American Football is a metaphor for the nation it represents. It is a collective sport, but where individual prowess differentiates the competing teams; it is violent and brawling and yet sublime in execution; it is raw and refined. A perfect contradiction. And it allows us to do and watch warfare without the war. It matters precisely because it doesn’t.

And yet it seems that this is no victimless pursuit. Paradoxically those who gain the most financially may have the highest risk of premature brain deterioration. And yet, these same individuals are also likely to gain increased self-esteem and confidence compared to their peers. Until the advent of Big Data, there was no way economic way to harvest and interrogate the statistics to help, for example, the parent of an 8 year old, whether to choose say football or basketball as school sport. Now, however, most of us have access to machines with as much processing power and speed as existed in the entire world less than 60 years ago. So why not use it to help make everyday decisions which we have traditionally based on gut feeling or conferring with an intimate or close friend.

It would, for example, be relatively straightforward to collate data and meta data from research into the likely physical, financial and psychological outcomes of starting to play football at 8. The axes could include earning potential, self esteem, finishing age and brain damage. It might look something like this:

Football Experience Outcome Correlator

football correlator 1

This could act as a crude, but perhaps broadly realistic predictor of long term outcome of a crucial but poorly data informed parenting decision.

In the same way, the vulnerability of hazardous process plants to significant loss of containment incidents can be plotted. There is a correlation between readily harvested site metrics and the likelihood that a major incident leading to injury or fatality is experienced. These include:

  • Application of an Effective System for recording and recycling learning from ‘near misses’
  • Experience of a major LOPC in the past year
  • Experience of a major LOPC in the past 5 years
  • Exclusive reliance on Lagging PS Indicators
  • Sharing of PS Incident information within organisation
  • Sharing of PS Incident information within industry
  • Application of an independently validated Process Safety Methodology
  • Undertaking of Process Safety Training for key staff at least annually
  • Carrying out of planned audits and safety drills at least annually
  • Carrying out of surprise audits and safety drills at least annually
  • Inclusion of at least one board member with a specific Process Safety Accountability
  • Use PSSRs for all major restarts
  • Operating a Legacy Facilities HAZOP schedule of not exceeding 5 years
  • PS related site docs (PFD’s, P&ID’s, Hazardous Area Drawings, Key Single Line Diagrams, Escape & Evacuation Routes, Fire & Gas locations & layouts etc) reviewed and revised on an annual basis
  • Availability of Emergency Lighting on site
  • Existence of Emergency Egress Routes on site
  • Onsite Fire & Gas systems tested annually

The answers to these questions then become the input to a program which applies the relevant data to rate said facility for incident (and therefore cost) vulnerability. The outcomes would look something like this:

  • Elevated Risk of PS related fatality within a year
  • Elevated Risk of PS related fatality within 5 years
  • Non-elevated Risk of PS related fatality. Keep vigilant.
  • Congratulations! You are a PS Exemplar and are automatically shortlisted for the prestigious PSM Awesomeness Award

I call it the Process Safety Sensibility Index.

Hell, if we can easily corral Big Data for something as mundane as saving 50 quid on your car insurance, just think how valuable it could be if applied to help Johnny’s mum make an informed life decision or Johnny’s dad come home from work alive.