Data & Intelligence

Using Cynefin Framework for Complicated HC Projects

So far in this blog series I have discussed using the Cynefin framework for providing guidance in determining the best SDLC methodology to use for a particular type of project defined by the framework as well as delving into the Chaotic type of project.

This month I will focus on the Complicated type of projects defined using the Cynefin framework.

 

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As you can see from the picture above, Complicated is the category where good practices can be found. In this category there are multiple right answers, and expert diagnosis is required to figure them out. This sector demands more quantitative approaches such as Six Sigma as an example.

There are several key characteristics which assist in identifying a complicated project.

Characteristics of the Complicated category:

  • Multiple right answers are available
  • A general idea of the known unknowns
  • You know the questions you need to answer
  • Don’t know how to obtain the answers
  • The problem is more predictable than unpredictable
  • Cause and Effect relationship is not immediately known but is discoverable given enough time

If you find yourself managing a complicated project the approaches defined below will help you better define the complex problems.

Approach for Complicated problems:

  • Assess the situation and Sense the problem
  • Investigate several options
  • Analyze large data groups, as needed
  • Use experts knowledge to gain insight
  • Use metrics to gain control
  • Base response on good practice
  • Determine a course of action
  • Execute the plan, following the Plan, Do, Check, Act cycle

As the picture above indicates, since this is a more quantitative type of project the waterfall methodology can be used with tenants of Agile.

 

About the Author

John Ideler is a delivery director within Perficient's national healthcare practice. John has more than 25 years of experience in the IT industry, including more than five years in life sciences and healthcare. Over the past several years, John has focused in providing clients BI analytics and value-based care capability using Epic's Cogito data warehouse as a centralized source.

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