Relationships in change

imageThrough this series of posts we are trying to tell a story of change through a deeper understanding of evidence and the interpretative analysis of data using practitioner expertise. One helpful lens through which to view data is the use of correlations that expose relationships between factors. We’ll place a cautionary note early that correlation does not show causation and suggest that you read this excellent article from the future work centre about the caution required when viewing data.

 

Relationships in Change

 

The relationship diagram shown here has been generated through analysis of the data coming from the Workplace Change Survey (results from the survey have already been presented in a previous post). The diagram on the left shows the relationships between the factors in the survey as exposed through correlations.

In the relationship diagram, the thicker yellow lines show a very strong positive relationship, the thinner lines show a strong positive relationship1.

Correlations

 

Correlations show if there is a relationship between variables in data. In the example shown on the right, where people reported that they felt that their concerns were being responded to, they were also likely to have reported that they felt that they were being listened to. Conversely, if they felt that their concerns weren’t being responded to, they were also likely to have reported that they weren’t being listened to.

 

Interpretative Analysis

What follows is our interpretative analysis from the perspective of our experience and expertise. It is quite legitimate that you may have an alternative view and we welcome your insights and perspectives. Your contributions will add richness to our collective wisdom.

People who reported that they thought that the objectives of the change were being met also reported that they received relevant information about the change, that their concerns were listened to, their concerns were responded to, that change planning and implementation was effective and that milestones were celebrated.

Positive feelings were associated with receiving relevant information, concerns being listened to, that change planning was effective, that they were able to influence the change process and that the change was meeting its objectives.

As change practitioners, we frequently advocate for greater, more meaningful communication throughout change processes. The data points towards the significance of listening, responding, and involving people in change processes if we want to achieve our change objectives and maintain the positivity of our people. Effective planning and implementation appears to be equally important and are complimentary to engaging our people in the change effort.

Change practitioners may look at this relationship diagram and shrug their shoulders – ‘of course, we know this’. We may know this through our expertise but there is now additional evidence through the data that supports our wisdom.

We will purposefully restrain from further analysis and interpretation at this point to allow collaborative input and for you to share your insight from your expertise in the comments area.

 

Stats stuff

Stats

 

n=189; N>20,000; E=6%; c=0.9

 

 

 

 

1Correlation ‘strength’ is based on Evans’ (1996) suggestions of r: · .00-.19 “very weak” · .20-.39 “weak” · .40-.59 “moderate” · .60-.79 “strong” · .80-1.0 “very strong”.  Evans J. D., 1996, Straightforward statistics for the behavioral sciences. Pacific Grove, CA: Brooks/Cole Publishing

 

It would be great if you contribute to the data collection. The link to the survey and to share with your colleagues is here: http://goo.gl/forms/XWiSg0HvlR

 

 

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