mtfw: a repeatable framework for analysing and improving processes

by admin on May 8, 2011

6 steps for developing and improving processes with application in global health delivery
An MIT team shares their framework after working with community nurses in India

Following the completion of their Global Health Delivery Lab (ghdLAB) projects in Africa and India, we asked our MIT student teams to reflect on their ghdLAB project experience and share what they learned – insights, a how-to guide, best practice tips  – in ways that can be used by others undertaking similar work or facing similar issues in global health. We share their thoughts under the ‘management for the world’ (mftw) collection in the hopes that others will build on it in keeping with the creative commons license.

By Emily Edwards, Ozge Karanfil, Alicia Pichard, and Julia Stark

We propose a generalized, concrete and repeatable framework for developing and improving processes in resource constrained settings, drawing on our field experience in a global health care setting where needs are pressing, and resources scarce.  The proposed framework is inspired by our experiences of the observed differences between the actual and imagined processes in health care settings, where the gaps between these two can be huge, and may affect the effectiveness and the efficiency of the health care service at all levels of the organization.

Our framework involves the following steps.

Step 1: Draw Imagined Process

Document what you believe reflects the basics of the current process.  Do this using a process flow diagram. We suggested a simple, iterative process flow diagram that can be easily modified according to specific purposes.

Example imagined process

Step 2: Observe Actual Process

“Go and See” how things actually work in the field.  Watch the process and take detailed notes. Some questions to ask in this step are:

  • How long does each step take?
  • Are there repeated activities?
  • What parts of the process seem critical to its success?
  • What process steps seem wasteful?
  • What metrics are currently being used?
  • What metrics could be used/or added to the existing ones?

Step 3: Draw Actual Process

Using your observations from the Go-See step to develop a process flow diagram which outlines the reality in place.

Example actual process

Step 4: Identify Differences Between Actual and Imagined

Use explosion clouds to emphasize the differences between what you believed was the current process and the actual process.  Use another color explosion cloud to highlight the wastes (any wastes of time and/or other resources) you identified in the process.

Example of the use of explosion clouds

Step 5: Learn Reasons Behind Differences

Identify the reasons for the differences between the imagined and actual processes, as well as the reasons for the wastes you highlighted. Talk with people who are directly involved with the process and use techniques such as 5 Why’s.  Make Fishbone diagrams to identify root cause of the issues.

Step 6: Design New Improved Process

Using all the information you have collected, design a new improved process within feasibility limits/ given the existing resource constraints.  You should fix broken parts of the process, streamline process to reduce waste, and identify critical process steps.  You must also design appropriate metrics.  Decide what needs to be measured, craft appropriate metrics to meet these needs, and determine how to collect the necessary data.

Example of new, improved process

Repeat the above steps as appropriate for continuously improving the process.

References:

—Ishikawa, Kaoru (1990); (Translator: J. H. Loftus); Introduction to Quality Control; 448 p.
Dale, Barrie G. et al. (2007); Managing Quality 5th ed.
—Taiichi Ohno; foreword by Norman Bodek (1988). Toyota production system: beyond large-scale production. Portland, Or: Productivity Press.
—“An Introduction to 5-why’s“. Retrieved 21 April 2011.

 

Was this article useful to you? Please give us feedback on how to improve sharing our work by leaving us a comment or e-mailing us at ghd.projects.lab@mit.edu.

Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.

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