Theory Thinking Helps Improvement
Ten years ago, Clayton Christensen and Paul Carlile wrote a cogent summary of theory building that applies directly to our work with the Model for Improvement. Their Figure 1 shows the process of building theory, the basis of their perspective.
George Box often sketched a time series view of this process, alternating cycles of induction and deduction, to show how effective engineers and scientists work to explore a system and build understanding.
Christensen and Carlile's summary had a great title, "Practice and Malpractice in Management Research." It circulated among improvement advisors at IHI several years ago as a Harvard Business School working paper-- the latest version I could find on-line is http://www.hbs.edu/faculty/publication%20files/05-057.pdf. I first got a copy from my colleague at API, Cliff Norman.
The authors subsequently published a version of their paper in 2009 (C.M. Christensen and P.R Carlile (2009), “Course Research: Using the Case Method to Build and Teach Management Theory”, Academy of Management Learning & Education, Vol. 8, No. 2, 240–251.)—that’s the source of Figure 1. I thank Professor Carlile for sending me the reference.
The first half of the published article describes a cycle of theory-building immediately relevant to improvement. The second half discusses application of the authors’ insights to applications in the business school classroom, engaging students in “course research.”
In applications of the Model for Improvement, we seek to learn how a system works in order to improve performance. In other words, you develop of theory of what works and why—a mental framework that tries to make sense of the way your part of the world functions.
As part of their discussion of theory-building, Christensen and Carlile also offer cogent advice about measurement, worth quoting at length. You can substitute the noun “manager” or “improver” for researcher in the next paragraph and the advice still holds—everyone involved in improvement, according to the Model for improvement, is trying to build a better theory of what works and why, seeking to build better predictions about future behavior. And it is good to recognize the value of both numbers and stories in theory building. For managers and improvers of course we can also add data that comes from direct observation, seeing for themselves how a system performs.
“The healthiest mind-set for researchers is that nearly all data—whether presented in the form of a large quantitative data set on one extreme, or an ethnographic description of behavior on the other—are subjective. Numerical and verbal data alike are abstractions from a much more complex reality, out of which the researcher attempts to pull the most salient variables or patterns for examination. Whereas the subjectivity of data from field-based, ethnographic research is glaringly apparent, the subjective etiologies of numerical data are hidden and cannot be reviewed. There should be no smugness among quantitative researchers about the alleged objectivity of their data, and no defensiveness amongst field researchers about the subjectivity of theirs. We are all in the same subjective boat, and are obligated to do our best to be humble and honest with ourselves and our colleagues about where our data comes from as we participate individually within and collectively across the theory-building cycle.”(p. 243)