In the art world, knowing the provenance, or the ownership history, of a piece of art, is critical to establishing its veracity and value. The same should be true of any ‘fact’ that you wish to use to support an argument in asset management. We speak of ‘evidence-based’ decision making, but how valid or reliable is our ‘evidence’? In other words, how do facts become facts? As you think about this, consider the following:
I had been asked to review a paper about disability access and the author was keen to get my comment. As I read it, I noted his use of substantial and very favourable benefit-cost figures. Knowing how difficult it is even to conceptualise some of the benefits, let alone measure them, and finding no explanation of the figures in his paper, I ask him for the source.
“Oh, never mind that”, he airily replied, “what do you think of the paper overall?
I told him that I wouldn’t be able venture an opinion until I understood the data and, after a fair amount of applied pressure on my part, he eventually said:
“Look, I made them up! But it doesn’t matter because I am giving this paper at an international conference and someone will quote me, and then someone will quote that person – and pretty soon, it will be fact!” Unfortunately, this is a true story and he may not the only one acting in this manner.
Much of the time, however, mis-representation is not as blatant as this. It can be simply a matter of not paying enough attention to labelling the axes. Often we slap up a graph without identifying the axes and expect the audience to fill in the gaps from the context of the conversation. This is a lazy habit that is responsible for many subsequent misunderstandings. For example, what we think is a trend line showing full life cycle costs, might simply be a trend of operating costs. With very different implications!
What other examples do you have where presentations or papers, have or can be, misinterpreted with ill effects on Asset Management?
“Asset Management professionals claim “Preventative Maintenance” would reduce “Reactive Maintenance” interventions and save maintenance expenditure in the long run. What kind of data and facts are available with Asset Managers to make this blanket declaration?
There are too many variables here. I managed assets for many decades. By experience, I know that the above claim is valid only for certain assets associated with certain conditions.
If the asset is a machine, this declaration can be proven by predictive modelling using he machine failure data on a machine of the same brand, same age, same usage hours, same operating environment etc. However, even in case of a machine, if the cumulative preventative maintenance costs over a period is higher than the value of a new machine, the wait until the failure, would be a better option. It is a matter of anticipating the failure and have pre-plan to ensure a quick replacement reducing the down time.
In case of a building which is consisted of many major components of different useful lives, preventative maintenance may not necessarily reduce reactive interventions when the building is in last quarter of its useful life.
The asset management professionals even talked about 80%-20% split on “Preventative: Reactive” as the best practice target.
However, they conveniently disregard to mention that this split is about maintenance activities rather than dollar value of the maintenance activities. It gives wrong message that asset owners should spend 80% of maintenance budget on preventative maintenance to get the best practice results. We need data and facts per asset to make a declaration and the declaration would only be relevant to the particular asset.