![A stakeholder table is a 3X3 grid](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEhW4pJIJHOSm2yeaik1tkCkn4E0aCyTNYldJTzWEgIGtVIQTQy0-xZ4xxx5hrkzV9-UBE3YHKYR0GHwtdRKwizgPnXXSoaCg-bytVBTEgJVdq2mA2ldsLejj-jNa_PfHhXAaRjCxxPqSZyg/s320/Grid.bmp)
To quickly recap, there are two types of tables in stakeholder analysis:
1. Effect versus Impact
2. Support versus Influence
The effect-impact table qualitatively assesses the contribution of a particular stakeholder to a quality improvement goal. The vertical axis represents the impact of the stakeholder, in measurements of "low", "medium", or "high". The horizontal axis represents the effect of the stakeholder's impact, in measurements of "negative", "neutral", or "positive".
Are admissions committees subconsciously making effect-impact tables when they predict the effect of an applicant's impact on their program? If so, how easy is it to make an accurate table? If not, what must tablemakers consider to ensure accuracy?
The support-influence table qualitatively assesses the contribution of a particular stakeholder to a quality improvement project. The vertical axis represents the influence of the stakeholder, in measurements of "low", "medium", or "high". The horizontal axis represents the support of the stakeholder's influence, in measurements of "negative", "neutral", or "positive".
Are patients subconsciously making support-influence tables when they evaluate the support of a provider's influence on their health? Since physicians are stakeholders in the quality of patients' lives, what can we learn from putting ourself in someone else's table?
The difference between these two stakeholder tables is subtle. One difference is the ability to specialize the impact-effect table by defining the impact according to the quality improvement goal. For example, when a physician is the target stakeholder, the particular impact may be defined by years of clinical experience, effectively creating a clinical experience-effect table. Or, maybe the impact is defined by average patient-encounter time, effectively creating an encounter time-effect table. Furthermore, multiple definition metrics can be used simultaneously.
-Brian Blaugrund