The fact that 'Lies, Damned Lies and Statistics' is a phrase that has been in use for more than 100 years is perhaps an indication of the abuse to which data has been subjected in public discourse. We are by turns exasperated, decieved and baffled by the incessant quoting of percentages, putative correlations and trends by politicians, journalists and pundits, which we then sprinkle into our conversations (tweets, facebook updates) in more or less thoughtful, balanced ways. Usually less.
If we are to harness the potential of open data to allow us to ask better questions, and make better choices, we need to consider what kinds of conversation allow us to reach an informed consensus, rather than afford 'victory' to the most skillful orator with the weightiest arsenal of 'killer stats'. more >
This post has the potential to come-over all Rumsfeld with ‘changed changes’ and ‘changes changed’, but it focuses on articulating the context for changes we’re trying to bring about through the appropriate use of digital technology.
Early next year Nominet Trust will be working with 10 Charities to explore how open data could enrich their work - and how their own data might bring our image of society into sharper focus.
Seeing pictures, it seems, is a deceptively tricky business. Leonardo Da Vinci suggested we might look at a stain on a wall and see "heads of men, diverse animals, battles, rocks, seas, clouds, woods and similar things". Our imagination can powerfully alter the mental image we create for ourselves: what we see is only partially determined by what we're looking at. Crucially, our imagination is directed by our intention: a professional Renaissaince wall-cleaner, for example, might have seen in Leonardo's stain only an embarrassing mistake (or a business opportunity). more >
If you’re looking at social returns on investment (and I mean the social returns, not the financial proxies of social returns) then you get to the point where you start to wonder, what is the social value that is being created by all the amazing work that our partner projects are doing? And, come to think of it, what does everyone mean actually by social value anyway?
After all, those crazy kids in the financial world have been working on ways of articulating (financial) value for several hundred years. So as a sector, there’s no shame in the spending some time developing our understanding of social value.
If you look at any of the partner projects we are working with, there’s no question they create heaps of social value. But how do we account for it? How do we understand it? What means do you use to capture it, express it, aggregate it and (dare I think it), compare it? As a sector, we still seem to be stuck on a financial understanding of social value, mostly famously of course the SROI approach. (While I think the guiding principles behind SROI are useful, it does have limitations. more >
I had a very interesting chat the other day with a researcher. I won’t say who, and I won’t say where. So essentially this could be part of an elaborate storytelling ploy.
It centred on why we are using logic models and theories of change as the basis of our new evaluation strategy when they’re not perfect tools to understand change. At least not when compared to deep, longitudinal ethnographic research.
As anyone will tell you, whether they are a secret evaluation geek or not (just me with my hand up?) evaluation can be a bit tricky. The fact is human and societal change is complex and messy. But if we want to progress our field, like any field of endeavour, we have to learn from what we have done to move forwards. more >
