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The main arguments on this topic from the papers by Dillman and Habermann a are summarized first, followed by the points made by the workshop participants. Census Bureau in the early s and his involvement in projects to reduce measurement and nonresponse errors.
He observes that three interconnected features of large government survey organizations make it difficult to create an environment of innovation: Page 24 Share Cite Suggested Citation: Facilitating Innovation in the Federal Statistical System: Summary of a Workshop.
The National Academies Press. Some government surveys are of great scale and complexity, so that not only do they present huge operational problems, but much of the specific knowledge for designing and implementing the surveys must come from research which only the host agency can design and implement.
A circumstance is thereby created that might be likened to, for example, an aircraft manufacturer attempting to operate an airline while continuing to design aircraft. Putting pilots and flight attendants into the same room with aeronautical and thermal systems engineers—each representing multi-million dollar enterprises with equal investment in the outcome of their common research project—could produce some unpredictable as well as strange outcomes.
It is perhaps inevitable that tension will develop between a employees responsible for the visible outcomes of the organization, whom the public and Congress are aware of and keep account of, and b employees who are part of the research arm of the organization, who are responsible for learning why and how things work and how to improve them.
From the perspective of the operations culture Dillman,p. Control groups are not really necessary, and the fewer treatment groups the better. From this perspective the real value of research is as the rehearsal is to a stage performance, where one dares not fail.
At the same time, those from the research culture have in mind carefully designed treatment factors and a full factorial design. Preordained rules of assignment to treatment and control groups as well as rules for interpretation of evidence must be scrupulously followed.
Both of these cultures are essential to success. However, as Dillman notes, the perceived needs of one culture can often interfere significantly with the needs of the other.
This is a major barrier to innovation. Two Value Systems As described by Dillman, the values and skills of the people in the two cultures are significantly different. Statistics is the core value of those in the research culture. However, people trained in measurement and nonresponse issues are few in number, and, Dillman asserts, they generally lack influence in the design process.
However, Dillman argues that the skills that are valued in the operations culture have almost nothing to do with reducing measurement and nonresponse errors; rather, the valued skills involve organizing large numbers of people to get tasks done accurately, on time, and at a low cost.
The result is that, although measurement and nonresponse issues have emerged as increasingly important sources of data collection error, there has not been a corresponding emergence of significant numbers of professionals to design theoretically based projects needed to ensure the development and implementation of appropriate innovations for resolving the error.
Dillman characterizes this situation as a barrier to innovation. Difficulty of Resolving the Culture Differences Dillman notes that government statistical agencies, such as the Census Bureau, are highly complex organizations with many different tasks.
He noted, for example, that the then-proposed research and development program of the Census Bureau might go through a minimum of eight entities outside the agency. Differences in organizational hierarchies may be resolved in a number of ways, such as by which entity is the most powerful or by who won the last time.
As a result, compromises are common, and the decisions made by organizational hierarchies are often based on different issues from those that originally led to the negotiation.
He notes Dillman,p. From the standpoint of innovation in a rapidly changing technological environment, though, hierarchical processes make such cultural and value system concerns more difficult to resolve.
The down-side of hierarchy for innovation is that it forces large amounts of critical information upwards through a series of smaller and smaller funnels. This process is slow, but the information that eventually gets through represents only 1 Although the focus of his article is on government statistical agencies and the Census Bureau in particular, Dillman noted the general nature of the issues.
The solutions he presents are not unique to government survey organizations, he wrote, but also apply to universities and corporations.Fascination with organizations that eschew the conventional managerial hierarchy and instead radically decentralize authority has been longstanding, albeit at the margins of scholarly and practitioner attention.
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