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?
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.
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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