The Goal by Eliyahu Goldratt

SP JAIN SCHOOL OF GLOBAL MANAGEMENT (GROUP 2 | CASE ANALYSIS ) |

OPERATIONS EXCELLENCE IN SERVICES AND MANUFACTURING

TEAM MEMBERS : ( In Alphabetical order ) Hardik Pandya, Manjari Gupta , Reena Dasan Sebastian Jose David.

Each group will prepare and submit a well-structured note that covers the following:

1.Key lessons learned during the hike that relate to managing a firm’s operations.

Mr Alex Rogo’s thoughts takes him back to his manufacturing plant in UniCo while leading his all-boys troops on a hiking expedition to the "Devil's Gulch”. His purpose is to lead a group of children on a trip through the woods as quickly as possible and the mission is accomplished when all of the children reach the finish line.

The author compares a production line to children marching in a line. Each child represents a machine, and "walking" represents the task that must be completed on each machine.

The trek, like a manufacturing system, is a series of interconnected events with statistical irregularities. For example, each child in the line may vary in speed, going quicker or slower. However, the ability to travel quicker than the average is limited. On the other hand, the kids' potential to slow down is limitless. The ability to walk is proportional to the number of children ahead of the preceding ones in line. As a result, the final child's pace is a dependent event that is closely related to all of the other kids walking.

During the hike, the result dependent events and statistical functions produce large gaps between faster and slower children. In a factory, the distance between two children is a "work-in-process inventory." It is not a productive setting if the last child arrives two hours after the first child. In this case, the first child will have to wait two hours to complete the task.

To overcome the gap challenge, Alex requested that the slowest child lead the hike. He also carries the kid's bag, which allows him to walk more quickly. All of the students behind the first one could walk faster than the leader, so everyone kept the same pace. A "bottleneck" is the "slowest youngster."

Faster machines (or faster children) will not enhance productivity on their own. The hike will be at the same pace as the slowest child's (machine) rate. This is known as the "Theory of Constraints." Because bottlenecks are constraints, you must remove them in order to advance your hike faster.

Alex and his scouts replicate the influence of statistical irregularities on a production line using a dye, bowls, and matchsticks. The experiment demonstrates that when a balanced plant relies on dependent events and is prone to statistical variations, it will have throughput deficits and growing inventory levels.

The bowl and stick game taught us that dependability and unpredictability interact to decrease overall plant performance. Several balanced plant models have been presented to assess the concept that growing (decreasing) levels of dependability and variability degrade (increase) plant performance.

Every workstation in a balanced facility must have the same capacity. Every workstation in the game will have an average capacity of 3. 5 units of matchsticks.

The essential learning after comprehending the fundamental dice game setup is that in the long term, the average number of units of output a plant should be able to produce in every cycle is the mean of the range of outputs that each station may create, which in the game is 3. 5 units.

However, the plant may not achieve the theoretically predicted outcomes due to differences in the output of each workstation, which may disrupt the plant's balance.

When Alex is back at Unico he discusses his learnings from the experiment with the boys on the Hiking trip. His team agrees with him that Automation / Robots bring digitisation and consistency into the manufacturing process, however in order to achieve the ultimate Business objective of making Profit they need to make the whole manufacturing system productive. At this juncture they are faced with a? crisis of completing an emergency job order where the subassemblies have to go through fabrication and welding departments before completion .They have to deliver the consignment to Smyth’s plant ?and the last truck that will carry the finished goods leaves at 5 pm . The next truck is the following day in the afternoon. They have already decided to set up the Robot to do the welding which means that there will be no inconsistencies in output. Alex’s Team has also decided that twenty-five units will get fabricated every hour and Fred will arrange for a materials handler to pick up the fabricated parts and hand it over to the Robots every hour.

Pete’s department can start fabricating only at noon? and his staff will be working till only 4 pm as per rules already set before. Output has to be 100 pieces by 5 pm.

Scheduling for Fabricating and Welding Teams and Total output grid in excel is not being accepted here . ( Hence it has been deleted )

If one of us were Alex Rogo we would check if inventory to service Smyth’s requirement was already present in current stock to service this client because the case clearly states that Alex Rogo had excess inventory and should not manufacture more

Also worth pondering – Alex was not allowed to fire any staff from the manufacturing site , so there must be welders who did not lose their jobs as a result of Automation , they surely could have helped out to complete the? welding of the subassemblies of 10 units which would not take more than 30 minutes (3pm- 3.30 ). At 3 pm 10 fabricated units were not welded by the Robots and this led to shortage of 10 units which did not complete the order of 100 units required. Clearly, there was no one to supervise the ?welded output generated by the Robots like Fred had arranged for movement of subassembly parts from Pete’s Fabricating department to the Robots for welding every hour from 1pm onwards.

Alex and his team miss transporting the finished goods by 10 units . Yet Pete and his team are feeling very proud that they have been able to fabricate 100 units .

But Alex was able to drive home the principle that ‘’The maximum deviation of a preceding operation will become the starting point of the next/subsequent operation. ‘’

2. How the lessons learned during the hike relate to the key dashboard metrics for any

Operations Manager [T, I, OE, OTIF].

Through interpretation in his book The Goal, Goldratt was able for his character Alex Rogo, project the manufacturing process through the hike experience with his son, Dave, and the other scouts. ?Every manufacturing organisation has standardised processes in their factories

the Hike too had a certain amount of standardization in terms of specifications in the form of a blazed trail for the troop of children to follow to reach their destination.

The ideal average time that Alex estimated before the start of the hike was to cover the distance at an average speed of 2miles per hour which means that they would cover the entire hike which is a total of 10 miles in just five hours, however, as they started Alex realized they were nowhere close to the ideal average time of 2miles per hour due to the dependable events which is the speed at which the second boy in the troop can move depends on the speed and miles covered by the first boy.

Throughput is considered as one of the most basic operations Key Performance Indicator (KPI) in the manufacturing industry dashboard. It basically measures the rate of production of a machine, line / plant over a period of time.? In the case of “The Goal” of ?albeit simplified,? throughput was a measurement of production / manufacturing wherein it the whole process until products are sold. In the case of the hike Throughput was represented as the amount / distance covered by the last person in the hiking group. As the main goal was for the whole troop to reach the campsite. ?It wasn’t going to be counted as a finished work process / hike if only the pacer and the first few hikers in the whole troop reached campsite, but rather a completed process is only reached when the whole group is able to reach the campsite, be it the sweeper or the very last hiker reaches the campsite 2 hours after the first one. For manufacturing, throughput comes in as a measurement for an operations manager to determine their ability to meet production deadlines. The measurement does not kick in whilst one part is still in a dependent process throughout one production line but rather as a finished product for a whole that is ready to be used for an independent work process that comes after or shipped off to be sold. Also, throughput cannot keep decreasing and Inventory cannot go on mounting leading to rising inventory holding costs directly proportional to an increase in operational costs of the manufacturing site under consideration. If Production capacity of each resource is balanced proportionately with market demand , then operations in the plant would be balanced out

In a manufacturing process where dependent events is / are present, this only means that latter stages of manufacturing can and will be dependent on requisite stages to be finished or met first. Contrary to the belief however that statistical fluctuations will average out in a series of dependent events, there is in fact an accumulation of fluctuations for stages of work that fall later in the manufacturing process because the dependency limits the opportunities for higher fluctuations.

For workstations located at the latter stages of manufacturing, their capacity and speed to complete work processes are not the only limitations that cap their production, but also, they are dependent on the capacity of the speed of the work processes before them. Explained during our discussions in class, how some modern manufacturing firms addressed these issues, is by increasing the inventory on work in process so as to maximize all production stages. However, by increasing inventory, manufacturing firms and plants also increase the holding cost for each work in process thereby in effect increasing operational expenses (OE). Any increase in inventory and operational expenses is a minus in production efficiency and thereby also a decrease in our throughput. The energy spent by each and every troop member to cover the distance or increase speed in case of any deviation from the standard speed is OE. Inventory was the length or the distance between each troop member which was either expanding or shrinking at certain places during the Hike.

Identifying bottlenecks and distributing load throughout the system helps to ensure a more efficient use of resources and higher / faster throughput. Coupled with the points raised above, we have to understand, that it is the speed and capacity of bottlenecks regardless of where they are in a manufacturing process that dictate the overall capacity and speed of a work process. . This realization of the speed and capacity of bottlenecks that determine the throughput is a good segue to our final metric of On Time in Full (OTIF) delivery.? It is best to ensure that an effective and not only an efficient use of the capacity of bottlenecks that need to be addressed in ensuring a smooth flow for the system. In the case of the Hike, the average 2miles per hour target could have been achieved when all the troop members right up from the first boy leading the troop to the last member which ,completed that distance within the average speed and time. This concept is referred to as On-time in Full which is widely used in manufacturing plants for determining how many final products sold to the customers were in full and on time as per the contract agreed between them.

?Similarly in that regard, the distribution of work can be done to optimize work in bottle necks, questions arise whether bottlenecks would be better placed early in the process or latter in the process, but rather, questions about efficiency and effective use of the bottlenecks are to be entertained .

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