humanitarian.info

Alertnet carries an interesting poll on the future of aid, the results of which are revealing in ways not necessarily intended by Alertnet or their respondents. In response to my comment that it was really interesting, and really wrong, Frank replied: “not sure I understand the “really wrong” comment. Is the data itself wrong? Or something else?” So here goes…

The first thing to note is that it has the interesting title “Where is the Money?”, explicitly tying the future of aid to the financing of aid. We can all agree that funding – both the amount and the sources – are vital to humanitarian aid, but it worries me that discussions about the future of aid might be reduced to a discussion about finance rather than principles.

The second thing to note is that the poll shows that the aid community is as unimaginative as the rest of the population. There’s no shame in that, but it does show that we need a bit more grit in the vaseline. If we’re responding to disasters, we need to actually predict disasters, not just predict business-as-usual with a few extra people living in cities. A word from Noah Raford:

In the end, futures work is rarely about accurate prediction. It is almost always about staging a useful intervention which encourages discussion of the most challenging aspects of the present… The best futures projects take on difficult subjects of today, cast them forward, then reflect them back upon the present in order to make them discussable, now.

The problem with the Alertnet poll is that it does take on difficult subjects of today but it fails to cast them forward. What do I mean by this? The poll notes that one factor increasing humanitarian need will be high and volatile food prices, which is true; but it’s been true for the last four years. Another factor noted is increased urbanisation, which is also true: but 50% of the global population became urbanised in 2008, so that’s also been true for at least the four years¹.

The same is basically true for every single item on this laundry list of future problems. They’re all problems that we should have been planning for ten years ago, have only recently noticed that they’re a big deal, and are now assuming that those are the problems that we’ll face in the future. In military terms, this is what’s referred to as “fighting the last war”, and it’s generally agreed to be the quickest way to lose the next war.

Exhibit A: the factor deemed likely to increase humanitarian need was an increase in climate-related disasters. The reason for this selection is that climate change is now the dominant meme in environmental circles – which isn’t to say it isn’t important, but it might not be important in the way you think.² Exhibit B: The biggest challenge to the delivery of humanitarian aid was thought to be the politicisation of aid. The reason for this selection is the war on terror – but the politicisation of aid is baked into the aid industry, and calling it a “challenge” completely misses that.

I could go on, but hopefully you get the point. The reason why this Alertnet poll is wrong is not that the responses are “wrong” – they accurate reflect what people believe to be true – the problem is that what they believe to be true is wrong, in the sense that it doesn’t actually reflect the future of aid. Visit the site, read the results and watch the video anyway: it’s still interesting, even if it’s wrong.

And now, a vision of the future we definitely won’t get:

1. In fact urbanisation has been a critical issue for much longer, but completely overlooked due to the rural bias of traditional livelihoods interventions. [↩]
2. There are a whole host of environmental problems that are not necessarily climate-related (eutrophication, topsoil degradation, deforestation, you choose) or that are climate-related but don’t come at us from the obvious direction of “more flooding!” Boy, am I looking forward to the first famine due to ocean acidification. [↩]

In a couple of previous posts, I outlined why I think open data poses serious difficulties for the humanitarian sector. A lot of those difficulties stem from endemic weaknesses in the humanitarian sector, because at root I believe that failure has been built into the humanitarian system, and I really need to get around to explaining what I mean by that. That can wait for next time, because right here I want to lay out what I think needs to happen if humanitarian organisations are ever going to survive the changes that the information age has brought, as it relates to using data effectively.

Two things to bear in mind. First, that this is taking the perspective of organisations as they are now; but I also think that organisations will evolve into new forms in the course of this century, a greater variety of forms than the traditional “corporate” model allows (and yes, most NGOs are set up on a corporate model). Second, that all of these steps are not merely realistic, they’re actually relatively easy, and especially relatively easy compared to the path that most organisations are currently taking. The reason that they’re not being widely pursued is that they emerge from a view of the humanitarian system as just that – a system, with multiple interacting layers – rather than as a hierarchy reaching from global headquarters down into “the field”.

Training

1. Create freely available training modules and support material via e.g. Moodle, so our staff can start doing it for themselves. Then open up that training material so that anybody can benefit from it – local government, local NGOs, affected communities, national universities, anybody.
2. Create an accreditation system for info management trainers, initially based on prior experience. Don’t accredit people in “information management”, they can do a university course if they want a diploma; but accredit trainers so that you can reach into the professional training community.
3. Run facilitated online and onsite courses, provided by accredited trainers and leading to accreditation for participants. Okay, I lied – it’s okay to accredit people in information management. The reason that I hesitate about this is because accreditation only really works if there’s an infrastructure around it that recognises and value accreditation.
4. Integrate accredited info management course into existing accredited programmes (e.g. RedR, Clusters, etc). This step deals with that infrastructure issue, but only to a certain extent. There’s a lack of recognition of “management” a professional skill in the sector, which is always going to work against us.

Data sharing

1. Establish data standards, mainly to stop the UN agencies from dicking around with their data and refusing to agree on e.g. basic demographic categories. Data standards are not complicated but they are difficult, especially when people don’t get the basic point. It’s a minimum set, not an exhaustive set; it’s for practical implementation, not policy roll-out.
2. Adopt common data sets and agreements on e.g. which population figures we’re going to use. OCHA has done the groundwork on Common Operational Datasets (pdf), but I don’t know what the latest state of play is. What I do know is that by this point there should be an online interactive map with those datasets easily searchable behind it AND THERE ISN’T. ; the next step is working out how to leverage those datasets more effectively in the field to create better decision-making tools. (Thanks to Ben in the comments for correcting my ignorance, and my apologies for shouting at OCHA when I really should have checked my own bookmarks folder – and well done to all involved.)
   
3. Begin capacity building from the field-level up in managing data and using information more effectively. I can’t stress this enough – all capacity building should start as far out on the “edge” of the organisation and work inwards, not the other way around.
4. Lobby from the HQ-level down on integrating actual information into decision-making. This is where HQs have the requirement – not for info management skills, but for decision-making skills based on good info. Don’t bother sending managers on info management courses, they’re never going to be crunching spreadsheets; they need to be able to read spreadsheets and connect that with their actual work.

Advocacy

• Operational level – lobby to solve location-specific data issues using time-limited task forces, as a way to raise awareness that IM is essential for decision-making.
• Country office level – lobby to create better environments for information management within organisations and meetings, focused on staff not technology.
• Head office level – lobby to integrate data into decision-making, and for HQs to make reasonable and informed calls about what information they’re requesting from the field.
• Global level – promote of data standards, CODs and capacity building strategies, and stop having high-level meetings that pretend to be designing tools for the field.

Most people think setting principles out and getting agreements down is important. I don’t. I would drop having principles in favour of signing up agencies to a ‘pathway’ of simple practical steps which incorporate the principles at an implicit level. Introducing principles makes it possible for everybody to nod their heads at the next meeting and then do absolutely nothing to follow up. And finally, that Shorty Long track at the top has literally no relevance to the blog post, except to the extent that I believe that I AM DE JUDGE.

“I have talked to teams of students designing new de-mining tools without ever having visited a mine field, students designing tools to make charcoal without understanding how poor people improve their incomes by selling the charcoal briquettes they make, and teams of students so convinced that they will create the next revolutionary product and make a fortune doing it that they forget to talk to the customers they are designing for. If these patterns of design arrogance and lack of respect and curiosity about customers and markets become institutionalized in the hundreds of new courses now springing to teach design for the poor, their impacts will be just as trivial as design for the rich.”

- Paul Polak, The Life and Death of Big Institutions

Some people thought that my previous post on needs assessments implied that I’m really unconvinced by open data. Surprisingly that’s not the case – I know, even I was surprised that my curmudgeonly instincts failed to kick in – I’m pro-open data, although I’m typically European in being sceptical about the scale of the potential benefits. The reason that I’m pro-open data is that it’s increasingly clear that governance systems in general are unable to cope with the complexity of post-industrial organisation. We need new forms of governance, we can’t rely on our governments to generate those forms themselves, and the decisions of an informed public are the only possible source of legitimacy.

Having said that, open data in government 2.0 [Wow, has that term dated quickly.] does not necessarily mean the same as open data in the humanitarian sector; importing of principles and approaches wholesale from one sector to the other is almost never effective. In more practical terms, if governments are already signing up to release their data in general, that already covers data that might be deemed humanitarian specifically. There is almost no data which can be labelled solely ‘humanitarian’ [most of it relates to population movements] and there’s an increasing amount of ‘development’ data online. Since we’re already seeing a big push in the open data movement globally, I’m content to let that play out rather than try to shoehorn it into the humanitarian sector.

While we are seeing is movement in open data on the development side, that seems to have translated into more transparency regarding development finance, rather than a push to turn everybody into Hans Rosling. Rosling’s work is fantastic, and has done a lot to raise the visibility of development issues, it’s not intended to provide serious tools for decision-making at the national or regional level; the data simply isn’t detailed enough. That’s changing, and will continue to change, as the Age of Big Data bears down on us; but Big Data doesn’t resolve policy issues, and technocrats are often misguided in their expectations.

So what do I think open data can achieve? Simply put: more effective assistance to disaster-affected communities. What sort of data do we need to achieve that? Equally simply: operationally relevant data. I don’t care about data being shared as much as I care about data being collected; you can’t open up data that you don’t have, so our first priority should be getting decent data in the first place. The problem at the supply end is the lack of systematic data collection, which needs to be addressed with better survey work; and data should be collected solely in order to facilitate better decision-making – there’s no other reason to collect it. If that data isn’t being used for decision-making, then sharing it is irrelevant, which means that advocacy for and training in using data for decision-making is a higher priority than making data open right now.

The next consideration is that there’s always a cost to sharing data: although that cost has become substantially lower (great job, internet!), it still exists. Do the benefits of sharing data outweigh the cost? Please don’t argue that the costs are neglible, because they’re not – it’s a massive investment in an organisational change process just to get on the first rung of data sharing, there are lots of technical costs, and the potential for disaster is high (as the UK National Health System can tell you). I think the benefits outweigh the costs, but we need to build a stronger case than currently exists, which means we need to do a better job of drawing the dots between data and impact.

And this is where it gets tricky. Government 2.0 is all about transparency and accountability, and Development 2.0 is an extension of that, with an additional component of aid effectiveness. I would argue that this effectiveness component is much, much more important in Disaster 2.0 (ha!), but there’s also a tension around the role of government that a lot of people are in danger of missing. Hopefully everybody can agree that the big push for better data needs to be at country level – but humanitarian organisations frequently have a more adversarial relationship to government than UN agencies. We can’t expect MSF to participate in open data sharing with the Government of Sudan.

This isn’t just a question of context, this is a question of ensuring that humanitarian principles are preserved in any data sharing agreement: for example, if neutrality is in tension with transparency, which principle wins out? That’s a question that the current discussion around open data has simply not addressed, but it may turn out to be the most important question of all.