Section 47. TimeIndividual Step Cycle Time

47. TimeIndividual Step Cycle Time

Overview

Simply put, the Individual Step Cycle Time is the time required, on an ongoing basis, by an individual step to process an entity. If the process step has a five-minute Cycle Time (if there is an entity ready and waiting to be processed in front of the process step and there is the appropriate resource to start processing the entity), then it takes five minutes for the resource to process the entity through this step.

The assumptions in parentheses here are keyIndividual Step Cycle Time takes no account of lack of an entity to work on, it is measured from the time an entity begins this step to the time that the step ends after processing. Neither does it take into account the availability of resources to commence the step, because it is measured from when the step starts. It does, however, take into account availability of resources during the processing of the entity (i.e., if resources become unavailable during processing (after start), then the Cycle Time is increased.

If the assumptions are met, then by standing at the end of the process step it should be possible to see an entity exiting the process step every Cycle Time interval as per Figure 7.46.1.

Figure 7.46.1. Graphical representation of Global Process Cycle Time.

Logistics

Calculating an Individual Step Cycle Time can be done in a relatively short period of time, because Cycle Time at this level tends to be a lot more consistent than across a process as a whole.

To capture average Cycle Time, data can usually be captured over a period of a day or so, with a week being more than sufficient. To calculate variation in the Cycle Time, a longer study is needed to allow normal variation to appear in the process; for example, if there is weekly variability, then data has to be captured over a few weeks to be able to see it.

While the data is collected, the step must never be starved of something to work on, so it is important to only time the step when an input entity is available.

Recording data across multiple steps in the process in the same study is known as a Multi-Cycle Analysis.

It takes approximately one hour of a preparatory meeting to identify exact timing points for the step, preferably using an already constructed Value Stream Map, and then structure a data capture method. It is always useful to do a dry run data capture, to ensure the correct data is being captured and no biases are creeping in, but inevitably some Hawthorne Effect occurs. For more detail regarding the data capture, see "KPOVs and Data" in this chapter.

Individual Step Cycle Time often varies by entity type. It is useful, therefore, to capture either data for just one entity type or preferably data for all (or multiple) entity types and then stratifying the Time by type during the data analysis.

Roadmap

Due to the relative consistency in times, it is possible to calculate Individual Step Cycle Time from as few as 710 data points. By taking the truncated mean (discarding the highest and lowest points and averaging the rest) a good approximation can be made. If understanding the variation in the Cycle Time is required, then 2530 data points are required as a minimum.

If multiple entity types are examined, seven data points per type allows calculation of an average for each type as well as the whole. If an understanding of variation is required by type then 2530 data points per type is required.

Step 1.	Determine the scope of the Process Step Time, by identifying the beginning point for the entity (when the clock starts) and the beginning point of the next entity (when the clock stops). The step Cycle Time must include all the work done to process an entity, including the setup, and so on; so measuring from beginning to beginning (or end to end) captures a full Cycle Time.
Step 2.	If the Cycle Time is less than one minute, then it is probably best to use a stopwatch, starting it when the step begins, processing the first entity, and stopping it when the step begins processing the subsequent entity. If the step takes significantly longer than a minute, then it probably is best to write down the start time and the end time and then calculate the step Cycle Time later. Record the times and also the entity type being processed to allow stratification by type later during the data analysis. It is sometimes useful, if the step time is short, to time three or more consecutive entities passing through the step (making sure there is always entity inventory available), to get a better reading on the average time.
Step 3.	From the captured data, calculate the Individual Step Cycle Times by subtracting the start time from the stop time for each cycle. Then calculate the mean and variation (standard deviation) in Individual Step Cycle Times. If data for multiple entity types was captured, analyze the data as a whole and then conduct separate analyses stratifying by entity type.

Interpreting the Output

Interpreting the Individual Step Cycle Times should not be done in isolation from other elements. The trick is to understand the relationship between the internal times relating to our process:

• Process Lead TimeTotal time for an entity to progress through the process

• Replenishment Time to CustomerTime to fill the Customer's "in-box" when they request it be refilled

• Global Process Cycle TimeRate (expressed in time) at which the process can generate entities

And to understand the relationship with the external Customer or Market related times:

• Requested Delivery TimeHow quickly the Customer needs delivery of an entity when they request it

• Takt TimeThe pace of usage of entities by the Customer, expressed in time

By looking at the Individual Step Cycle Times versus the Takt Time, it is possible to ascertain whether the steps in the process will be able to keep up with the pace of Customer demand and also which step, if any, is the bottleneck.

See "Load Chart" in this chapter.