We covered few key topics that required a lot of thought. This group is tackling a really difficult topic in an industry that in the past has not really put in the effort.
There seems to be some issues on just getting off first base - i.e. agreeing on scope. There is an elephant to be consumed and it's difficult to know where to begin.
The OEMs seem to think that the raw data being collected by their on-board monitoring systems, particularly that involving the health of the machine, is competitive IP and they do not want to part with it, even when the mining companies have purchased the equipment.
However I think that we're seeing the rise of big data / advanced analytics solutions that are able to balance the reliability of equipment with the production task of the equipment. Miners do this already with preventative maintenance aimed at optimised production. They will need almost all the data to do it properly in the future.
Without naming names, I happen to know that a major OEM has been having this argument with their largest mining client. However, because this client only represents 3% of their business, then there is not a lot of leverage that just one miner can have in this particular argument.
Another, point discussed yesterday was that unless we drill right down on an issue, we will not actually do anything useful. I agree, and I believe this is often best done by what I like to call the pi shaped project. It's a variant of the T shaped project (which is more often referenced in the context of the T shaped person).
In a pi shaped project, the scope covers a broad range at a high level (i.e. in our case: data access and usage across all mining equipment) and then we drill down on just two key areas to the level of depth required to actually get something done.
By doing two of these at a separated scoping distance, we avoid just solving a specific problem in a specific way that cannot be easily translated to other areas (hence the scope looks like the greek letter pi). That is, by doing two focus areas at once, we can see what issues are common to both as well as what is specific to each domain.