Developing Improvement Capability: Part 1 – What do we need to know?

in Building Capability

by David M. Williams, PhD

As organizations pursue quality as a business strategy, they quickly realize a need to develop improvement capability across the workforce. This requires understanding what people need to know, who needs to know what, and what is the best way to learn.

This is part one of a four-part series. You can read part two here, part three here, and part four here.

What do we need to know?
The body of knowledge on the science of improvement is large and can feel daunting but, for most improvers, building capability around an initial set of tools and methods can go far.

First, improvers need to have a roadmap or framework for chartering and executing improvement projects. The Model for Improvement is an example that uses three powerful questions to help guide improvement work:

  • What are we trying to accomplish? The response to this question is an aim statement and the outcome of the work. It includes what will be improved, by how much, and by when.
  • How will we know a change is an improvement? This requires a set of three to eight measures including an outcome measure (aim), process measures, and balancing measures.
  • What changes can we make that will result in improvement? This includes your theory of change that is predicted to achieve the outcome.

The Model for Improvement strongly promotes action learning with the use of the plan, do, study, act (PDSA) cycle to test and learn. 

In addition to the PDSA cycle, there are a handful of core tools and methods that are helpful to people in most projects. This list is adapted from Kaoru Ishikawa’s seven basic quality tools:

  • Check sheets – to collection data 
  • Flowchart – to map a process
  • Cause-and-effect diagram – to capture potential causes of a problem and organize into categories
  • Scatter diagrams – to look at relationships in data
  • Pareto chart – to see which issues are contributing the most
  • Histogram – to see the frequency distribution of data
  • Run and Shewhart statistical process control charts – to display and track measures overtime in order to study variation and understand the impact of changes on your measures

A working understanding of when and how to use these few tools can aid improvers in most improvement projects.

Moving from improvement projects to quality as a system requires adding a broader set of competencies including clarity of purpose, systems thinking and measurement, understanding the customer and organizational performance, and systematic approaches to improvement, learning, and sustaining of results.

In part two, I’ll look at how to think about who needs to know what.

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