In our last blog, we understood the 3 main strategies of Capacity Planning. Hence it is important to get into the KPIs and derivatives to measure an enterprises’ Capacity performance.
Objectives & Measures of Capacity Planning
Having a fair idea about strategic part, its time to look at some of the key derivatives used for measuring outputs and performance under Capacity Planning.
We all know this phrase ‘Numbers speak louder than words’ and similarly, it becomes very crucial for an enterprise to measure its operation capacities. There is a systematic approach using some mathematics to measure and derive the performance indicators.
In the context of capacity planning, ‘Design Capacity’ is the highest output that an enterprise is capable of completing in a given period. Whereas, ‘Effective capacity’ is the maximum output that an enterprise is capable of completing in a given period after considering the constraints arising out of Machine Maintenance, Material shortages or scraps, Man hours availability, etc. Finally, we have Actual Output which is the output actually achieved (goods actually produced). Actual Output, cannot exceed Effective Capacity. At its best, it can be equal to Effective Capacity. The reason for Actual Output lower than Effective Capacity could be quality defects in output, unexpected plant shutdown, machine breakdown, higher shortage of material, defective raw materials received from vendor, etc.
Every enterprise must know its Design Capacity, Effective Capacity & Actual Output to understand the key measures which are ‘Efficiency’ & ‘Utilization’. These measures are expressed in percentages and they are calculated as follows :
EFFICIENCY = (ACUTAL OUTPUT ÷ EFFECTIVECAPACITY) x 100
UTILIZATION = (ACUTAL OUTPUT ÷ DESIGN CAPACITY) x 100
Let us understand this with an example. A company has 4 machines namely M1, M2, M3 & M4. Every machine is used for producing different sizes of Jute Bags. Their monthly capacities & final output are as follows:
To calculate Efficiency and Utilization, we must follow the said formula and derive the values which is given below in the table:
Though it is important to know Efficiency % to derive the performance, an enterprise, on a long-term perspective, tries to improve its Utilization %. In view of this, an enterprise relies on Capacity Planning to take some key decisions which are as follows:
- Capacity required to meet the demand
- When to adjust Capacity?
- Balancing Supply with Demand
- Process / Facility flexibility
ValQ on Power BI exactly happens to support such key decisions with its ‘on-the-fly’ simulation capabilities. A tool like ValQ empowers the user to change the capacity fills and requirement which eventually leads to scenario creation that can be compared easily. To know how this is possible instantly using ValQ on Power BI, stay connected and keep watching this space for more.