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Tuesday, June 18, 2013

27 B The Productivity Experiment

There is another experiment that I developed that helps managers in charge of processes for which a high throughput is important to the effectiveness of the organization.  This experiment is a game that teaches the impacts of variation and work in process on effectiveness and profitability.
The game is for two teams each with an equal number of players and a team leader. It is adaptable to two to about 20 trainees, it can be generic or specific to a process and there can be multiple levels of sophistication, although only one level is described here. This level treats variation and work in process inventory but ignores inventories of raw materials and finished goods and ignores the effects of lot size. Students can modify the game to include these effects if the effects are important to training in their organization. This description assumes ten or fewer trainees with two as team leaders and the others as workers. Workers role dice and move items representing work from process to process. Leaders verify workers results, record data, calculate throughput and work in process inventory. If there are more than ten trainees they are given assignments as production control, inspectors, supervisors or finance workers and take over the leader’s roles in the game appropriate to these titles.
 One leader gets to choose between two processes with the same average throughput. One process has high capacity, but relatively high variation, and the other process has lower capacity but also lower variation. The other gets the left over process. The game is played by rolling dice that determine the throughput of each step in a process that has a step for each worker on a team. The game is played in cycles with a cycle being one turn at rolling the die for each worker on the team. Three cycles are usually sufficient to demonstrate the principles.
The high capacity team gets a die with numbers 1 to 6 so that its average throughput is 3.5 but the variation can be from 1 to 6. If the game is played for three cycles this team’s overall process has a capacity equal to the number of cycles times the largest die number, or 18. Capacity is defined as the maximum possible through put if each worker rolls the largest number on each turn.
The low capacity team gets a die with only the numbers 3 and 4 so that its average through put is also 3.5 but the variation is only from 3 to 4. (Equivalently, use a regular die but rolling 1, 2, or 3 is counted as a 3 and rolling a 4, 5, or 6 is counted as a 4.) The capacity of this team’s overall process for three cycles is 12 compared to 18 for the high capacity team’s overall process. Each team starts with a pile of chips that represent items of work. The objective is to move as many items from the first step through the entire process for delivery at the end and to have as few chips as possible left stranded as work in process (WIP) inventory.
Each team gets the same amount of input items for its process and gets “paid” according to its total production, i.e. sum over the number of cycles of the number of output items at the end of each cycle. However, each team is charged with the cost of WIP inventory, i.e. the sum over the cycles of the number of items that are still in the intermediate steps of its process when each cycle is over.
When a player rolls a die a number of items equal to the die result are moved through that player’s step in the process. E.g. if the first player rolls a three then three items are moved through the first step to the second step. If the second player rolls a two then two items are moved to the third step but if the second player rolls a four only three items are available to be moved. After each team has completed the same number of cycles the game is stopped and the financial results are calculated.
I have found that the typical manager that is oriented toward high productivity chooses the high capacity process in spite of its higher variation and is then amazed when his team gets soundly beaten because of both low production and all the work in process the high variation produces. It is easy to see how this happens. The production is equal to the number of cycles times the throughput of the last worker in the process. The low capacity team has a throughput of at least three per cycle whereas the high capacity can easily be limited to a throughput of only one or two if any of the workers rolls a one or two during a cycle. Thus the lower variation of the lower capacity team overcomes the lower capacity and usually results in higher total production. The lower capacity team’s lower variation results in WIP for each cycle being one, if the first worker rolls a four or zero if the first worker rolls a three. The higher capacity team can have WIP for each cycle of as much as five if the first worker rolls a six and any subsequent player rolls a one.
This game is a good introduction to teaching process improvement, just in time inventory and theory of constraints to managers responsible for processes in which throughput is important. Although the game was designed for a manufacturing process it doesn’t matter whether the items moving from step to step are manufactured items or paper products in a service organization. In both organizations processes with high variation result in both reduced throughput (efficiency) and excess work in progress. Therefore reducing variation has a high payoff even without changing the mean throughput capability of any step in the process, including the constraining step. This is not obvious to many workers or managers until they experience the results of the game described above.
Exercise 3
Try the productivity experiment yourself. You can play the roles of each of the workers on each of the teams. For example use a spreadsheet with a column for each worker plus a column for throughput per cycle and a column for WIP inventory per cycle. Each cycle is assigned three rows, one for the result of rolling the die, one for the throughput and one for the WIP inventory. Try four workers per team and carryout three cycles as described. You will find that the process with a capacity of 12 and variation of 3 or 4 typically achieves production of 9 and WIP of 3 or less for three cycles. The process with capacity of 18 and variation of 1 to 6 typically achieves production of less than 9 and WIP of 6 to 8 for three cycles.

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