We live in a data age. In fact, we have more data at our fingertips than ever before, and it would not be a stretch to note that most of us are drowning in it rather than putting it to effective use.
Despite this, people love collecting data and putting together reports – many of which are of absolutely no value whatsoever! But two inescapable things need to be understood before you can take data and do something useful with it. Interestingly, they both tend to head us down a discussion as to what “common sense” is.
So how can you make data your friend and put the “devil” in a backseat?
The first thing is to understand that numbers generated in an operation reflect actual, physical, real world events. They are not just numbers. Interestingly, many people see numbers (or key performance indicators) as some sort of abstraction, and don’t make a link between the number they see on paper (or a screen) and what that means in the field (or what needs to be done to change the number).
Secondly, numbers are only as useful as their comparison with something else (hence my comment earlier about “common sense”). By way of example, we regularly see haul truck actual payload figures on reports. This is a useless number unless the correct target payload is known.
{{quote-A:R-W:300-Q:"People love collecting data and putting together reports"}}If we told the management trainee that a haul truck had an average payload of 50 tonnes, we would probably get a nod of acknowledgement, but it is unlikely this number would mean anything to the person. Why? It’s because they likely have nothing to compare the figure against!
A much more useful number to record would be payload variance – so instead of saying the average payload was 50 tonnes, we said the payload variance was, say, minus 10 (in other words, the average payloads were ten tonnes light). This way, the problem is immediately apparent and action can be taken to resolve it.
Clearly, people do think this way – financial budgets are a good example of this, but beyond this area, effective comparisons can be hard to find.
One of the reasons for this is that, as an industry, we often don’t have the tools or the time to sit down and really determine what a system or process is capable of and then carry out an effective gap analysis to determine the difference.
For example, we have a client who has seen a consistent 30 per cent increase in productivity through exactly this type of approach.
No one in the business would have believed this was possible initially, and to those on the outside it could be similarly hard to believe – but not when you look at things from a “what is it truly capable of?” versus a “what is it currently running at?” type analysis, run by people who have a thorough understanding of what the numbers mean in real life and what is required to move them.
Thankfully, tools exist now to help us better understand what a system is capable of. The application of advanced scheduling tools such as Deswik.Sched can help us better visualise and determine how to quarry a deposit, the resources required to do so, the changes that should be made to pit shape and quarrying approach as the market changes and, most importantly, what the financial implications of these choices are.
There is a lot to be said for experience. Advanced simulation tools that help the experienced user look at things in new ways and “what if?” until an optimal solution is found are a “force multiplier” that can add significant value to the bottom line.
Perhaps the question we should ask is not “how did we do?” but “how did we do against what the system or process is capable of?”
You might be surprised by the difference.
