“If you don’t know where you’re
going, any [set of Best Practices] will get you there”
“Best Practices don’t always
yield Best Results”
Simulation began back in the early 1970’s in
industry, where today it is used by nearly all of the
Fortune 500 manufacturers to enable productivity and
performance improvement gains. Today, advances in the
technology and computer programming have made even the
most complex and chaotic environments suitable for simulation.
The key
attributes that have always made process simulation
an accurate, reliable tool for “predictive analysis”
include its ability to account for:
• Variability
in and between processes
• Interdependencies
of, and between, processes and resources
• Change in systems
over time (dynamism)
• Random events and stochastic environments
• Constraints, bottlenecks, and “pinch-points”
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In doing so, simulation
enables users to accurately replicate
complex working systems in a risk-free, computer
environment. Based on this accurate replication,
reliable and predictive “what if”
scenarios can then be run to see the impacts
of various and multiple changes to the system, and
ascertain the best combinations of options for optimization.
Through the effective use of simulation, users can
understand the future state and make sound, rational
decisions with great accuracy and confidence.
This removes issues on both sides of an implementation
argument, since it…
•
Reduces skepticism about
the expected performance, since the results are
realistic and fully explainable
•
Develops realistic expectations for
ALL participants in the process
•
Helps develop a “road map”
to change, with performance expectations for each
step along the way
•
Helps management understand the true
limits of current performance (given current constraints),
and when to begin to change tactics
