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| Understanding the Contingencies of Systems and Implementing Change |
| Monday, May 30, 2016 |
| 8:00 AM–9:50 AM |
| Crystal Ballroom A, Hyatt Regency, Green West |
| Area: DEV/OBM; Domain: Translational |
| Chair: Michael Lamport Commons (Harvard Medical School) |
| Discussant: Dristi Adhikari (Colby-Sawyer College) |
| CE Instructor: Michael Lamport Commons, Ph.D. |
| Abstract: The symposium on Understanding the contingencies of systems and implementing change focuses on social, behavioral and cultural aspects of change in business and society as a whole. Change is perceived to be uncertain and complex; therefore it is often met with resistance and fear. As adaptation to change requires conscientious effort, not everyone is able to make it. The symposium attempts to demystify this uncertainty and analyze the process. The presentations dissect different cultures and schools of thought to discuss how new memes evolve, propagate and adapt and thereby play a critical role in an individuals survival. Further, the symposium will include empirical reports as well as theoretical reviews focusing on organizational change. The scope of the presentations spans across behavioral aspects of partners in start-up to stakeholder in large, top-down organizations. The presentations will emphasize the effects of reinforcement contingencies, task mastery and recognition, behavioral momentum and successful startup partnership. |
| Keyword(s): behavioral momentum, change, startups, success |
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| The Effects of Regression to the Mean and Behavioral Momentum in Organizations |
| WILLIAM JOSEPH HARRIGAN (Harvard Extension School), Saranya Ramakrishnan (Core Complexity Assessments ), Sarthak Giri (Core Complexity Assessments ), Michael Lamport Commons (Harvard Medical School) |
| Abstract: Large, top-down organizations tend to be bureaucratic, less innovative and more resistant to change. There are two forces that prevent such an organization from changing. 1) Behavioral momentum, which is the tendency for behaviors to continue as it has been, rather than evolving with the dynamic world. 2) Regression to the mean, which refers to the phenomenon that ensures that even if an organization overcomes behavioral momentum and adopts change, the windfall gains of the change is always at risk of being lost. This may happen by mass adoption from large competing organizations. Furthermore, in such organizations the chain of command extends from top to bottom, which implies a greater superiority and domination of higher levels over multiple lower ones. However, in a rapidly changing business world, these characteristics are a death knell to business success and sustenance. Adopting a highly autonomous 2-3 layer flat management structure on the other hand fosters creativity and innovation. Companies then can rely on a broad base of leaders and employees who feel ownership for the overall success of the organization and innovation can occur in small units that have autonomy and power over their own culture. |
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| Decoding Successful Startup Partnerships |
| SARTHAK GIRI (Caldwell University), Saranya Ramakrishnan (Core Complexity Assessments ), Michael Lamport Commons (Harvard Medical School) |
| Abstract: Startups are high risk and high reward environments with an extremely high rate of failure. Marmer et. al, in their report on “Why high-growth technology startups fail?” report that the success rate of these startups is lower than 10%. Understanding co-founder partnerships that have a higher likelihood of success could be a crucial factor for business survival. This study attempts to understand interest and stage of successful past co-founder partnerships. We then derive trends about their compatibility and complementarity to assess the success of co-founder pairs in Start-ups. The study focuses on start-ups that are less than 5 years old. There are three hypotheses: 1) Successful past co-founders would have had complementary interests/ skills; 2) They would have been at least Metasystematic Stage or higher; 3) At least one of the cofounder would be high on Enterprising on the Holland’s interest scale. To test these hypotheses, secondary data primarily from biographies and peer-reviewed articles will be used for past co-founders whereas primary data mainly from surveys and interviews will be used for Startup co-founders. We believe this study would help current entrepreneurs seek out co-founders that lead to a thriving and profitable startup. |
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Cultural Adaptability |
| SARANYA RAMAKRISHNAN (Core Complexity Assessments), Anne Zhang (Swarthmore College), Michael Lamport Commons (Harvard Medical School) |
| Abstract: Human beings face similar adaptive challenges as all other organisms. However, humans are unique in that for the last 150,000 years, most of their adaptations have been cultural. Culture may be roughly described as consisting of an extremely large set of memes, which are units of information. As humans interact within their society or social groups these memes are continually reinforced and thereby play an integral part in molding their perception of cause and effect. When individuals translocate from one country to another, specifically from one country with a relatively traditional social structure to one with a more liberal social structure, these individuals have to adapt in order to assimilate into society. This is because the memes and reinforcers of the different societies vary significantly. Cultural adaptations are spectacularly complex and essential for their survival. They are also not without an underlying biological basis of sociability, inventiveness and imitativeness. In this paper we explore the reasons around why some individuals adapt and why some are more resistant to change. |
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Social Change |
| NICHOLAS HEWLETT KEEN COMMONS-MILLER (Tufts University), Saranya Ramakrishnan (Core Complexity Assessments ), Dhushanthi Ramakrishnan (Lake Forest College), Michael Lamport Commons (Harvard Medical School) |
| Abstract: Social change is characterized by (1) the creation of powerful memes by a single individual (2) propagation of those memes to a large group of people (3) sustenance of those memes via behavioral change and transmission to associated social groups as well as to the next generation. Thus social change is complete when there is a collective change in group behavior. When large social groups adapt to a new way of thinking or behaving however behavioral momentum of social groups needs to be overcome. To displace a current group behavior with new behavior, therefore this new behavior or thinking has to be often more potent than the current behavior. In such a scenario the adoption curve of new behavior is often slow at the beginning but as time progresses the number of people who adopt increases. The pace of adoption however can range from a few months to one or two generations. Finally to sustain this change the operation of long term contingencies with long term attractors acting as reinforcers need to be at play. |
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