engagement Load

Managers can instantly determine whether a user is:

  • Overloaded
  • Optimally engaged
  • Underutilized

No manual tracking. No guesswork.

How the System Works in Practice

For example, if a user has:

  • Daily tasks: 3 hours
  • FMS tasks: 2 hours
  • PMS tasks: 1 hour

The report displays:

  • Total Effort Time: 6 hours
  • Clear breakdown by task type
  • Immediate visibility into workload concentration

Everything is measurable at a glance.

Impact on Subhasree’s Operations

After implementation, Subhasree experienced measurable improvements:

  • Clear visibility into team engagement
  • Identification of workload imbalances
  • Improved task allocation fairness
  • Structured capacity planning
  • Data-driven managerial decisions

The organization transitioned from assumption-based distribution to measurable workload management.

Turing Effort Data into Operational Control

By integrating effort time tracking with centralized reporting, Subhasree transformed how productivity is monitored.

What was previously unstructured is now:

  • Measurable
  • Transparent
  • Actionable

With this enhancement, leadership gains continuous visibility into engagement levels, ensuring balanced workloads and scalable operational control.

MIDAP (MI Digital Autopilot) continues to support Subhasree in strengthening performance visibility and building systems that scale with growth.


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