Adding, dividing, averaging power?

In our IFPRI project about “research into policy making” in Malawi we drew NetMaps with people who had very different levels of detail when describing the policy landscape. Some just talked about “the” Ministry of Agriculture and Food Security, while others divided the ministry in several divisions and even individual positions. If we want to compare the data between interviews and especially the influence assigned in influence towers, we have to find a rule how to merge these detailed descriptions into a common influence value for the whole organization. How do we best do that? How about adding up all the influence values we got for parts of the Ministry, so that the Ministry’s influence is the sum of it’s pieces? Let’s think about what that means: If someone mentioned every little department of the Ministry, separated the cleaners, the drivers and their grandmothers, gave all of them a medium or low influence tower, then summing all of them up, would give this Ministry a lot more power than in a comparable interview where the respondent just talked about the Ministry as a whole. Even if you disregard the grandmothers…

Now how about using an average influence value? Our definition of influence is that someone (or an organization) can achieve their goals in a social setting, even despite resistance. Let’s look at the complex respondent who includes a lot of irrelevant or lesser actors to the picture: Does the fact that the Ministry has a lot of drivers who have nothing to say decrease the ability of the Minister (or Permanent Secretary) to make things happen? That’s what you assume, if you take the average. There might be special cases where that is true.

But mostly it seems to be the most reasonable approach to assume that an organization is a powerful as it’s most powerful part. So use the influence value of the most influential department to describe the influence of the organization.

Can you think of cases where this is not the case?

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