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The key issue (I would go as far as to say the over-riding issue) about getting indicators into common use is the widespread negative perception by field operators. Mention indicators and the reaction is something like "that's all nonsense, no-one in the field has time to go around collecting page after page of data that is never going to be used anyway". This is almost a direct quote from a reaction I had from a colleague who is relatively positive about GIS and other technology, and seems to sum up the most common reaction.
As a result, it seems likely that the biggest problem to overcome is perception and acceptance, and technical issues are secondary. In terms of an approach this means things like:- * go for quick wins with indicators that may not be overall so useful but are very easy to data collect and produce obvious results- * try to find out what the biggest issue that needs addressed is (i.e. which indicator is most requested) and decide if this is a feasible problem or not. If not feasible then ruthlessly set it aside and look at next most urgent. What we choose _not_ to do is going to be important. (ref to Steve Jobs: there is no shortage of very good ideas, but you have to say no to all of them if you are going to work on the best ideas). - * in looking at indicators from other parallel development areas, we should focus not on the "technical" fit of the indicator to mine action as our first criterion, but at how well the indicator is accepted in the field. Build up a library of these and then look for common factors and characteristics in why and how they are accepted (and also maybe the timescale and process from first use to acceptance). If our main problem is perception then that must be addressed analytically as far as possible.
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