Search

Search Results

• 1. [Article] Employee Training Schedule Optimization

  As the amount of technical information explodes in volume and technical professionals struggle with staying current with the latest information, one important channel is the large scale trade or technical ...

  Citation × Citation Citation Abstract Copy Title: Employee Training Schedule Optimization Author: Alzahrani, Ahmed, Gupta, Apeksha, Hsu, Allen Wei Chen, Tiwari, Rashi, Vinchhi, Komal Year: 2016 As the amount of technical information explodes in volume and technical professionals struggle with staying current with the latest information, one important channel is the large scale trade or technical conference. Bringing value back to business by keeping employees up to date with trends in the industry is something that a company expects when it invests time and money in sending its employees to such conferences. To choose sessions from a large conference is an exacting job for employees as they need to scroll over such huge data set and select the best session that matches their interest and preferences. This results in large number of employee hours consumed, which ultimately can prove expensive to a company. Due to these reasons, organizations might find formal planning methods beneficial to get the best return on their investment. To test this, we are examining the case of a major automotive industry company named Daimler Trucks North America. This company is sending six of its employees from the IT department to attend a conference conducted by IBM called “World of Watson”. Human Resource and IT capability being key resources to create competition and differentiating factors between two companies. Training presents a prime opportunity to expand the knowledge base of all employees, but companies and employees alike find this activity a little taxing, what with training conferences having a rigid schedule, with back to back sessions, some even running parallel to each other and add to this the work schedule of employees and their varying skills level and interests, companies and employees face variety of issues to be sorted out before employees can actually figure out which session to attend. The main objective of this project is to take the interest of the employee into account and develop an optimized schedule for 6 Daimler employees who have to attend a three-day training conference being organized by IBM. The primary metrics used for this schedule planning are the availability of employee, their skill level, and the area of preference. To increase overall coverage of sessions, we came up with a model that does not assign the same session to two employees. The model also assures that no time slot is left vacant. This helped with increasing the scope of learning. Currently, Daimler has a traditional and delegated approach, where another employee was given the task of going through the list of sessions and to choose the sessions each attendee should attend. The main problem with this approach is that the entire decision of selecting sessions is manual and hence not very personalized. This paper attempts to propose a scheduling tool based on excel to cope with the complex task of picking the best session to be attended by an employee based on their pillar preferences. Title: Employee Training Schedule Optimization Author: Alzahrani, Ahmed, Gupta, Apeksha, Hsu, Allen Wei Chen, Tiwari, Rashi, Vinchhi, Komal Year: 2016 As the amount of technical information explodes in volume and technical professionals struggle with staying current with the latest information, one important channel is the large scale trade or technical conference. Bringing value back to business by keeping employees up to date with trends in the industry is something that a company expects when it invests time and money in sending its employees to such conferences. To choose sessions from a large conference is an exacting job for employees as they need to scroll over such huge data set and select the best session that matches their interest and preferences. This results in large number of employee hours consumed, which ultimately can prove expensive to a company. Due to these reasons, organizations might find formal planning methods beneficial to get the best return on their investment. To test this, we are examining the case of a major automotive industry company named Daimler Trucks North America. This company is sending six of its employees from the IT department to attend a conference conducted by IBM called “World of Watson”. Human Resource and IT capability being key resources to create competition and differentiating factors between two companies. Training presents a prime opportunity to expand the knowledge base of all employees, but companies and employees alike find this activity a little taxing, what with training conferences having a rigid schedule, with back to back sessions, some even running parallel to each other and add to this the work schedule of employees and their varying skills level and interests, companies and employees face variety of issues to be sorted out before employees can actually figure out which session to attend. The main objective of this project is to take the interest of the employee into account and develop an optimized schedule for 6 Daimler employees who have to attend a three-day training conference being organized by IBM. The primary metrics used for this schedule planning are the availability of employee, their skill level, and the area of preference. To increase overall coverage of sessions, we came up with a model that does not assign the same session to two employees. The model also assures that no time slot is left vacant. This helped with increasing the scope of learning. Currently, Daimler has a traditional and delegated approach, where another employee was given the task of going through the list of sessions and to choose the sessions each attendee should attend. The main problem with this approach is that the entire decision of selecting sessions is manual and hence not very personalized. This paper attempts to propose a scheduling tool based on excel to cope with the complex task of picking the best session to be attended by an employee based on their pillar preferences. Close