Economic competitiveness relies upon innovation and digitized tools, services and data representation. These innovations are required for organizations to remain effective. Designers and design managers guide the evolution of digitally enabled design capabilities by integrating different types of digital process capabilities and resources. Such capabilities can also help optimize complex systems (e.g., smart grid, pervasive healthcare). Building on organizational and evolutionary theory, this project studies changes in organizational processes as they incorporate innovative virtual elements. It applies a process modeling framework to explore underlying mechanisms that generate patterns of change, and uses computational tools in conjunction with theories of evolutionary genetics to analyze longitudinal changes in organizational processes for integrating virtualized innovations. Generative structural elements of design processes (e.g., genotypes) give birth to surface-level design routines and variations (e.g., phenotypes) over time. Processes are represented as sequences akin to biological genes and their translated protein products. while combinations of elements akin to DNA base pairs and their corresponding amino acids capture essential traits of design activity. This new vocabulary helps us delineate structurally the fundamental design task elements and their variation across design task instances.
The study advances theoretical understanding of how digital capabilities alter organizational processes. It shows how mutations emerge and how processes change over time. It identifies strategies for embedding digital capabilities into processes, and explores the impact of complexity. It advances instrumentation, methodology and analytical techniques by describing digitally-enabled processes and performing comparative, hierarchical, structural-analytical analyses of event-sequence-based process data. It provides longitudinal data on the micro- and meso-level changes in design processes from systematic studies of design for cars, chips and buildings. Genetics research is used to evaluate design in light of evolutionary models and agent-based simulations and to identify patterns of integration of digital capabilities into design processes over time.
Organizational routines are fundamental in carrying out these activities. These routines provide the foundation of organizational identity and stability. At the same time, routines continue evolve and become the source of changes in organizations. Recently, digital technology has become an important source of changes in organizational routines. In this study, we used theories and analytical tools from contemporary evolutionary to analyze evolution of routines in organizations. Using our method, we aim at undestanding the role of digital technology in the evolution of organizational routines. Specifically, we analyzed the evolution of organizational rourtines at a construction engineering firm, an automaker, and a global microprocessor manufacturing firm. We also studied the evolution of design routines in open source projects at GitHub. Through this study, we explored the DNA of these organization's routines. Once we identified the DNA of these organizations, we were able to analyze how these organizations' routines evolve as its envionrments and technological tools are changing over time. For the first time, we are able to understand exactly how organizational routines change over time and precisely measure their dynamic patterns and pace of change. For example, Figure 1. shows how MEP (Mechanical, Electrical and Pluming) coordination routine has evolved over four years at the construciton engineering firm we studied. It shows that the routine that developed 2008 was not preserved further. Instead, the original routine of 2007 created an alternative routine in 2009 which then continue to evolve 2011. Furthermore, we are able to understand exactly what aspects of routines are changing and what are being mutated. We also are able to understand what routines become exctinct and what routines are preserved in organizations. Ultimately, our study offer new evolutionary perspective in understanding organizations as dynamic entities that constantly go through on-going changes. While such theoretical insights were avilable in organizations, our study provides for the first time empirical ways to understand how organizational routines change over time. Using our methods, organizations can better understand the nature, source, and consequences of changes in organizational routines.
