The ingenuity of Julian’s undemocracy.com, which slices-up debates in the UN General Assembly and Security Council into a usable form, is making it ever harder to put up with some of the UN’s websites.

One particular offender is this portal set up by the Human Rights Commissioner to provide information about the sessions of the Human Rights Council’s Universal Periodic Review of Human Rights (UPR), a diplomatic speed-dating process for states to assess each other’s overall record on human rights. The UPR’s novelties are the “interactive dialogue” between states, and the direct, mandated involvement of civil society organisations in the review process of individual states.

So, with all this novelty going around, might we see some innovative thinking about how to communicate the proceedings in a modern, web-savvy way? Hardly. Staffers have resorted to the double-sin of scanning in the draft statements of delegations and dumping them onto the portal as a PDF. Here’s a clip from the statement of the Bangladesh delegation in Brazil’s first review session:

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Perhaps a graphologist can help us read between the lines here, giving us unprecedented access into the minds of diplomats.

I’ve just finished writing up the Lessons Learned from the cluster experience in Bangladesh (only a little bit late…). It was harder than I thought it would be, because I realised that there were a number of different potential audiences for the Lessons Learned, and each audience would be expecting something slightly different in terms of recommendations. Ironically this is quite a common problem that I have when trying to develop an information product - different people want different things from it and, as any fule kno, you can’t fool please all of the people all of the time.

What was depressing was that most - if not all - of the lessons that we identified are ones that we should already have learnt. Many of the things we were writing were things that I’ve written before, in one place or another, but particularly in relation to the Humanitarian Information Centres. Really obvious stuff like - target information products effectively! Pay attention to information at the sub-national level! Maps are more effective than other products! Invest in data preparedness! And so on, and so forth.

What prevents me from falling into depression is prozac the cluster approach. Since the cluster lead agencies have very specific responsibilities and tasking, and since part of that is related to information management, there’s actually a vehicle for getting these lessons incorporated into (for example) training exercises, which means that they’ll live beyond the document itself. This is the single biggest problem with Lessons Learned (and evaluations, and after action reviews) - whether they are actually learned. Or not.

Once we’ve agreed the Lessons Learned, I’ll see if I can get the group’s approval to post some of it here. Then we can come back to it in a year and see if anything’s changed, right? Accountability Joe, that’s me.

In the last few days of my mission to Bangladesh, I chaired a meeting of the Information Management Working Group in Dhaka, at which something curious and exciting happened. The Group is comprised of representatives from each of the clusters, the CDMP (a government body) and usually a couple of others (today, CARE - it’s really just a place to reach agreement on basic issues like geocodes.

But in the meeting we actually agreed that all the clusters would pursue a policy of open data - that all data collected during assessments would be shared in its raw form as soon as the collecting organisation had published its own report, through the offices of the Disaster Management Information Centre (DMIC).  This will make it possible for other agencies to incorporate that data into their own analysis, enabling better cross-cluster co-ordination.

As far as I know, this is the first time that this has happened in any humanitarian response operation anywhere (I could be wrong).  It could be that the cluster leads won’t be able to live up to this commitment, since there are all sorts of internal agency constraints.  Nevertheless I thought it was indicative that we are moving in the right direction, and that alone made my work in Bangladesh worthwhile.

The single most important co-ordination tool that you will find in any humanitarian response is the Who’s doing What Where, better known as the W3 or 3W. This is the basic tracking that shows which organisations (who) are doing which activities (what) in which locations (where). It comes in a limited range of flavours, and it’s usually a spreadsheet with a simple matrix by location.

For some reason, here they’ve decided to add an extra W - When. I have no idea why they decided to do this, since we’ve never been able to successfully get the first 3Ws; the decision was taken before I arrived, and I would have fought tooth and claw to stop it. To be fair, I’ve been asked for a chronological component in other places, because it’s really useful to know what plans organisations have.

The problem is, I think the W3 sucks. To be more precise, I think our current approach to the W3 sucks. Why do I think so? Because it never bloody works, that’s why. I’ve been through this process in every emergency I’ve ever worked in, and I’ve never seen it work. Sometimes we’ve managed to fake it, but that’s not the same thing as having a really solid information system that provides useful analysis.

There’s no doubt that knowing who’s doing what where is essential to coordinating a humanitarian response, so we need to rethink the entire thing urgently.  I chaired a meeting of the Information Management Working Group yesterday, and we reflected on the problems that we’d had implementing the W3 and how we’d dealt with them.  That will go into a longer document that Neil Bauman and I are going to write up, but here are the headline problems for me right now:

a. We set up templates for people to fill out, but they never use them. This is because the forms don’t resemble anything they use internally for planning their activities, and they don’t have a good reason to fill out our forms in addition to their own.

b. When they do use our formats, they inevitably fill them out incorrectly. This means that you have to work out what on earth they were trying to tell you when they were typing out their information. Is that really 18 water purification plants in one union location? Surely not.

c. We ask for quite a high level of detail - in my opinion, an unreasonably high level of detail - without really asking whether that much detail is useful.   As a result, people are often put off by the thought of that level of reporting - particularly if their own organisation doesn’t ask them for that much information, why should a co-ordinator?

d. As a result, most of the time we just get the information in whatever format they have with whatever detail they have it in already or can be bothered to submit it in. This means that we have to shoehorn it into our format (usually unsuccessfully) and then pretend that we’ve got some useful data.  In reality, the coverage is patchy at best and the accuracy is questionable - by the time you’ve typed it up, it’s already out of date.

e. A lot of the time - especially in the early stages of a response - people simply don’t know exactly what their organisation is doing. They know roughly what activities their organisations are going to undertake, and in roughly what locations, but precision is not their usual frame of mind.

Having said that, it’s clear that people and organisations do plan their activities, so the question is - how do we get a better picture of what they’re doing? That will probably be the subject of my next post, once I’ve finished cutting and pasting NFI distribution data into this bloody spreadsheet for the meeting today.

There’s inevitably a data drought when you’re working in an emergency in a developing country - either the coverage isn’t good, the historical record is patchy or the accuracy is questionable. In many cases, the data simply isn’t there - nobody has collected it in the past or is collecting it at present. Where they are collecting it, the collection process often isn’t systematic and the results are in formats that aren’t easily shared - where people are willing to share their data, which they often aren’t.

In my last blog post, you might have noticed that we were trying to identify water scarce unions. There’s no actual data on water scarcity, though - it’s not the sort of thing that anybody has ever measured in itself. So how do we work out which locations are potentially water scarce?

What we did was use a proxy - a set of data that we do know that can stand in for what we want to know. In this case, we had a list of unions where tube wells aren’t feasible - derived from a couple of phone calls and some photocopied sheets. Tube wells are the primary means through which the government delivers water to communities, due to the nature of the ground and the groundwater (particularly when you’re close to the sea, salinity is too much of a problem).

Where tube wells aren’t possible, we assumed (and it was an assumption) that there would be chronic problems with water supply - problems that would have been exacerbated by Cyclone Sidr. These are the locations where the humanitarian community needs to make sure that alternatives are available - for example, water trucking to ensure a supply line, even if it isn’t sustainable - and to allocate resources for rehabilitation, particularly rehabilitating the ponds that local communities rely on where they don’t have tube wells.

Now I freely admit that there aren’t many people who are as fixated on data quality and quantity as me - most people are busy actually implementing programmes rather than crunching numbers. Yet it’s something we should be concerned about, because if we don’t accurately know the numbers and locations of people in need, then how can we possibly target assistance properly? If we don’t have good baseline data, then how can we know if our work has had any impact (especially where high poverty levels make it difficult to work out which problems are specifically caused by a disaster and how many were pre-existing)?

Last weekend in Barisal, I managed to get some vaguely interesting data that might help water and sanitation provision in the cyclone-affected areas of Bangladesh, and decided that it would work best on a map. Problem: no maps.

Sometimes you simply don’t have the resources to implement GIS in the field. The UNICEF office here is quite large, but there’s nobody who uses GIS the only people with GIS skills are too busy to work on this. I don’t have the time to set anything up (and I’m barely competent to do so); and even if I did set something up, there’s nobody to take it over when I leave (imminently).

I’d prefer to have some proper GIS going, but I’m not a purist when it comes to mapping. In the end, a map is just a tool, and if it does the job, it doesn’t matter what technology you use to make it. So I took the gif file maps which I found on the Government of Bangladesh website, inserted them into a word document, and then added a bunch of text boxes. The result? Scrappy maps!

Now these maps need some a lot of explanation, so every time we distribute them in meetings, we include an explanation note. However their main purpose is simply to provoke discussion and to encourage people to commit resources, so it’s important that they’re not seen as definitive. So what do they show, and why did we make them?

This is a map of Barguna District in Barisal Division. In the left-hand column there’s a list of unions (the lowest administrative level in Bangladesh) where it’s not possible to sink tube wells. We collated this list from the Department of Public Health Engineering, from telephone calls, and DANIDA, from some photocopied reports that I lifted from their office.

The data itself only tells us whether it’s possible to sink tube wells in a particular location - but we assume that if that isn’t possible, then the local people rely on ponds for their water needs. Given that most ponds were contaminated by the cyclone, that means that they’re likely to be suffering from water scarcity, which means that they should be a priority for relief.

The right-hand column shows the water supply activities that we know about (from our co-ordination meetings) and the locations where water trucking has been proposed (by our field teams). This list is very provisional, but it tells us roughly how much activity is going on in each location. If you match the demand (left-hand column) with the supply (right-hand column), you can start to see where there might be gaps in service.

So these maps can be used in meetings for two purposes. First, they give people an overview of the situation in a particular district, on which they can give their feedback. These maps could be wrong or misleading, and we want to hear if anybody has any corrections, comments or updates. Second, they give us a tool for co-ordination, helping us to make better decisions about how to respond to a particular issue - in this case, water scarcity.