Strategic by Design: Iterative Approaches to Educational Planning: In the Push for Accountability, Colleges and Universities Resort to Simplistic, Linear Thinking When Planning-An Approach Not Well-Suited to Academia

Article excerpt

Today's tumultuous economic and political conditions require universities to adapt--fast. Leaders must attend to unforeseen crises, events, and opportunities in ways that align with their core missions, promote their universities' continued existence, and help achieve disparate goals (Rowley, Lujan, and Dolence 1997). Good planning and good plans involve iteration; simple cause-and-effect thinking is no longer enough.

Good planning and good plans involve iteration; simple cause-and-effect thinking is no longer enough.

Universities can--and frequently do--suffer when they use linear, mechanistic thinking (Presley and Leslie 1999; Rowley, Lujan, and Dolence 1998). Leaders can make too many erroneous assumptions about the future. And, when users view strategic plans as fixed road maps, they often fail to recognize the faulty assumptions that hinder their success along the way. They generally fail to harness emerging opportunities as well. To enhance outcomes, planners must ensure there are adequate resources for monitoring and adjusting plans during implementation. Those empowered to monitor outcomes and activities must fully understand the plan's core intentions so they can effectively refine the plan as it unfolds (Allison and Kaye 2005; Holcomb 2001).

Linear problem solving (as in figure 1) assumes a rational and predictable sequence of events. Models for rational decision making assume that problems are clear and well structured from the start. They require that resources and abilities be determined before designing, and they prevent the designer from introducing new possibilities that present themselves in the course of problem solving (Simon 1973). Higher education's overtly linear, internally-oriented form of planning is more appropriately described as "long-range planning" (Presley and Leslie 1999). Long-range planning is generally more prescriptive and less adaptive than strategic planning and does not provide the mechanisms for quick, purposeful adaptation that could render change efforts more effective.


Strategic planning works best when seen as a continuous process of experimentation that allows multiple decisions to emerge on many different fronts simultaneously (Leslie and Fretwell 1996). Chaffee (1985) notes that while strategy formation in the business context actually had three facets (linear, adaptive, and interpretive), higher education has relied almost exclusively on linear models. This has contributed to some of the problems educational planning faces today. Adams (1991) describes three major areas of crisis: (1) definition and identity, (2) intellectual foundation and scientific theory, and (3) utility and success. This article explores many of these issues in an effort to enhance practice.

Iterative Strategy

Pearson (1990) indicates that in higher education, strategy is best used to set direction, focus effort, encourage consistency of effort over time, and promote flexibility. Organizations can respond to unforeseen challenges in advantageous ways when they define a collective vision--and chart a course aligned with that vision--through a truly strategic and ongoing planning process (Barnetson 2001; Cutright 2001; Gordon 2002; Rowley, Lujan, and Dolence 1997; Swenk 2001).

"Iteration," according to Merriam-Webster Online (2009, [paragraph] 1a), constitutes "a procedure in which repetition of a sequence of operations yields results successively closer to a desired result." Architectural design strategies reflect the sort of non-linear, iterative, and synthesizing processes scholars recommend for effective strategic planning in higher education. Architects synthesize a vast array of concerns. They continually revisit key objectives throughout the planning and implementation (i.e., construction) process. Using iterative thinking, problems are defined over time. As they emerge, they are paired with appropriate solutions (Dorst 2006; Maher, Poon, and Boulanger 1996). …


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