Resource assignment in short life technology intensive (SLTI) new product development (NPD)

Abstract

Enterprises managing multiple concurrent New Product Development (NPD) projects face significant challenges assigning staff to projects in order to achieve launch schedules that maximize financial returns. The challenge is increased with the class of Short Life Technology Intensive (SLTI) products characterized by technical complexity, short development cycles and short revenue life cycles. Technical complexity drives the need to assign staffing resources of various technical disciplines and skill levels. SLTI products are rapidly developed and launched into stationary market windows where the revenue life cycle is short and decreasing with any time-to-market delay. The SLTI-NPD project management decision is to assign staff of varying technical discipline and skill level to minimize the revenue loss due to product launch delays across multiple projects. This dissertation considers an NPD organization responsible for multiple concurrent SLTI projects each characterized by a set of tasks having technical discipline requirements, task duration estimates and logical precedence relationships. Each project has a known potential launch date and potential revenue life cycle. The organization has a group of technical professionals characterized by a range of skill levels in a known set of technical disciplines. The SLTI-NPD resource assignment problem is solved using a multi-step process referred to as the Resource Assignment and Multi-Project Scheduling (RAMPS) decision support tool. Robust scheduling techniques are integrated to develop schedules that consider variation in task and project duration estimates. A valuation function provides a time-value linkage between schedules and the product revenue life cycle for each product. Productivity metrics are developed as the basis for prioritizing projects for resources assignment. The RAMPS tool implements assignment and scheduling algorithms in two phases; (i) a constructive approach that employs priority rule heuristics to derive feasible assignments and schedules and (ii) an improvement heuristic that considers productivity gains that can be achieved by interchanging resources of differing skill levels and corresponding work rates. An experimental analysis is conducted using the RAMPS tool and simulated project and resource data sets. Results show significant productivity and efficiency gains that can be achieved through effective project and resource prioritization and by including consideration of skill level in the assignment of technical resources

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