How does capacity planning differ in service
Some examples are; cloud computing services, airline seat capacity and fast-food restaurants. Human capacity includes those organizations which sell specific skills of their team members.
This can include project management, technical service technicians and data centres. Many organizations that use human capacity include financial auditing companies, legal firms and engineering project companies. Most manufacturers go through five common capacity planning challenges, irrespective of the operational strategy used. These challenges could impact the production flow no matter the level or scale or the complexity of the organization.
Traditional manufacturing processes have mostly relied on siloed data to plan the production capacity. Disparate, unconnected systems imply manual reconciliation of data before consumption. This results in higher time consumption and data could get outdated even before it can be applied and used. Since most capacity planning tools rely on inputs from demand forecasts, supply chain, warehouse management etc, a disconnected system can be risky as it increases reliance on manual reports and human capability to identify and manage trends.
Very often, manufacturing operations involve capacity data arising in the form of records and reports which then must be manually aggregated before the final information can be consumed. After this is done, planners add in the much needed supply and demand data and develop a formula to arrive at the available capacity. During this process, if at any step, these multiple data inputs are inaccurate or outdated or if they exist in multiple formats, this again needs to be formatted and standardized before they can be utilized for planning purposes.
And since most of these data points are not connected, any new iterations must go through the same process all over again. Planners use many complex formulae and calculations to arrive at the final capacity plan. This can include several aspects like the material availability, load by work center, alternate sourcing, attribute-based planning rules and more. While doing this, if the data entry errors or bad data are present, the entire capacity plan could be wrong. In addition to this, a lag based on the time needed to assemble the data, new information and changes must be input into several sources, again lengthening the time to produce a plan and creating the risk of errors.
In most manufacturing environments, capacity planning is often done at different levels. A rough cut planning is usually done at the master schedule level and this is used for short-term planning may be for a week to two months.
Medium or aggregate planning uses a month planning window to provide a longer view that allows the organization to ensure that demand can be met long-term.
It also helps smoothen supply chain challenges to look at production cost reductions. Each of these levels need larger data sets and longer time periods as they are used for multiple decision-making tasks. Due to this, the challenges of data collection, data quality and formulae and calculations are multiplied in complexity, creating possibilities of errors with those issues. As the capacity planning process involves so many dynamic and moving parts, and since very few of them interconnected, there is a chance of a possible breakdown or gap in communication which can be risky to the integrity of the capacity plan.
Planning ensures that operating cost are maintained at a minimum possible level without affecting the quality. It ensures the organization remain competitive and can achieve the long-term growth plan. Capacity planning based on the timeline is classified into three main categories long range, medium range and short range.
Long Term Capacity: Long range capacity of an organization is dependent on various other capacities like design capacity, production capacity, sustainable capacity and effective capacity. Design capacity is the maximum output possible as indicated by equipment manufacturer under ideal working condition. Production capacity is the maximum output possible from equipment under normal working condition or day.
Sustainable capacity is the maximum production level achievable in realistic work condition and considering normal machine breakdown, maintenance, etc. Effective capacity is the optimum production level under pre-defined job and work-schedules, normal machine breakdown, maintenance, etc. What is Human Resource Planning? What is resource leveling on a project?
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Capacity planning is more high level and helps you determine what and how many resources you need to meet demand. Resource planning is more about analyzing resource utilization: you use it to takes the number of resources available as determined by your capacity planning and allocate them to individual projects. You would use capacity planning to determine if you need to hire more employees, bring on seasonal workers, or increase your stock of flowers before February So, if most of your demand is for vases of red and pink posies, you could allocate the largest portion of your resources to creating those floral arrangements.
There are three methodologies behind capacity planning. Lag strategy is planning to have enough resources to meet true demand not projected. Lag strategy is a conservative method of capacity planning that ensures your costs are as low as possible.
The potential downside to this strategy is that it can create a lag in the delivery of products or services to customers, which is where the name comes from. If you get a sudden surge in orders or land a large new client who wants fast turnaround times, lag strategy may prevent you from meeting due dates. Lead strategy is planning to have enough resources to meet your demand forecasts.
Lead strategy assumes more risk than lag strategy. The major benefit of this strategy is that if you do have a sudden uptick in orders, you will most likely be able to keep all of your customers happy and meet due dates. Match strategy is the middle ground between lag and lead strategy. Using match strategy, you do strategic capacity planning more frequently. Based on this information, you adjust your capacity management to meet demand in increments.
This strategy offers the most flexibility with less risk than lead strategy, but it has more ability to scale than lag strategy. The goal of capacity planning is to ensure that your supply chain is always ready and able to meet demand.
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