Happy Employee Scheduling

Happy Employee Scheduling 2017-11-16T19:36:10+00:00

Project Description

Project Brief

We wall want happy employees. Our client had a complex set of rules and constraints governing the deployment of employees across a set of sites. These rules were conditioned on employee specialization, unique characteristics of the site, and the prior history of employee deployments to a site.  Employees, on the other hand had their preferences for shift selection, vacation dates, and constraints for the accommodation of certain planned life events requiring employee absence.

The end result is a highly complex constrained optimization problem than could not be solved using off-the-shelf softwares. Even finding a single solution that satisfies all hard constraints was for our client a difficult and time consuming process, and adding in a ‘happiness’ factor (satisfying employee preferences to the greatest extent permitted by the constraints) seemed like an unattainable goal. The end result was a system that was in perpetual risk of collapse compounded by low employee satisfaction due to the perpetual fire-fighting.

Using our unique background as physicists and mathematicians we were able to develop a custom optimizer which efficiently and reliably solved the hard constraints, and optimized happiness to an impressive extent. Nearly 99.5% of the preferences could be satisfied 95% or more of the time. It turned out that the solution space satisfying the hard constraints was ample enough, and the employee preferences varied enough, that the vast majority could indeed be accommodated. All it took was for a few creative and experienced mathematical minds to look at the problem, and go a bit beyond the box of off-the-shelf software.

Skills Needed

The primarily skills needed were mathematical ingenuity and a solid foundation in optimization technology – coupled with visualization skills so that the client could quickly understand the inputted constraints and results. The latter was achieved by the development of a browser based app which the client could use from anywhere with a valid internet connection.

Mathematical Algorithms 98%
Web Development 92%
Data Visualization 96%

The Process

Initial Concept Planning

First it needed to be understanded what the client had tried before and why it did not work. Also of high importance was to understand if the clients requirements were actually as complex as they were stated or perhaps a change in perspective could induce important simplifications which would render the problem much more tractable.

Prototype Development

A prototype demonstrating a proof of concept that the problem could be solved was rapidly developed. By maintaining close communication with the client, multiple ‘secret’ requirements and preferences were drawn into the light and addressed.

Final Delivery

Once the prototype had gone under several iterative improvements and all client requirements and most preferences were accommodated for, final implementation and deployment was executed. After a period of initial testing and tweaking the system turned on live and incorporated into business operations.

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