This ties in nicely with the concept of information as an asset. We're finding more people looking at data as an asset, so we need to make sure they see information through the same lens.
100% - thinking about information as an asset is where this post came from. I'm about to start a bit of a literature review of the work that's been done on information valuation, I think it's one of those areas that could really help us. It might also do us some harm - but being able to really strongly defend how much money we're spending managing our information - and tying that to a valuation seems like one of those things that we just have to do - even though it's really hard.
One of our challenges is that we have traditionally handled all information the same: whether it's high or low value, high or low risk - it all gets the same gold-plated treatment. The question is whether we can continue to do this. The alternate view is that we don't really know now the value of some of this information - it may be that in five years, things that we currently see as low value or risk have become incredibly important.
I think the evidence is in that we can't gold-plate everything. I'm also still prepared to be the house on the idea of the high quality information environment - the one that delivers information where it needs to be, and captures only to facilitate automation and organisation (so people want to do it, rather than forcing them to do it as a post-process). I also think that we can almost always estimate the largest possible downside - which is why I'm looking at FAIR risk management at the moment, I think it provides a way of getting to a realistic representation of what the statistical value of our information is - and arriving there by factoring in the combination of uniqueness and downside. It's an emergent approach - because it does require some existing information about failure rates to be useful, but I think we could pretty quickly get to a sense of an organisation and how often it gets things wrong (ultimately down to cultural factors) so that we could start to estimate new things.
This ties in nicely with the concept of information as an asset. We're finding more people looking at data as an asset, so we need to make sure they see information through the same lens.
100% - thinking about information as an asset is where this post came from. I'm about to start a bit of a literature review of the work that's been done on information valuation, I think it's one of those areas that could really help us. It might also do us some harm - but being able to really strongly defend how much money we're spending managing our information - and tying that to a valuation seems like one of those things that we just have to do - even though it's really hard.
One of our challenges is that we have traditionally handled all information the same: whether it's high or low value, high or low risk - it all gets the same gold-plated treatment. The question is whether we can continue to do this. The alternate view is that we don't really know now the value of some of this information - it may be that in five years, things that we currently see as low value or risk have become incredibly important.
I think the evidence is in that we can't gold-plate everything. I'm also still prepared to be the house on the idea of the high quality information environment - the one that delivers information where it needs to be, and captures only to facilitate automation and organisation (so people want to do it, rather than forcing them to do it as a post-process). I also think that we can almost always estimate the largest possible downside - which is why I'm looking at FAIR risk management at the moment, I think it provides a way of getting to a realistic representation of what the statistical value of our information is - and arriving there by factoring in the combination of uniqueness and downside. It's an emergent approach - because it does require some existing information about failure rates to be useful, but I think we could pretty quickly get to a sense of an organisation and how often it gets things wrong (ultimately down to cultural factors) so that we could start to estimate new things.