To successfully develop a complex product, a firm must answer two critical questions: how to “develop the right product” and how to “develop the product right.” Motivated by the real practice of Xiaomi’s new product development (NPD) projects, this article responds to these calls in the following ways. To design the right product, using an enhanced PageRank algorithm to investigate customer needs, NPD managers can select appropriate function modules of the new product to meet customers’ demand. To develop the new product in the right way, NPD managers should optimize the NPD organization. This article applies the multi-domain matrix (MDM) to identify the technical coordination dependency strength among different teams and then to measure the NPD organization’s complexity according to its entropy. By proposing the External Entropy of Cluster (EEC) and Internal Entropy of Cluster (IEC), we develop an entropy-based two-stage clustering criterion of design structure matrix (DSM) to optimize the NPD organization. The first-stage clustering criterion maximizes the added average dependency strength of DSM, and the second-stage clustering criterion minimizes the Weighted Total Entropy, including the IEC and EEC. An industrial example is provided to illustrate the proposed model. The results indicate that the clustered DSM can reduce the organization’s complexity.
All Science Journal Classification (ASJC) codes
- Modeling and Simulation
- Computer Science Applications