Not these boring spaghetti all over again….

picture by Rachel Ray

Roberta Amaral de Andrade from Brazil used Net-Map to get a better understanding of ” conflicts and opportunities for developing Jequitiba’s Forest Settlement Project”. She took the time to write a reflection  (323 KB) of her experience and allowed me to share it. Two of the struggles she describes are actually rather typical, they are things that often happen to us in our pre-tests so I’ve developed some ideas of how to deal with them so that they aren’t carried over into the actual research.

Let’s call the problem:


Your interviews are boring (for your interview partner and after the first three or so also for you) because the maps are all more or less the same. And they look like a bowl of spaghetti, because there are so many links between the actors. Drawing the links takes up a lot of time but doesn’t generate much new insight. So your data doesn’t tell you much beyond, well, everyone somehow interacts with everyone, but it is also a pain to collect, because it takes hours to draw and even more hours to enter the data.

What happened? I would guess you asked commonly known and agreed upon networks and / or low effort links. Low effort links are for example “exchange information” while a high effort link might be “gives money to” or “fights with”. Commonly agreed upon links are often those that are formal (such as “reports to”).

So why, if I know this can happen and I claim to have a remedy for it, do we commonly run into it in our pre-tests? That’s because you have to know the specific situation, to actually know which links are boring or common and how far you have to up the stakes to get to something more interesting. And to get a first overview over the situation, it makes a lot of sense to look at the formal hierarchy system, general information exchange and similar links that are boring and / or cumbersome if done too often. But if you see that it’s just boring spaghetti all over again, see how you can make it more difficult for your respondent do connect actors with links:

  • ask for more specific links: instead of “information flow” this could be “research findings”,  “information about farmer’s performance” or “information about corruption”.
  • ask for less formalized links: that’s why you do interviews instead of reading a document, because the different interview partners can tell you about the kinds of friendships, family relations, work coalitions, enemies and information shortcuts that an outsider can’t see.
  • ask for links that take more effort: we can greet a lot of people each day but won’t be close friends with all of them, we can give presentations (share information) to a big group of people but will only work closely with few… If the links you ask for require more effort, you will be less likely to link everyone to everyone.
  • ask for very different links: I have spent a lot of time drawing funding links in one direction and reporting links between the same actors in the opposite direction… if you realize that two links appear together most of the time, just ask for one of them and substitute the second one for something completely different.
  • ask for hot links: When pre-testing, observe which issues (links or aspects of the discussion) heat up the discussion and add some spice to the interview. Follow your intuition and look for things that stir up the interview, that confuse you or make you curious.
  • ask for riskier links: this is a recommendation that you have to follow only very carefully, depending on the trust you can develop and the openness with which your interview partners can talk, but sometimes it has proven very interesting to ask for “who annoys whom” or “where are informal money flows”

One final recommendation: Pre-test and take your pre-test seriously. Be aware that you might not know which questions to ask before you actually asked them. It’s so much better to change your questions after a pre-test than to collect a set of boring spaghetti data.

Sum it up

Some weeks back I had a great discussion (or two…) with Siraj Sirajudin of Influence and he was excited about Net-Map. We drew a map about a change process that he facilitates at the moment and came up with a little powerful innovation in the corner of the map. The major driver or draw-back of change processes is the buy-in of those involved. So after adding actors and links to the map the obvious goals to add to the actors were whether their attitude towards change was supportive, neutral or negative. So far, so standard Net-Map. But then we wondered: “So how many people are for or against us, and how powerful are they?” And added a little calculation to the corner, adding up the numbers of individuals in each camp – and adding up their influence towers. So if you stacked all influence towers of the nay-sayers on top  of each other, how high would the resulting super tower be? A little calculation that you can do right there at the table with your participants, and that can have an extremely eye-opening effect. And, as Siraj rightly remarked, sometimes the neutral ones can be a bigger problem than the outspoken opposition.

Can it be new if it makes so much sense?

I know there is even a name for it (but have forgotten what it is called): Sometimes research findings make so much sense, that everyone afterward says: “Well, that’s no surprise, I could have told you that… why did you have to waste so much time and money to find out something that is just common sense?” Well, maybe not everyone says it but you can see it on the faces of even your more polite listeners. And maybe they are right and you have come up with a finding of the innovative power of “Water is wet.” Or: “Wheels are round.”

But it might also be that you just found out something that makes so much sense that it feels to your audience like they should have known it before… even though they didn’t. There is one very easy way of finding out whether you learned something new or something old when drawing Net-Maps: Do a test run before going to the field. Draw a map of how you guess it would be. Sit down with the whole research team to draw a map. Or do it with your client, if you do this research for someone else. Maybe you can even convince the guy who always says “Well, we knew that before…” to sit with you and draw a map of what he actually does know before.

In most cases you will find out (and your audience will as well) that you/your client/your audience didn’t know beforehand what afterward they thought they did. And while it is great and lends a lot of TATAAA to your research, if you can come up with the unexpected, most of the things you will find out (in any field) are things that make sense and thus, somehow, feel familiar. And, honestly, isn’t it a good thing, if your findings make sense?

Other people’s thoughts…

On a quiet Saturday morning, my baby sleeps longer than I could hope for so I have a few minutes in which I could either finish a proposal, do the dishes or float around in the web, looking for one or two inspiring thoughts. By the fact that I am writing this post, you can guess, that the dishes are still dirty…

Viv McWaters
is always a good person to turn to for something to think about. Today I stumbled over the following:

“We act our way into a new way of thinking rather than think our way into a new way of acting.” Which Viv got from the Melbourne Playback Theatre Company

Then she refers to the Cynefin framework, stating that
“in complex environments, what’s needed are ‘multiple small and diverse interventions to create options.’ Probe – Sense – Respond.”

And as the third thought in this series of posts that caught my eye was her pledge to “stop interpreting for others”, that’s what I will do, and not go into lengthy explanation of what I think these things mean or should mean to you.

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?