Probabilistic Workforce Planning System for IT Consulting
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Solution Overview
Problem
Conventional workforce planning systems struggle to accurately forecast workforce demand in rapidly changing markets due to uncertainty in project acquisition and attrition, leading to underestimation of true workforce requirements, especially in industries like IT consulting and integration services.
Innovation Solution
A probabilistic analysis method and system that quantify the risk in workforce requirement planning by creating a probability distribution of the gap between workforce supply and demand, using a graphical user interface and statistical formulas to assess uncertainties in project opportunities and attrition, allowing for a hiring plan across skill sets and periods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a target probability threshold is set to identify workforce for projects, then implementation simplicity is improved, but workforce availability level deteriorates
Solution Approach 1:
The patent transforms the workforce planning approach by changing the parameter from a single probability threshold to a comprehensive probability distribution analysis. Instead of using a fixed threshold (e.g., 75%) to filter projects, the system calculates the complete probability distribution of workforce gaps by considering all projects in the funnel with their individual winning probabilities. This allows managers to see the full range of possible outcomes and make more informed decisions about workforce requirements.
2Device complexity
If projects below threshold probability are ignored in workforce planning, then planning complexity is reduced, but workforce requirement accuracy deteriorates
Solution Approach 1:
The patent merges all projects in the project funnel into a single probabilistic workforce requirement calculation. Instead of separating projects into accepted/rejected categories based on a threshold, the system combines the workforce requirements of all projects, weighting each by its probability of being won. This integration ensures that even low-probability projects contribute to the overall workforce planning, providing a more accurate and comprehensive view of potential requirements.
Solution Approach 2:
The system provides feedback through probability distribution outputs that show the full range of possible workforce gaps. By displaying the complete distribution rather than a single point estimate, the system enables managers to understand the uncertainty and variability in workforce requirements. This feedback mechanism helps adjust planning decisions to account for the cumulative effect of multiple probabilistic projects.
Data Source
AI summary
A method and system of workforce related resource planning is disclosed. The method includes receiving workforce related resource data wherein the workforce related resource data includes demand data and supply data, disaggregating the demand data and the supply data and creating a probability distribution of a workforce gap between the demand data and supply data to quantify risk associated with workforce related resource planning.