Capacity Planning Requires Tradeoffs

Capacity planners would like for resources to be utilized 100% of the time and for customers to never experience a wait.  These goals, however, naturally contend with each another. 

In a process with variability in processing times, small increases in the pace of demand (and, consequently, utilization) can create disproportionately large increases in customer wait times.  It is for this reason that many capacity planners will work to match capacity (throughput) to a demand level (arrival rate) that will result in approximately 80% utilization, rather than 100%.  This unused utilization serves as a buffer to minimize the impact of variability.

The decision to increase capacity or throughput to reduce utilization can require tradeoffs.  While it is true that increases in capacity will reduce utilization; assuming the pace of demand is relatively constant, this reduction in utilization may not yield a large enough reduction in customer wait times to justify the investment required to increase capacity.

Arriving at an appropriate balance between capacity/throughput and the pace of anticipated demand is a balancing act and the ideal plan selected is often a subjective one.  Process models can provide a mechanism to understand the performance under varied conditions and make data-driven decisions about these tradeoffs.  Scenario-based modeling allows evaluation of the tradeoffs under varied levels of anticipated demand and planned throughput values.  ProcessView, Bluespring’s add-in to Microsoft Visio for process modeling and analysis, is one such solution.

To see how ProcessView can help you improve your capacity planning, contact us for a demonstration.  To obtain a ProcessView trial, go to

About Bluespring

Bluespring is a software development arm of Ascendum Solutions with a singular focus on helping organizations make work flow in Microsoft SharePoint.  We provide software and services that boost an organizations use of SharePoint to get critical information to the right people at the right time ... Read More

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