The
concept of full
capacity is a tool to estimate revenue for budgeting and a gauge
for sales planning. Using sampling, full capacity projects output
based on maximum use of existing resources with optimal availability
of materials and logistical elements. Think of it as the optimistic
average of what existed in the near past projected for the entire
forecast period. Assumes optimal output with no disruptions or
changes.
A
simple illustration: sampling of production volume is 10 widgets per
hour; the organization runs two shifts weekdays; 20 workdays per
month – full capacity per month is 3,200 widgets (10 units x 16
daily hours x 20 workdays). If actual output is 2,500 widgets, they
are at 78% of full capacity and up to 700 more widgets could be made
and sold - theoretically. This can be a handy tool when viewed as
'here's what we can do in addition' –
it is not so handy if viewed ' we cannot do more than
this'.
Business
has changed and continues to evolve (government is making similar
inroads) – automation eliminates roles needing a live person,
flexible staffing reduces fixed overhead, products and services are
made new & improved by removing features and chopping the price.
The
point is that the past is becoming less and less relevant as a tool
for the future, but we hold on to several myths when looking forward.
Myth:
presupposing
full capacity is the maximum output of the
organization.
An
organization can adjust to meet higher production volume, when needed
– add a 3rd shift, for example.
Myth:
sampling throughput gives a good estimate for projections of
capacity.
Assuming
each person works at their best pace for all hours on the job is
unachievable in practice. Parkinson
noted that work expands to the time available – and even NASCAR
racers have pit stops.
Myth:
all resources are being used fully throughout the organization.
It
is unusual for all teams to be fully engaged at the same time.
Starting up and winding down require different intensity and pace,
than does the core activities of a project. Some functional roles are
active at different time – like sales before the project and
shipping at the end of it.
Myth:
productivity is constant.
Experience
boosts productivity – first time a person creates a website there's
a learning curve to master; the second time it takes only about 60%
of the original time.
Myth:
history describes the future with gradual changes.
We
are in a time of discontinuous
growth – the era of 30-years and a gold watch is gone...now
it's start-up + 4-years and sell. The New
Normal is driven by agility, collaboration, and continual
skill/knowledge development.
Sitting
in the Big Chair, I can bring in collaborators to do what the staff
can't because of lack of time or experience, when needed, or match up
experienced with inexperienced Doers
to develop future capacity.
In
an environment where customers are reluctant to buy, or projects are
awarded but not funded, full capacity is not as important as
sufficient capacity and extensive external resources.
Business
as usual is now unusual, and there's a premium on flexibility,
innovation, and applying new equipment and devices to enhance the
technology (how work gets done) within the organization.
The
choice is stuck on full capacity, or adapt to the evolutionary
changes afoot. How would you like to proceed?
2 comments:
In Sid Mukherjee's biography of Cancer, he relates how surgeons, chemotherapists, politicians, and advertisers use different accounting methods to bring full capacity to their benefit. There's a quote that statistics tend to favor the statistician.
Dick:
Thanks for your comment. Even in medical research, there is a similar measure to 'full capacity' used to assist in planning.
Highlights the importance of knowing what is included/excluded in the statistics. Like with the unemployment statistics - 8.1% cited, but employed is 63.3%...
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