Posts in Learning to Improve
Goal Setting is Often an Act of Desperation, Part II

January is a popular month to set new goals, so I decided to kick-off this year with a four-part series on this very topic. In Part I of the series, I proposed four conditions that organizations should understand prior to setting a goal.

  1. Organizations should understand the capability of the system or process under study.

  2. Organizations should understand variation within the system or process under study.

  3. Organizations should understand if the system or process under study is stable.

  4. Organizations should have a logical answer to the question, “By what method?”

Absent an understanding of these conditions, goals are too often “arbitrary and capricious.”

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Goal Setting is Often an Act of Desperation, Part I

At a recent district leadership team meeting, I put the following quote up on a slide: “Goal setting is often an act of desperation.”1 We are in the midst of updating our strategic plan at United Schools Network, so the purpose of the quote was to start a discussion on healthy goal-setting and to provide a framework for any goal-setting the team would do as a part of this process. I think the typical reaction to the quote is something like the following: “But I thought goal-setting was something highly effective people and organizations do?” I would argue however, that this is rarely the case, be it in organizations or accountability systems, and only can be true if a number of conditions are met during the process.

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Getting on the Same Page with Operational Definitions

A critical component of the Planning phase of the cycle is the idea of operational definitions. The concept of operational definitions is straightforward. The idea is that language must be made operational in order to perform the basic functions in an organization. To put it another way, an operational definition puts communicable meaning into a concept. Concepts that are important to schools such as attendance, engagement, and learning have no communicable value until they are expressed in operational terms.

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The PDSA in Action

Now that I’ve outlined the basic idea of the PDSA cycle, it will be helpful to turn to a real PDSA that I used in my work at United Schools Network. This in fact was the first PDSA I ever designed, so it by no means is being held up as an exemplar. However, I think it is useful as an introductory point to the concept because this particular example is so simple. I’m also happy to report that for a first attempt, this PDSA cycle was fairly successful.

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The Power of PDSA

One of the most powerful tools that sits at the heart of Deming’s Theory of Knowledge is in fact the Plan-Do-Act-Study (PDSA) cycle. PDSA cycles are experiments during which you gather evidence to test your theories. Observed outcomes are compared to predictions and the differences between the two become the learning that drives decisions about next steps with your theory. The know-how generated through each successive PDSA cycle ultimately becomes the practice-based evidence that demonstrates that some process, tool, or modified staff role or relationship works effectively under a variety of conditions and that quality outcomes will reliably ensue within your organization.

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Writing Fiction

Last month, I discussed a powerful tool, the process behavior chart, that can be used to filter the noise out of our data. The whole point of this series has been to think through how to properly interpret and react to data, which includes the filtering process. Unfortunately, much of what happens on the data analysis front in the education sector is akin to writing fiction. Writing fiction will be the main topic of this post.

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Filtering Out the Noise

Last month, I discussed the difference between information and knowledge by analogizing the two concepts to data ponds (information) and data streams (knowledge). A key idea in the transformation of information to knowledge is adding the element of time and visualizing the data in a tool called a process behavior chart. Part of the power of the process behavior chart (PBC) is its ability to filter out the noise in our data; the idea of filtering out data “noise” is the focus of this post.

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Data Ponds & Streams

Last month, I outlined why data has no meaning apart from their context. The discussion centered on some key ideas for presenting data in context as well as a logical definition of improvement. I also introduced an example of how data is often misinterpreted in the education sector. In this post, I’ll begin to lay the foundation for understanding variation in quality improvement work; this will be a precursor to comprehending why so much of the data analysis that is done in organizations is akin to writing fiction.

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Data Has No Meaning Apart from Their Context

In the K-12 education sector, one of the primary uses of data is in state accountability systems. Many states now issue district and school report cards typically based on various performance metrics such as proficiency rates on standardized tests, absenteeism rates, and college and career readiness indicators. Unfortunately though, as James Leonard stated so eloquently in The New Philosophy for K-12 Education:

Absent an understanding of the type of variation present, any discussion of accountability is a burlesque!


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Numerical Naiveté

Dr. Russell Ackoff, the eminent systems thinker said, “Managers do not solve problems, they manage messes.” My take would be more optimistic than Ackoff’s assuming managers knew something about variation. This is in fact why I’ve spent so much time over the last year studying this idea as it fits into W. Edwards Deming’s theoretical framework, the System of Profound Knowledge.

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Leadership & the Essential Elements of Transformation

The case I’ve been making for organizational transformation is based on the premise that our education system is not broken. Rather, it is a system that is operating exactly as it was designed to operate, and it’s producing exactly what it was designed to produce. I do not believe that our schools need reform or restructuring but rather a change in state. This transformative change in state does not occur overnight, but instead is a process that unfolds over 5-10 years (as Deming would put it, “There is no instant pudding!”).

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The Psychology of Joy in Work

Each part of the SoPK is interdependent and equal in importance. Nonetheless, if there is one of the four components that seems to flow through each of the others, it is psychology. A leader of organizational transformation must understand the psychology of individuals, the psychology of groups, the psychology of society, and the psychology of change.

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