A Hierarchical Product Development Planning Framework

Abstract

Uncertainty in new product development (NPD) planning embraces market, creative, technological, and process dimensions to a much greater extent than in non‐NPD project planning. Yet, NPD management is becoming increasingly decentralized, both within the firm and across the supply chain. Hence, planning for NPD uncertainty often results in path‐dependent scenarios cutting across the strategic, tactical, and operational levels of planning. To coordinate this resulting complexity, we propose a stochastic hierarchical product development planning framework with multiple recourses, i. e., corrective actions, to maximize performance across a firm's entire NPD program. We also argue the necessity for a fourth planning level, the infrastructural, that reestablishes norms for market projections, technological forecasts, scheduling, and requirements as latent uncertainty in the environment is continually revealed. An illustration from the automotive industry is presented to demonstrate a deployment of our framework. We additionally discuss the applicability of this framework for managing NPD capabilities over time.

Researching at the Intersection of Innovation, Operations Management, and Entrepreneurship

“…This type of research would likely further develop and expand current operations management research on the various forms of uncertainty entrepreneurs and entrepreneurial firms face in the new product development process (e.g., market, creative, and process uncertainty [Anderson & Joglekar, 2005]) and methods to handle these uncertainties, including, for example, flexible manufacturing capacity (Fine & Freund, 1990), trial-and-error learning or real options reasoning (Sommer & Loch, 2004), supplier selection (Riedl, Kaufmann, Zimmermann, & Perols, 2013;Simangunsong, Hendry, & Stevenson, 2016), and maybe even supply chain management (Seshadri & Subrahmanyam, 2005;Tomlin, 2003).…”

“…However, if changes like these are expected to be large and occur frequently, a more dynamic system is necessary. Future research in this area can build on the current research stream exploring learning in and about complex dynamic systems (see Rahmandad, 2008;Sterman, 2000aSterman, , 2000b as well as dynamic processes for new product development (Anderson & Joglekar, 2005;Brown & Eisenhardt, 1997).…”

The role of standardization at the interface of product and process development in biotechnology

“…Path dependency explains the phenomenon that small differences in early development stages have unequally large impact on development outcomes (Anderson and Joglekar 2005). An illustrative example in biotechnology is the choice of the production strain which often results in lock-in situations for further development steps.…”

Fuzzy Approach for Three Level Linear Programming Problems

“…The lower-levels DMs (DM2, DM3 …) called followers. They execute their policies after the decision of higher levels DMs and then the leader optimizes his objective independently but may be affected by the reaction of the followers (G. Anandalingam, 1988, Anderson 2005, O. Ben-Ayed 1993).…”