Case Notes/Answers
Coats Supply Chain Challenges By Willy Shih, Adina
Wong
Discussion Questions:
This case looks at a company whose business model was transformed by the advent of digital technology,
which enabled rapid consistent measurement of colors. In parallel to the technologica change, the
demands of accelerating fashion cycles drove a shift in the company’s manufacturing strategy as well. As
you read the case, please consider the following questions:
1. Looking at scale economies from using larger dye machines (Exhibit 10), as well as the relatively long
production cycles compared with customers’ desired lead times, how would you plan your production?
Your inventory? At what point would you transition from make to stock to make to order?
2. The company’s inventory classification scheme is based on the percentage of annual sales and
obsolescence exposure. Are there other criteria for the classification that you might consider? What
would be the advantages and disadvantages of adding additional criteria?
3. Look at the AA category in Exhibit 14 and consider the coefficient of variation for each SKU over the
course of 12 months. If you assume a normal distribution of orders over the course of a year for each SKU,
what level of inventory of each SKU would you need if you wanted to target a 90% fill rate on orders in a
given month (i.e., a 10% chance that you will not be able to fulfill some or all of an order)? How about
category “B” (Exhibits 15 and 16)?
4. Coats uses a make to stock policy for AA and A, and a make to order policy for C and D. What would you
recommend for B?
5. What is your overall assessment of Coats’s inventory policies?
6. Should the company move AA production from Bangladesh to Indonesia?
, 5 -6 2 2 -0 3 4
REV: NOVEMBER 1, 2023
TEACHING NOTE
Coats: Supply Chain Challenges
Coats, the largest thread maker in the world, has undergone two major transformations in the last
two decades. First, it moved its manufacturing base from Europe and North America to Asia as it
followed its customers east. Second, it transformed its business to use digital colour a measurement
technology so that it could respond better to garment industry demand for rapid product cycles and
more diverse colour choices. Its embrace of digital colour measurement technologies enabled much
shorter fulfilment cycles, but this created a monumental challenge in forecasting demand for the wide
spectrum of colours and thread types. The company shifted to an ABC inventory classification model
for make-to-stock versus make-to-order products. The question at hand was whether it should now
consolidate some of its high volume make-to-stock manufacturing in an ultra-low-cost location while
leaving the make-to-order products close to the customer.
Learning Objectives
This case aspires to connect several diverse topics in supply chain management, helping students
to:
1. Develop an understanding of how the digitization of a product feature that is traditionally very
subjective can transform operational processes across a value chain and have a major impact
on how business is conducted.
2. Introduce the concept of ABC inventory planning – classifying inventory based on
consumption value, the total value of an item consumed over a time period. This leads to
differentiated stocking and production strategies.
3. Probe more deeply into the differences between direct costs and indirect costs, and the
consequences of assigning production locations on cost absorption and hangover costs. Why
do we allocate costs? The instructor could also potentially introduce activity-based costing.
a The spelling colour is used in the English-speaking world outside the United States. Because Coats uses this spelling, it is used
throughout the case and teaching note.
, 622-034 Teaching Note—Coats: Supply Chain Challenges
Background
The Coats case is interesting because it is a very clear example of how digital technology enabled
the transformation of a supply chain. Before the widespread availability of digital color measurement,
the process of sampling and approval of colours was quite long, so the company’s customers were
conditioned to waiting for samples and production quantities. Coats used digital technology to shorten
these cycles, but also as a response to the demands of the fast fashion sector where product cycles were
much shorter. While deploying the technology was a competitive advantage (and necessity over time),
it also had significant back-end implications on the company’s manufacturing and logistics operations
and how it could plan for this type of quick response model. It meant increasing fragmentation in its
assortment, and more need for a make-to-order model, which was more expensive in terms of cost per
SKU, compared to larger batch production.
This teaching plan first seeks to establish how the traditional dye house model was highly
dependent on experienced colourists, and how this depended on often very subjective judgments. It
does this using several PowerPoint slides that almost appear to be optical illusions, but illustrate the
subtle perceptual issues associated with visual assessment of colour that make the process very prone
to error and drift. This will make apparent the powerful consequences of fast, reproducible (digital)
colour measurement and the impact on the whole value chain. This will be followed by a discussion of
the consequences on Coats’s manufacturing and inventory strategy, and touch on the company’s
implementation of an ABC classification model. Then it will look at the case question - the implications
of moving high volume SKUs to an ultra-low-cost production site.
Digital Color Measurement of Textiles
The colour approval process in garment manufacturing historically was a slow process, especially
when it depended on human visual perception and physical matching of samples. There are many
reasons for this difficulty, including accurate and repeatable spectral characterization of illumination,
and perceptual factors that cause the eye to be easily mislead. Such perceptual factors can be
demonstrated to students using the accompanying PowerPoint slides available to instructors. The
perception of a colour depended on three attributes: the spectral content of the object, the spectral
content of the light that illuminates the object, and the spectral response of the viewer. 1 The latter two
varied widely, for example the colour temperature of a light source measured by the corresponding
temperature of an ideal black-body radiator suggests that illumination can vary widely. Thus, rigorous
control is necessary to obtain repeatable measurements. The colour temperature of daylight (overcast
sky) is 6500 K, fluorescent lamps 5000 K, soft white incandescent lamps 2550 K, and a candle flame
2400 K, and the perceived colour will be very different under this range of lighting conditions.
Early research on human colour vision suggested that colours could be mathematically specified in
terms of three independent components, based on the observation that the human eye had three color
receptors, each with a unique spectral response. Thus, in principle any additive color mixture could be
matched by mixing the proper amount of three primary colours. This was known as a tristimulus
response model.
Digital technology offered the opportunity to precisely specify colours. As the case recounts, many
attempts had been made over the years to define a precise colour description system that correlated
well with visual assessment. In 1931, the Commission Internationale de l'Éclairage (CIE) defined the
first quantitative links between the wavelengths of light observed in the colour spectrum of an object
and the colours perceived by the human eye. This paralleled the tristimulus response model, and was
embodied in the CIE 1931 colour space, in which each colour was characterized as a combination of
2
Coats Supply Chain Challenges By Willy Shih, Adina
Wong
Discussion Questions:
This case looks at a company whose business model was transformed by the advent of digital technology,
which enabled rapid consistent measurement of colors. In parallel to the technologica change, the
demands of accelerating fashion cycles drove a shift in the company’s manufacturing strategy as well. As
you read the case, please consider the following questions:
1. Looking at scale economies from using larger dye machines (Exhibit 10), as well as the relatively long
production cycles compared with customers’ desired lead times, how would you plan your production?
Your inventory? At what point would you transition from make to stock to make to order?
2. The company’s inventory classification scheme is based on the percentage of annual sales and
obsolescence exposure. Are there other criteria for the classification that you might consider? What
would be the advantages and disadvantages of adding additional criteria?
3. Look at the AA category in Exhibit 14 and consider the coefficient of variation for each SKU over the
course of 12 months. If you assume a normal distribution of orders over the course of a year for each SKU,
what level of inventory of each SKU would you need if you wanted to target a 90% fill rate on orders in a
given month (i.e., a 10% chance that you will not be able to fulfill some or all of an order)? How about
category “B” (Exhibits 15 and 16)?
4. Coats uses a make to stock policy for AA and A, and a make to order policy for C and D. What would you
recommend for B?
5. What is your overall assessment of Coats’s inventory policies?
6. Should the company move AA production from Bangladesh to Indonesia?
, 5 -6 2 2 -0 3 4
REV: NOVEMBER 1, 2023
TEACHING NOTE
Coats: Supply Chain Challenges
Coats, the largest thread maker in the world, has undergone two major transformations in the last
two decades. First, it moved its manufacturing base from Europe and North America to Asia as it
followed its customers east. Second, it transformed its business to use digital colour a measurement
technology so that it could respond better to garment industry demand for rapid product cycles and
more diverse colour choices. Its embrace of digital colour measurement technologies enabled much
shorter fulfilment cycles, but this created a monumental challenge in forecasting demand for the wide
spectrum of colours and thread types. The company shifted to an ABC inventory classification model
for make-to-stock versus make-to-order products. The question at hand was whether it should now
consolidate some of its high volume make-to-stock manufacturing in an ultra-low-cost location while
leaving the make-to-order products close to the customer.
Learning Objectives
This case aspires to connect several diverse topics in supply chain management, helping students
to:
1. Develop an understanding of how the digitization of a product feature that is traditionally very
subjective can transform operational processes across a value chain and have a major impact
on how business is conducted.
2. Introduce the concept of ABC inventory planning – classifying inventory based on
consumption value, the total value of an item consumed over a time period. This leads to
differentiated stocking and production strategies.
3. Probe more deeply into the differences between direct costs and indirect costs, and the
consequences of assigning production locations on cost absorption and hangover costs. Why
do we allocate costs? The instructor could also potentially introduce activity-based costing.
a The spelling colour is used in the English-speaking world outside the United States. Because Coats uses this spelling, it is used
throughout the case and teaching note.
, 622-034 Teaching Note—Coats: Supply Chain Challenges
Background
The Coats case is interesting because it is a very clear example of how digital technology enabled
the transformation of a supply chain. Before the widespread availability of digital color measurement,
the process of sampling and approval of colours was quite long, so the company’s customers were
conditioned to waiting for samples and production quantities. Coats used digital technology to shorten
these cycles, but also as a response to the demands of the fast fashion sector where product cycles were
much shorter. While deploying the technology was a competitive advantage (and necessity over time),
it also had significant back-end implications on the company’s manufacturing and logistics operations
and how it could plan for this type of quick response model. It meant increasing fragmentation in its
assortment, and more need for a make-to-order model, which was more expensive in terms of cost per
SKU, compared to larger batch production.
This teaching plan first seeks to establish how the traditional dye house model was highly
dependent on experienced colourists, and how this depended on often very subjective judgments. It
does this using several PowerPoint slides that almost appear to be optical illusions, but illustrate the
subtle perceptual issues associated with visual assessment of colour that make the process very prone
to error and drift. This will make apparent the powerful consequences of fast, reproducible (digital)
colour measurement and the impact on the whole value chain. This will be followed by a discussion of
the consequences on Coats’s manufacturing and inventory strategy, and touch on the company’s
implementation of an ABC classification model. Then it will look at the case question - the implications
of moving high volume SKUs to an ultra-low-cost production site.
Digital Color Measurement of Textiles
The colour approval process in garment manufacturing historically was a slow process, especially
when it depended on human visual perception and physical matching of samples. There are many
reasons for this difficulty, including accurate and repeatable spectral characterization of illumination,
and perceptual factors that cause the eye to be easily mislead. Such perceptual factors can be
demonstrated to students using the accompanying PowerPoint slides available to instructors. The
perception of a colour depended on three attributes: the spectral content of the object, the spectral
content of the light that illuminates the object, and the spectral response of the viewer. 1 The latter two
varied widely, for example the colour temperature of a light source measured by the corresponding
temperature of an ideal black-body radiator suggests that illumination can vary widely. Thus, rigorous
control is necessary to obtain repeatable measurements. The colour temperature of daylight (overcast
sky) is 6500 K, fluorescent lamps 5000 K, soft white incandescent lamps 2550 K, and a candle flame
2400 K, and the perceived colour will be very different under this range of lighting conditions.
Early research on human colour vision suggested that colours could be mathematically specified in
terms of three independent components, based on the observation that the human eye had three color
receptors, each with a unique spectral response. Thus, in principle any additive color mixture could be
matched by mixing the proper amount of three primary colours. This was known as a tristimulus
response model.
Digital technology offered the opportunity to precisely specify colours. As the case recounts, many
attempts had been made over the years to define a precise colour description system that correlated
well with visual assessment. In 1931, the Commission Internationale de l'Éclairage (CIE) defined the
first quantitative links between the wavelengths of light observed in the colour spectrum of an object
and the colours perceived by the human eye. This paralleled the tristimulus response model, and was
embodied in the CIE 1931 colour space, in which each colour was characterized as a combination of
2
