Sunday, September 20, 2015

Data Nucleus

For a moment, look at Data as a Nucleus where Data is the Atom and the Variables are Negative (electron) charges or Positive (proton) charges, creating Data Nucleus. The atom, or data, is constant, while electrons and protons are variables. If the number of protons and electrons are equal, that atom is electrically neutral, and variables in the processes are predictable within standard deviations.
If an atom, or data, has more or fewer electrons than protons, then it has an overall negative or positive charge, respectively. Data is affected by variety of variables, with environmental and human factors as major contributors. Environmental and human factors are reliable unpredictable with only a short time-span when outcome is predictable.
Environmental and human variables shapes data nucleus. 
When conducting a risk assessment based on collected data, and predicting the future based on that data, is like collecting locations of marbles when they are dropped, and then applying assumptions that these marbles will duplicate exact same location every time. The purpose of risk assessments are to predict the future based on past history. This is impossible, since data which are collected are data nucleus, with variable forces at that moment in time. These variable forces do no carry forward with past data collected. Without applying current data nucleus, risk assessments are just opinions of common sense without future reliability.

Incorrect risk-based wildfire management is not management but opinions.
It is widespread knowledge that forests around the world rejuvenate themselves by burning fires. These fires are damaging with an extremely high monetary cost. Wildfires burns not only the forest, but destroy lives, homes, businesses, equipment, recreational structures and everything else that are in their raging path. Precision dispatching of wildfire fighting resources to predicted regions becomes highly important.
These risk-based dispatching decisions, which are based on recorded data from previous years, become assumptions and opinions unless data nucleus is applied to each data collected.


Tuesday, September 1, 2015

Testing Of Safety Management System (SMS)

Introduction of new equipment or processes is done with the expectancy that changes are improvements to increased productivity with a higher rate of return on cash invested. When new airplanes are introduced it is assumed that this will attract more customers and improve service in a competitive world. Airlines with an operational philosophy of high quality customer service have greater chances to attract more repetitious flyers and paint a positive image of the company.

A positive image sets the stage for success.
SMS is a risk-based approach to safety where risks are identified, assessed and placed into existing, or new operational programs. SMS is the management of variables in a Timing Management System (TMS). Timing of variables is a fundamental factor of risk management. It is irrelevant to safety-specific if an airplane is parked on the hanger line due to mechanical failures, but becomes relevant for the purpose of flight. If a crew is waiting for that same airplane to be airworthy, the issue of mechanical failure becomes a variable highly important to safety.

A change-management system must be in place for tabletop exercises and testing how changes affects SMS operational systems. When introducing changes as new equipment or processes, scenarios are configured and played out to establish the risk-factor for risk-factor management. These change-management analysis becomes virtual events of the future, as they are not assessed based on future data collection, but based on past data collection of similar scenarios.

A selective picture of a risk assessment leaves the rest of the story up for assumptions. 
When operational changes or new processes are introduces without a change-management system in n place the testing of SMS is not fully completed. Operational changes involves human factors which are not regular variables, but special, and often unpredictable variations. These human factors cannot be applied to react in the same manner to changes as mechanical factors do. 

Eliminating human factors from the equation when testing SMS, skews a risk assessment in favor of assumptions.