Harvard Business Case - Bayonne Packaging

1. Amsterdam MBA
Operations & Supply Chain Management
Bayonne Packaging, Inc.
HBS brief case 4420
March 5, 2013
Gulcin Askin
Michelle Donovan
Kivanc Ozuolmez
Peter Tempelman
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2. The answers in this report relate to the questions given in the document ‘Case 1: Bayonne Packaging,
Inc.’
Question 1: Operations Performance of Bayonne Packaging
1A. How would you define the Operations Strategy of Bayonne Packaging?
The operations strategy of a company is the prioritization of the five key performance measures:
cost, quality, speed, dependability and flexibility.
The president of Bayonne Packaging, Inc. indicates that the problems of the company are: they have
incurred their first losses since 2001, there are complaints about quality and they are delivering late
more often. The other department managers, except for the absent Finishing department manager,
also indicate to the new vice president of operations that they have problems in their departments
that relate to the performance measures dependability, quality and speed.
Based on the priorities given by the key personnel of Bayonne Packaging we have determined the
operations strategy of Bayonne Packaging to be as follows (key performance measures in descending
order of importance:
1. Dependability
2. Quality
3. Speed
4. Costs
5. Flexibility
1B. How can Bayonne Packaging, Inc.’s Operations & Supply Chain performance be quantified?
Per Key Performance Measure we have determined the following ways to quantify the performance.
Dependability
• Percentage of full (i.e. not partial) deliveries that is on time per time period
• Average delay time of an order for the customer per time period
• Down time per machine as a result of poor maintenance per time period
Quality
• The percentage of goods rejected by Quality Control per time period
• The percentage of goods rejected by the customer per time period.
• The percentage of goods with missing glue lines or excess glue
Speed
• The number of days between the signing of a proof by the customer and the delivery date
• The amount of time spent on set up times per order / per period
• The number of materials flowing through operations per period
• The average critical ratio (should be as close to target ratio as possible)
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3. Costs
• The cumulative volumes in US dollars / The cumulative numbers of shipped orders
• The COGS per month as a percentage of net sales
• The profit before tax
Flexibility
• The number of different orders that can be expedited
• Number of different packages Bayonne Packaging can print
• The number of different industries and their industry specific requirements that Bayonne
Packaging can produce for
1C. How is Bayonne Packaging doing on these performance measures?
To determine the performance of Bayonne Packaging on the performance measures listed is to
determine Bayonne Packaging, Inc.’s position on the line of operational excellence. It is safe to say
that Bayonne Packaging, Inc. is not operating on the curves of operational excellence that currently
seem to trouble the company, that is the lines that depict the trade-offs between dependability and
speed, quality and speed, and dependability and quality.
We rate the performance of Bayonne Packaging as follows.
Dependability
Bayonne Packaging is not doing well. In October 2011, 20% of the orders are late, where two years
ago 5% was considered a bad result (p.3). Customers are aware of this and consequently want to
‘move up’ their order (p.3).
Quality
Bayonne Packaging, Inc. has problems with its gluing operation. In October 2011 Quality Assurance
has found 6% of the products to be defective. Worse yet, customer rejected 1% of the goods due to
glue problems (p.2). Furthermore, some packages with additional parts were shipped incomplete
(p.3)
Speed
Bayonne Packaging, Inc. is not doing well on speed. It is running its operations to full capacity (see
question 2A – Heidelberg press is the bottleneck – exhibit 2). Small changes in the variability of
customer orders can therefore result in increasing queues. This in turn causes the Sales department
to expedite some orders at the expense of others’ orders (p.7). Expediting orders also causes
breaking up production runs into two parts, which causes extra set up time of the machines.
The combination of running at full capacity, variability of customer orders, expediting orders and
partialing orders causes a lower overall speed of delivery to customers.
Cost
According to exhibit 1 Bayonne Packaging, Inc. has incurred a Net Profit Before Tax of -7.2% (i.e. it
incurred a loss) in October 2011.
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4. Its total COGS significantly went up from 83.2% in September 2011 to 90.7% in October 2011. (Yearly
averages 2010: 74.4%, 2009: 72.1%)
For these reasons, Bayonne Packaging, Incl. is not performing well on the cost performance measure.
Flexibility
Bayonne Packaging, Inc. is doing well on flexibility. It is ‘grabbing into new markets’ (p.4) such as
packaging for candies, corporate gift sets and packages meeting FDA requirements. Flexibility defined
as being able to serve different markets is a performance measure Bayonne Packaging, Inc. is doing
well at.
1D. What are the main problems in fulfilling the Operations Strategy?
The main problems in fulfilling the Operations Strategy are:
• A process that is running at full capacity and has no buffer to cope with variability in
customer orders.
• A lack of understanding how the processes actually function due to the lack of a consistent
ERP system, resulting in departments that are forced to operate independently from each
other and do not consider themselves as one unit.
• The company does not have a method of determining the priority of orders
• Information systems that are used are based on incorrect assumptions
Question 2: Analysis of the operations system of Bayonne Packaging, Inc.
2A. What is the current utilization in the work centers (excluding Finishing)?
Number of working hours in October 347
The machines ran in total
Machine Total Hours Number of Combined Theoretical Capacity
per machines running times running times Utilization per
machine work center
Composition 255 1 255 347 73.49%
Jagenburg 279 1 279 347 80.40%
Heidelberg press 348 2 696 694 100.29%
Bobst die-cut 272 2 544 694 78.39%
Int. Royal - Queen 156 3 468 1041 44.96%
Int. Staude 179 4 716 1388 51.59%
Int. 3A 145 2 290 694 41.79%
The Heidelberg press machine is the slowest, and the bottleneck in the process. Therefore, the
process capacity utilization is as much as the bottleneck, hence 100.29%
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5. Quote To Order
Customer Size?
Capacity Utilization
Capacity Utilization 51.59%
Composition Royal/Queen Staudes
73.49%
Department
Capacity Utilization
44.96%
Design
3A?
OK?
Capacity Utilization Sheet Capacity Utilization
3A
80.40% Department 41.79%
Capacity Utilization Print Finish
100.29% Department Department
Capacity Utilization Die Cut
78.39% Department
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6. 2B. Capacity in pieces of the Die-cut center in three cases
For the Gantt chart of this question see appendix 1.
Order size (pieces) 30,000
Time per sheet 0.0075
Time per piece (1 sheet = 3 piece) 0.0025
Time to process order (30000 piece * Time per piece) 75 minutes
Case (i)
Set up time 2,5 hrs 150 minutes
Total minutes per order 225 minutes
15 hours per day is 900 minutes
Total capacity of Die-cut center 4 orders
Total capacity of Die-cut center in pieces 120,000 pieces
Order size (pieces) 30,000
Time per sheet 0.0075
Time per piece (1 sheet = 3 pieces) 0.0025
gang 2 orders in a batch, number of pieces in batch 60,000
Time to process order (60000 piece * Time per piece) 150 minutes
Case (ii)
Set up time 2,5 hrs 150 minutes
Total minutes per batch 300 minutes
15 hours per day is 900 minutes
Total capacity of Die-cut center 3 batches
Total capacity of Die-cut center in orders 6 orders
Total capacity of Die-cut center in pieces 180,000 pieces
All orders are ganged
Time per sheet 0.0075
Time per piece (1 sheet = 3 piece) 0.0025
total minutes per day 900 minutes
Case (iii)
minutes required for one required set up 150 minutes
Remaining available minutes for running orders 750 minutes
Number of pieces possible per day 300,000 pieces
Number of orders possible per day 10 orders
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7. 2C. Orders in the Royal / Queens work center
Assume that the question asks for actual performance
Assumptions and
implicit findings
Number or partialed orders Royal Queen 40 orders
Number of orders on Royal Queen total 77 orders
Total set up time Royal Queen in October 231 hours
Setup time per order 3 hours
40 orders require 40 set ups (no partials)
Total number of set ups 40 + 37 77 setups
Time per set up 3 hours
Case (i)
Total set up time 231 hours
Total number of working hours for three machines (347 * 3) 1,041 hours
Time left for folding and gluing (1041 - 231) 810 hours
Time required for F&G of one piece 0.0023 minutes
Number of pieces to be folded and glued 21,130,435 pieces
40 orders require 80 set ups ( 40 orders are partial)
Total number of set ups 80 + 37 117 setups
Time per set up 3 hours
Case (ii)
Total set up time 351 hours
Total number of working hours for three machines (347 * 3) 1041 hours
Time left for folding and gluing (1041 - 351) 690 hours
Time required for F&G of one piece 0.0023 minutes
Number of pieces to be folded and glued 18,000,000 pieces
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8. 2D. Order size to the Royal / Queen and Staude work centers
Work center Number of Set up per Total set up Speed per Speed per
machines machine time machine work center
(minute/piece) (minute/piece)
Royal/Queen 3 180 540 0.0023 0.00077
Staudes 4 40 160 0.015 0.00375
difference in setup time 380 minutes
in 380 minutes, Staudes center can process 101,333 pieces
after both setups; the production breakeven point can be calculated as :
x is minutes of both machines in process
Staudes Royal/Queen
101333 + x * 1/0.00375 x*1/0.00077
x= 98 minutes
Breakeven point in time is 98 minutes after Royal/Queen's setup.
in 98 minutes, Royal/Queen can process 98/0.00077 pieces.
Breakeven point in pieces is : 127.506 piece
Conclusion; in the 380 minutes set up time needed to set up the same order on Royal Queen,
the Staudes can produce 101.333 pieces. After both machines are operational, it takes 98
minutes to Royal/Queen to catch up. Therefore, orders up until 127.506 pieces should be
routed to the Staudes.
Note: this result relates to the Royal/Queen and Staude CENTERS (i.e. all machines combined)
Number of Pieces produced by Royal/Queen Number of Pieces produced by Staude
500000
450000
400000
350000
300000
250000
200000
150000
100000
50000
0
20 60 100 140 180 220 260 300 340 380 420 460 500 540 580 620 660 700 740 780 820 860 900
Figure 1 : Illustration of the breakeven point of Royal/Queen vs Staude work centers in a work day.
See appendix 2 for data source of the graph.
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9. 2E. Yield per work center
Work Center Pieces out sheets (3 Scheduled Production loss
(exhibit 3) pcs./sheet) pieces
Sheet 9,488,211 3,185,032 9,555,096 66,885
Print 9,326,912 3,162,737 9,488,211 161,299
Case (i)
Die-cut 9,233,643 3,108,971 9,326,913 93,270
Royal Queen 5,588,396 6,209,329 620,933
Total 33,637,162 34,579,549 942,387
Percentage of loss throughout the process 2.80%
Case (ii)
The cumulative yield for an order which the sheeter starts with 40,000 sheets
40,000 * (1-2.8%) = 38,880 pieces yield
2F. Neil Rand’s performance evaluation
Evaluating Neil Rand’s performance using the key performance measures dependability, quality,
speed, costs and flexibility, it is safe to say that he performs well on these measures:
Dependability – ‘he makes sure it happens’ (p.7)
Quality – ‘he is a good set up man in fold and glue’ (p.7)
Speed - ‘His orders are never late’, ‘he puts it on a machine right away’ (p.7)
Flexibility – ‘Neil worked all over the factory’ (p.7)
We cannot evaluate his performance on the ‘cost’ performance measure for lack of information.
However, when he puts rush orders on machines right away he increase the costs of other orders
due to additional set ups required.
From the position of John Milliken, the new VP of Operations, the performance of Neil Rand could be
evaluated as ‘not good’. By handling the rush orders the way he does, he solves one problem, but
creates new problems elsewhere (‘he puts it on a machine right away’ – this may result in two new
rush orders since the machines cannot be used for the scheduled orders). This way of prioritizing, in
which the regular process flow is disturbed, as enabled by Neil Rand, may actually harm the company
in the long run.
His presence is obscuring the underlying problems which may therefore not be addressed.
Neil Rand is very useful to the company due to his extensive experience. He would be useful to the
company in the F&G department since he knows how to set up the machines and this department
has quality issues (glue).
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10. Question 3. What are the root causes of Bayonne Packaging, Inc.’s performance problems?
We have determined the root causes of Bayonne Packaging, Inc.’s problems to be as follows.
A lack of capacity to deal with variability
The process is running at full capacity but there is no buffer to deal with variability in customer
orders. The variability of delivery time, order type, order time, has increased.
The variability of delivery time, order type and order time has increased without any changes to the
process.
Communications
There is a lack of effective communication between the various departments within Bayonne
Packaging, Inc. and between Bayonne Packaging, Inc. and its customers.
The lack of effective communication between departments causes the department managers take
their own decisions without consideration of the consequences for other departments.
Lack of effective communications about waiting times and a poor track record on meeting delivery
deadlines causes variability and unpredictability in customer orders.
Quality
The pressure of meeting delivery deadlines and insufficient maintenance causes quality problems.
4. Recommendations to Dave Rand
We recommend the following actions to Dave Rand.
Short term actions (0 – 3 months)
- Increase capacity by allowing for overtime. This takes the strain off the process and allows
coping with variability better.
- Facilitate the ganging of orders as a means of increasing capacity.
- Daily meetings discussing production issues with all departments, changing the nature of
these meetings by looking further ahead.
- Introduce a system of prioritizing orders (e.g. red flags for rush orders) and weigh the
consequences of rush orders for the remaining orders, therewith optimizing (i.e. reducing)
the number of rush orders.
- Increase / improve maintenance on machines in order to increase quality.
Mid-term actions (3 – 9 months)
- Manage variability better by managing of demand e.g. introducing price reductions for bulk
orders
- Increase capacity by widening the bottle neck (e.g. extra shift on the Heidelberg press).
- Introduce pre-Work Order Jacket – a report that is sent to other departments when the prior
department starts working on and order. This way, the later department knows what orders
are on the way in couple of days.
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11. Long term actions (9 months and longer)
- Due to the expected increase in volume and to solve the current bottleneck it is
recommended to increase capacity by investing in additional equipment
- Introduce a companywide ERP system in order to schedule production in reliable, achievable
way that is adhered to by all departments (including sales). This should result in fewer rush
orders, fewer partial orders and less unnecessary set up time.
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12. Appendix 1 : Gantt Chart of Die-cut center in three cases (Answer 2B)
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13. Appendix 2: Order size for the Royal / Queen and Staude work centers (Answer 2D)
Number of Pieces Number of Pieces Time in Process
produced by produced by Staude minutes
Royal/Queen
Staude set up period
0 0 20
0 0 40
0 0 60
0 0 80
0 0 100
0 0 120
0 0 140
0 0 160
0 5333 180
Royal/Queen set up period
0 10667 200
0 16000 220
0 21333 240
0 26667 260
0 32000 280
0 37333 300
0 42667 320
0 48000 340
0 53333 360
0 58667 380
0 64000 400
0 69333 420
0 74667 440
0 80000 460
Staude process period
0 85333 480
0 90667 500
0 96000 520
0 101333 540
26087 106667 560
52174 112000 580
78261 117333 600
104348 122667 620 Breakeven
Royal/Queen process period
130435 128000 640 point
156522 133333 660
182609 138667 680
208696 144000 700
234783 149333 720
260870 154667 740
286957 160000 760
313043 165333 780
339130 170667 800
365217 176000 820
391304 181333 840
417391 186667 860
443478 192000 880
469565 197333 900
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