Hill A.V. The Encyclopedia of Operations Management: A Field Manual and Glossary of Operations Management Terms and Concepts
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CAM – Capability Maturity Model (CMM)
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The Erlang C formula is commonly used to determine staffing levels in any time period. (See the queuing
theory entry for more information.)
See Automatic Call Distributor (ACD), cross-selling, customer service, help desk, knowledge management,
order entry, pooling, queuing theory, service management, shrinkage.
CAM – See Computer Aided Manufacturing.
cannibalization – The sales of a new product that will be taken from the firm’s other products.
For example, a new computer model might take sales from an existing model and therefore add nothing to
the firm’s overall market share or bottom line.
See market share.
cap and trade – A system of financial incentives put in place by the government to encourage corporations to
reduce pollution.
The government issues emission permits that set limits (caps) for the pollution that can be emitted.
Companies that produce fewer emissions can sell their excess pollution credits to those that produce more.
See carbon footprint, green manufacturing, sustainability.
capability – See Design for Six Sigma (DFSS), process capability and performance.
Capability Maturity Model (CMM) – A five-level methodology for measuring and improving processes.
CMM began as an approach for evaluating the “maturity” of software development organizations, but has
since been extended to other organizations. Many capability maturity models have been developed for software
acquisition, project management, new product development, and supply chain management. This discussion
focuses on the Capability Maturity Model for Software (SW-CMM), which is one of the best-known products of
the Carnegie Mellon University Software Engineering Institute (SEI). CMM is based heavily on the book
Managing the Software Process (Humphries 1989). The actual development of the SW-CMM was done by the
SEI at Carnegie Mellon University and the Mitre Corporation in response to a request to provide the federal
government with a method for assessing the capability of its software contractors.
The SW-CMM model is used to score an organization on five maturity levels. Each maturity level includes a
set of process goals. The five CMM levels follow:
Level 1: Initial – The software process is characterized as ad hoc and occasionally even chaotic. Few
processes are defined and success depends on individual effort and heroics. Maturity level 1 success depends on
having quality people. In spite of this ad hoc, chaotic environment, maturity level 1 organizations often produce
products and services that work; however, they frequently exceed project budgets and schedules. Maturity level
1 organizations are characterized by a tendency to over-commit, abandon processes in the time of crisis, repeat
past failures, and fail to repeat past successes.
Level 2: Repeatable – Basic project management processes are established to track cost and schedule
activities. The minimum process discipline is in place to repeat earlier successes on projects with similar
applications and scope. There is still a significant risk of exceeding cost and time estimates. Process discipline
helps ensure that existing practices are retained during times of stress. When these practices are in place, projects
are performed and managed according to their documented plans. Project status and the delivery of services are
visible to management at defined points (for example, at major milestones and at the completion of major tasks).
Level 3: Defined – The software process for both management and engineering activities is documented,
standardized, and integrated into a standard software process for the organization. All projects use an approved,
tailored version of the organization’s standard software process for developing and maintaining software. A
critical distinction between maturity levels 2 and 3 is the scope of standards, process descriptions, and
procedures. At level 2, the standards, process descriptions, and procedures may be quite different in each
specific instance of the process (for example, on a particular project). At maturity level 3, the standards, process
descriptions, and procedures for a project are tailored from the organization’s set of standard processes to suit a
particular project or organizational unit.
Level 4: Managed – Detailed measures of the software process and product quality are collected. Both the
software process and products are quantitatively understood and controlled. Using precise measurements,
management can effectively control the software development effort. In particular, management can identify
ways to adjust and adapt the process to particular projects without measurable losses of quality or deviations
from specifications. At this level, the organization sets a quantitative quality goal for both the software process
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and software maintenance. A critical distinction between maturity level 3 and maturity level 4 is the
predictability of process performance. At maturity level 4, the process performance is controlled using statistical
and other quantitative techniques and is quantitatively predictable.
Level 5: Optimizing – Maturity level 5 focuses on continually improving process performance through both
incremental and innovative technological improvements. Quantitative process-improvement objectives for the
organization are established, continually revised to reflect changing business objectives, and used as criteria in
managing process improvement. The effects of deployed process improvements are measured and evaluated
against the quantitative process-improvement objectives. Both the defined processes and the organization’s set
of standard processes are targets of measurable improvement activities. Process improvements to address
common causes of process variation and measurably improve the organization’s processes are identified,
evaluated, and deployed. The organization’s ability to rapidly respond to changes and opportunities is enhanced
by finding ways to accelerate and share learning. A critical distinction between maturity level 4 and maturity
level 5 is the type of process variation addressed. At level 4, processes are concerned with addressing special
causes of process variation and providing statistical predictability of the results. At level 5, processes are
concerned with addressing common causes of process variation and changing the process to improve process
performance (while maintaining statistical probability) and achieve the established quantitative process-
improvement objectives.
Although these models have proven useful to many organizations, the use of multiple models has been
problematic. Further, applying multiple models that are not integrated within and across an organization is costly
in terms of training, appraisals, and improvement activities. The CMM Integration project (CMMI) was formed
to sort out the problem of using multiple CMMs. The CMMI Product Team’s mission was to combine the
following:
• The Capability Maturity Model for Software (SW-CMM) v2.0 draft C
• The Systems Engineering Capability Model (SECM)
• The Integrated Product Development Capability Maturity Model (IPD-CMM) v0.98
• Supplier sourcing
CMMI is the designated successor of the three source models. The SEI has released a policy to sunset the
Software CMM and previous versions of the CMMI.
Many of the above concepts are from http://en.wikipedia.org/wiki/Capability_Maturity_Model #Level_1_-
_Initial (November 4, 2006).
Interestingly, maturity level 5 is similar to the ideals defined in the lean sigma and lean philosophies.
See common cause variation, lean sigma, lean thinking, operations performance metrics.
capacity – (a) Process context: The maximum rate of output for a process, measured in units of output per unit of
time; (b) Space/time/weight context: The maximum space or time available or the maximum weight that can be
tolerated.
This entry focuses on definition (a). The unit of time may be of any length (a day, a shift, a minute, etc.).
Note that it is redundant (and ignorant) to use the phrase “maximum capacity” because a capacity is a maximum.
Some sources make a distinction between several types of capacities:
Rated capacity, also known as effective capacity, nominal capacity, or calculated capacity, is the
expected output rate for a process based on planned hours of operation, efficiency, and utilization. Rated
capacity is the product of three variables, hours available, efficiency, and utilization.
Demonstrated capacity, also known as proven capacity, is the output rate that the process has actually
been able to sustain over a period of time. However, demonstrated capacity is affected by starving (the process is
stopped due to no input), blocking (the process is stopped because it has no room for output), and lack of market
demand (we do not use capacity without demand).
Theoretical capacity is the maximum production rate based on mathematical or engineering calculations,
which sometimes do not consider all relevant variables; therefore, it is quite possible that the capacity can be
greater than or less than the theoretical value. It is fairly common for factories to work at 110% of their
theoretical capacity.
Capacity should not be confused with load. If an elevator has three people on it, what is its capacity? This is
a trick question. The capacity might be 2, 3, 20, or 99. If it has three people on it, the elevator has a current load
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of three and probably has a capacity of at least three. For many years, this author wrote APICS certification
exam questions related to this concept. It was amazing how many people answered this question incorrectly.
The best capacity will minimize the total relevant cost, which is the sum of the capacity and waiting costs.
All systems have a trade-off between capacity utilization and waiting time. These two variables have a non-
linear relationship. As utilization goes to 100%, the waiting time tends to go to infinity. Maximizing utilization
is not the goal of the organization. The goal of capacity management is to minimize the sum of two relevant
costs: the cost of the capacity and the cost of waiting.
For example, the optimal utilization for a fire engine is not 100%, but much closer to 1%. Utilization for an
office copy machine should be relatively low because the cost of people waiting is usually higher than the cost of
the machine waiting. One humorous question to ask students is: “Should you go make copies to keep the
machine utilized?” The answer, of course, is “no” because utilization is not the goal. The goal, therefore, is to
find the optimal balance between the cost of the machine and the cost of people waiting.
In contrast, some expensive machines, such as a bottling system, will run three shifts per day 365 days per
year. The cost of downtime is the lost profit from the system and can be quite expensive.
In a manufacturing context, capacity management is executed at four levels: Resource Requirements
Planning (RRP), Rough Cut Capacity Planning (RCCP), Capacity Requirements Planning (CRP), and
input/output control. See those entries in this encyclopedia to learn more.
The newsvendor model can be used to find the optimal capacity. The model requires that the analyst define
a time horizon, estimate the distribution of demand, and estimate the cost of having one unit of capacity too
much and the cost of having one unit of capacity too little.
In some markets, customers can buy capacity rather than products. For example, a customer might buy the
capacity of a supplier’s factory for one day per week. This can often help the customer reduce the procurement
leadtime. Of course, if the customer does not use the capacity, the supplier will still be paid.
See absorptive capacity, bill of resources, bottleneck, capacity management, Capacity Requirements
Planning (CRP), closed-loop MRP, downtime, input/output control, Little’s Law, load, newsvendor model,
Overall Equipment Effectiveness (OEE), process design, queuing theory, Resource Requirements Planning
(RRP), Rough Cut Capacity Planning (RCCP), safety capacity, utilization, yield management.
capacity cushion – See safety capacity.
capacity management – Planning, building, measuring, and controlling the output rate for a process.
See capacity.
Capacity Requirements Planning (CRP) – The planning process used in conjunction with Materials
Requirements Planning (MRP) to convert open and planned shop orders into a load report in planned shop hours
for each workcenter.
The CRP process is executed after the MRP planning process has produced the materials plan, which
includes the set of all planned and open orders. CRP uses the order start date, order quantity, routing, standard
setup times, and standard run times to estimate the number of shop hours required for each workcenter. It is
possible for CRP to indicate that a capacity problem exists during specific time periods even when Resource
Requirements Planning (RRP) and Rough Cut Capacity Planning (RCCP) have indicated that sufficient
capacity is available. This is because RRP and RCCP are not as detailed as CRP with respect to timing the load.
The output of the CRP process is the capacity plan, which is a schedule showing the planned load (capacity
required) and planned capacity (capacity available) for each workcenter over several days or weeks. This is also
called a load profile.
See Business Requirements Planning (BRP), capacity, closed-loop MRP, input/output control, Master
Production Schedule (MPS), Materials Requirements Planning (MRP), planned order, Resource Requirements
Planning (RRP), Rough Cut Capacity Planning (RCCP), routing, Sales & Operations Planning (S&OP).
capacity utilization – See utilization.
CAPEX – An abbreviation for the CAPital EXpenditure used as the initial investment in new machines, equipment,
and facilities.
See capital.
capital – Money available for investing in assets that produce output.
See CAPEX, capital intensive.
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capital intensive
– Requiring a large expenditure of capital in comparison to labor.
A capital intensive industry requires large investments to produce a particular good. Good examples include
power generation and oil refining.
See capital, labor intensive.
carbon footprint
– A measure of the carbon dioxide (CO
2
) and other greenhouse gas emissions released into the
environment by a person, plant, organization, or state; often expressed as tons of carbon dioxide per year.
The carbon footprint takes into account energy use (heat, cooling, light, power, and refrigeration),
transportation, and other means of emitting carbon.
See cap and trade, energy audit, green manufacturing, triple bottom line.
cargo
– Goods transported by a vehicle; also called freight.
See logistics, shipping container.
carousel
– A rotating materials handling device used to store and retrieve smaller parts for use in a factory or
warehouse.
Carousels are often automated and used for picking small parts in a high-volume
business. The carousel brings the part location to the picker so the picker does not have
to travel to the bin location to store or retrieve a part. Both horizontal and vertical
carousels are used in practice. The photo on the right is a vertical carousel.
See Automated Storage & Retrieval System (AS/RS), batch picking, picking,
warehouse.
carrier
– (1) In a logistics context: An organization that transports goods or people in its
own vehicles. (2) In a telecommunications context: An organization that offers
communication services. (3) In an insurance context: An organization that provides risk management services.
Carriers may specialize in small packages, less than truck load (LTL), full truck loads (TL), air, rail, or sea.
In the U.S., a carrier involved in interstate moves must be licensed by the U.S. Department of Transportation.
The shipper is the party that initiates the shipment.
See common carrier, for-hire carrier, less than truck load (LTL), logistics.
carrying charge
– The cost of holding inventory per time period, expressed as a percentage of the unit cost.
This parameter is used to help inventory managers make economic trade-offs between inventory levels, order
sizes, and other inventory control variables. The carrying charge is usually expressed as the cost of carrying one
monetary unit (e.g., dollar) of inventory for one year and therefore has a unit of measure of $/$/year. Reasonable
values are in the range of 15-40%.
The carrying charge is the sum of four factors: (1) the marginal cost of capital or the weighted average cost
of capital (WACC), (2) a risk premium for obsolete inventory, (3) the storage and administration cost, and (4) a
policy adjustment factor. This rate should only reflect costs that vary with the size of the inventory and should
not include costs that vary with the number of inventory transactions (orders, receipts, etc.). A good approach for
determining if a particular cost driver should be included in the carrying charge is to ask the question, “How will
this cost be affected if the inventory is doubled (or halved)?” If the answer is “not at all,” that cost driver is
probably not relevant (at least not in the short-term). It is difficult to make a precise estimate for the carrying
charge. Many firms erroneously set it to the WACC and therefore underestimate the cost of carrying inventory.
See carrying cost, Economic Order Quantity (EOQ), hockey stick effect, inventory turnover, marginal cost,
obsolete inventory, production planning, setup cost, shrinkage, weighted average.
carrying cost
– The marginal cost per period for holding one unit of inventory (typically a year).
The carrying cost is usually calculated as the average inventory investment times the carrying charge. For
example, if the annual carrying charge is 25% and the average inventory is $100,000, the carrying cost is $25,000
per year. Many firms incorrectly use the end-of-year inventory in this calculation, which is fine if the end-of-
year inventory is close to the average inventory during the year. However, it is quite common for firms to have a
“hockey stick” sales and shipment pattern where the end-of-year inventory is significantly less than the average
inventory during the year. Technically, this type of average is called a “time-integrated average” and can be
estimated fairly accurately by averaging the inventory at a number of points during the year.
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cash cow
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Manufacturing and inventory managers must carefully apply managerial accounting principles in decision
making. A critical element in many decisions is the estimation of the inventory carrying cost, sometimes called
the “holding cost.” Typical decisions include the following:
Service level trade-off decisions – Many make to stock manufacturers, distributors, and retailers sell
standard products from inventory to customers who arrive randomly. In these situations, the firm’s service
level improves with a larger finished goods inventory. Therefore, trade-offs have to be made between
inventory carrying cost and service.
Lot size decisions – A small order size requires a firm to place many orders, which results in a small “cycle”
inventory. Assuming instantaneous delivery with order quantity Q, the average cycle inventory is
approximately Q/2. Even though small manufacturing order sizes provide low average cycle inventory, they
require more setups, which, in turn, may require significant capacity leading to a large queue inventory and a
large overall carrying cost.
Hedging and quantity discount decisions – Inventory carrying cost is also an important issue when
evaluating opportunities to buy in large quantities or buy early to get a lower price. These decisions a total
cost model to make evaluate the economic trade-offs between the carrying cost and the purchase price.
In-sourcing versus outsourcing decisions – When trying to decide if a component or a product should be
manufactured in-house or purchased from a supplier, the inventory carrying cost is often a significant factor.
Due to longer leadtimes, firms generally increase inventory levels to support an outsourcing decision. It is
important that the proper carrying cost be used to support this analysis.
The above decisions require a “managerial economics” approach to decision making, which means that the
only costs that should be considered are those costs that vary directly with the amount of inventory. All other
costs are irrelevant to the decision.
The carrying charge is a function of the following four variables:
Cost of capital – Firms have alternative uses for money. The cost of capital reflects the opportunity cost of
the money tied up in the inventory.
Storage cost – The firm should consider only those storage costs that vary with the inventory level. These
costs include warehousing, handling, insurance and taxes, depreciation, and shrinkage.
Obsolescence risk – The risk of obsolescence tends to increase with inventory, particularly for firms that
deal with high technology products, such as computers, or perishable products, such as food.
Policy adjustment – This component of the carrying cost reflects management’s desire to pursue this policy
and is based on management intuition rather than hard data.
When estimating the unit cost for the carrying cost calculation, most authors argue for ignoring allocated
overhead. However, given that it is difficult for most organizations to know their unit cost without overhead, it is
reasonable for them to use the fully burdened cost and use the appropriate carrying charge that does not double
count handling, storage, or other overhead costs.
See carrying charge, Economic Order Quantity (EOQ), hockey stick effect, Inventory Dollar Days (IDD),
inventory management, inventory turnover, marginal cost, materials management, opportunity cost, outsourcing,
overhead, production planning, quantity discount, service level, setup cost, shrinkage, weighted average.
cash cow
– The firm or business unit that holds a
strong position in a mature industry and is being
“milked” to provide cash for other business
units; the cash cow is often in a mature industry
and therefore not a good place for significant
new investment.
The Boston Consulting Group (BCG)
Growth-Share Matrix can help managers set
investment priorities for the product portfolio in
a business unit or for business units in a multi-
divisional firm. Stars are high growth/high
6
The figure above is different from the original because it puts high market share on the right rather than the left.
The BCG Growth-Share Matrix
6
Market
growth rate
High
Question marks Stars
Low
Dogs Cash cows
Low High
Relative position (market share)
Adapted by Professor Arthur V. Hill
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market share products or business units. Cash cows have low growth but high market share and can be used to
supply cash to the firm. Dogs have low growth and low market share and should be either fixed or liquidated.
Question marks have high growth, but low market share; a few of these should be targeted for investment while
the others should be divested. Stern and Deimler (2006) and Porter (1985) provide more detail.
See operations strategy.
Cash on Delivery (COD)
– Contract terms that require payment for goods and transportation at time of delivery.
See FOB, terms, waybill.
casting
– See foundry.
catchball
– A lean term used to describe an iterative top-down/bottom-up process in which plans
are “thrown” back and forth between two levels in an organization until the participants at the
different levels come to a shared understanding.
The term “catchball” is a metaphor used in the hoshin planning process for participative
give-and-take discussions between two levels of an organization when creating a strategic plan.
Catchball can help an organization achieve buy-in, find agreement, build a shared
understanding, and create detailed execution plans for both the development and execution of a strategy.
Catchball is “played” between multiple levels of the organization to ensure that the strategic plan is embraced
and executable at every level.
The strategic planning process in many organizations has two common issues: (1) the plan is difficult to
implement because the higher-level management is out of touch with the details, and (2) the lower-level
managers do not understand the rationale behind the plan and therefore either passively resist or actively oppose
the new strategy. With catchball, higher-level management develops a high-level plan and then communicates
with the next layer of management to gain understanding and buy-in. Compared to other types of strategic
planning, catchball usually results in strategic plans that are embraced by a wider group of managers and are
more realistic (e.g., easier to implement).
Catchball essentially has two steps: (1) conduct an interactive session early in the planning process to give
the next level of management the opportunity to ask questions, provide feedback, and challenge specific items,
and (2) have the next level managers develop an execution plan for the higher-level initiatives and toss it back to
the higher-level managers for feedback and challenges.
Catchball is comparable to agile software development where software ideas are tested early and often,
which leads to better software. The same is true for strategy development with catchball where strategic plans
are tested early and often. Both concepts are similar to the idea of small lotsizes and early detection of defects.
See agile software development, early detection, hoshin planning, lean thinking, operations strategy,
prototype.
category captain
– A role given by a retailer to a representative from a supplier to help the retailer manage a
category of products.
It is a common practice for retailers in North America to select one supplier in a category as the category
captain. A retailer usually (but not always) selects the category captain as the supplier with the highest sales in
the category. The supplier then selects an individual among its employees to serve in the category captain’s role.
Traditionally, the category captain is a branded supplier; however, the role is sometimes also given to private
label suppliers. Category captains often have their offices at the customer’s sites.
The category captain is expected to work closely with the retailer to provide three types of services:
Analyze data:
Analyze category and channel data to develop consumer and business insights across the entire category.
Perform competitive analyses by category, brand, and package to identify trends.
Analyze consumer purchasing behavior by demographic profile to understand consumer trends by channel.
Audit stores.
Develop and present plans:
Develop business plans and strategies for achieving category volume, margin, share, space, and profit targets.
Help the retailer build the planogram for the category.
Prepare and present category performance reviews for the retailer.
Participate in presentations as a credible expert in the category.
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Support the retailer:
Respond quickly to the retailer’s requests for information.
Provide the retailer with information on shelf allocation in a rapidly changing environment.
Educate the retailer’s sales teams.
Advise the retailer on shelving standards and associated software tools.
Craig Johnson, a Kimberly-Clark category captain at Target, adds, “Most category captains also have
responsibilities within their own company as well and have to balance the needs of their retailer with internal
company needs. It can get hairy sometimes.”
7
The category captain must focus on growing the category, even if requires promoting competing products
and brands. This practice will lead to the growth of the entire category and therefore be in the best interests of
the supplier. In return for this special relationship, the supplier will have an influential voice with the retailer.
However, the supplier must be careful never to abuse this relationship or violate any antitrust laws.
The category captain is usually given access to the retailer’s proprietary information, such as point-of-sale
(POS) data. This information includes sales data for all suppliers that compete in the category. The retailer and
category captain will usually have an explicit agreement that requires the captain to use this data only for
category management and not share it with anyone in the supplier’s company.
Retailers will sometimes assign a second competing supplier as a category adviser called the “category
validator.” In theory, the validator role was created as a way for the retailer to compare and evaluate the category
captain’s recommendations. In practice, however, the adviser is usually used by the retailer as another category
management resource. The adviser conducts ad hoc category analyses at the request of the retailer, but does not
usually duplicate the services provided by the captain.
See antitrust laws, assortment, category killer, category management, consumable goods, consumer
packaged goods, Fast Moving Consumer Goods (FMCG), planogram, Point-of-Sale (POS), private label.
category killer – A term used in marketing and strategic management to describe a dominant product or service
that tends to have a natural monopoly in a market.
One example of a category killer is eBay, an on-line auction website that attracts large numbers of buyers
and sellers simply because it is the largest on-line auction. Other examples include “big box” retailers, such as
Home Depot, that tend to drive smaller “mom and pop” retailers out of business.
See big box store, category captain, category management.
category management – The retail practice of segmenting items (SKUs) into groups called categories to make it
easier to manage assortments, inventories, shelf-space allocation, promotions, and purchases.
Benefits claimed for a good category management system include increased sales due to better space
allocation and better stocking levels, lower cost due to lower inventories, and increased customer retention due to
better matching of supply and demand. Category management in retailing is analogous to the commodity
management function in purchasing.
See assortment, brand, category captain, category killer, commodity, consumable goods, consumer packaged
goods, Fast Moving Consumer Goods (FMCG), private label.
category validator – See category captain.
causal forecasting – See econometric forecasting, forecasting.
causal map – A graphical tool often used for identifying the root causes of a problem; also known as a cause and
effect diagram (C&E Diagram), Ishikawa Diagram, fishbone diagram, cause map, impact wheel, root cause tree,
fault tree analysis, and current reality trees.
A causal map is a diagram that shows the cause and effect relationships in a system. Causal maps can add
value to organizations in many ways:
Process improvement and problem solving – Causal maps are a powerful tool for gaining a deep
understanding of any problem. As the old adage goes, “A problem well-defined is a problem half-solved.”
The causal map is a great way to help organizations understand the system of causes that result in blocked
goals and then find solutions to the real problems rather than just the symptoms of the problems. People
7
Email communication with the author in the fall of 2010.
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think in “visual” ways. A good causal map is worth 1000 words and can significantly reduce meeting time
and the time to achieve the benefit from a process improvement project.
Supporting risk mitigation efforts – Causal maps are a powerful tool for helping firms identify possible
causes of problems and develop risk mitigation strategies for these possible causes.
Gaining consensus – The brainstorming process of creating a causal map is also a powerful tool for “gaining
a shared understanding” of how a system works. The discussion, debate, and deliberation process in building
a causal map is often more important than the map itself.
Training and teaching – A good causal map can dramatically reduce the time required to communicate
complex relationships for training, teaching, and documentation purposes.
Identifying the critical metrics – Many organizations have too many metrics, which causes managers to
lose sight of the critical variables in the system. A good causal map can help managers identify the critical
variables that drive performance and require high-level attention. Focusing on these few critical metrics
leads to strategic alignment, which in turn leads to organizational success.
Many types of causal maps are used in practice, including Ishikawa Diagrams (also known as fishbone
diagrams, cause and effect diagram, and C&E Diagrams), impact wheels (from one cause to many effects), root
cause trees (from one effect to many causes), and strategy maps. The Ishikawa Diagram was developed by Dr.
Kaoru Ishikawa (1943-1969) and is by far the most popular form of a causal map. The Ishikawa Diagram is a
special type of a causal map that shows the relationships between the problem (at the “head” of the fishbone on
the right) and the potential causes of a problem. The figure below is a simple example of an Ishikawa Diagram
for analyzing long waiting lines for tellers in a bank.
The Ishikawa Diagram is
usually developed in a
brainstorming context. The
process begins by placing the
name of a basic problem of
interest at the far right of the
diagram at the “head” of the main
“backbone” of the fish. The
main causes of the problem are
drawn as bones off the main
backbone. Many firms prescribe six causes: machines (equipment), methods, measurement, materials,
manpower (labor), and Mother Nature (environment). However, many argue that this list is overly confining and
a bit sexist. Brainstorming is typically done to add possible causes to the main bones and more specific causes to
the bones on the main bones. This subdivision into ever-increasing specificity continues as long as the problem
areas can be further subdivided. The practical maximum depth of this tree is usually about four or five levels.
The Ishikawa Diagram is limited in many ways:
It can only analyze one output variable at a time.
Some people have trouble working backward from the problem on the far right side of the page.
It is hard to read and even harder to draw, especially when the problem requires many levels of causation.
The diagram is also hard to create on a computer.
The alliteration of Ms is sexist with the terms “manpower” and “Mother Nature.”
The six Ms rarely include all possible causes of a problem.
Causal maps do not have any of these limitations.
The Ishikawa Diagram starts with the result on the right. With root cause trees, current reality trees (Goldratt
1994), and strategy maps (Kaplan & Norton 2004), the result is usually written at the top of the page. With an
FMEA analysis and issues trees, the result is written on the left and then broken into its root causes on the right.
The causal map diagram below summarizes the 304-page book Competing Against Time (Stalk & Hout
2003) in less than a half-page. This is a strategy map using a causal map format rather than the Kaplan and
Norton (1992) four-perspective strategy map format. This time-based competition strategy reduces cycle
times, cost, and customer leadtimes. Reducing customer leadtimes segments the market, leaving the price-
No queue informationInefficient processNot enough ma chines
Long
lines
Machines Methods Measurement
Machine failures
Lack of forms Not enough tellers Storm power outa ge
Source: Arthur V. Hil
l
Materials Manpower Mother Nature
Ishikawa Diagram example
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causal map – causal map
The Encyclopedia of Operations Management Page 64
sensitive customers to the competition. This strategy map could be taken a step further to show how the firm
could achieve lower cycle time through setup time reduction, vendor relationships, 5S, and plant re-layout.
Regardless of the format used, these diagrams are usually created through a brainstorming process, often
with the help of 3M Post-it Notes. The team brainstorms to identify the root causes of each node. The process
continues until all causes (nodes) and relationships (arcs) have been identified. It is possible that “loops” will
occur in the diagram. A loop can occur for a vicious cycle or virtuous cycle. For example, a vicious cycle
occurs when an alcoholic person drinks and is criticized by family members, which may, in turn, cause him or
her to drink even more, be criticized further, etc. A virtuous cycle is similar, except that the result is positive
instead of negative.
Scavarda, Bouzdine-Chameeva, Goldstein, Hays, and Hill (2006) developed a method for building collective
causal maps with a group of experts. This method assigns weights to each causal relationship and results in a
meaningful graphical causal map, with the more important causal relationships shown with darker arrows.
Many software tools are available to help brainstorm and document the cause and effect diagrams. However,
Galley (2008) insists that Excel is the best tool.
The C&E Matrix provides a means for experts to assign weights to certain causal input variables. The same
can be done with a causal map. All that needs to be done is to score each input variable on several dimensions
that are important to customers and then create a weighted score for each input variable. Priority is then given to
those variables that are believed to have the most impact on customers. Alternatively, experts can “vote” (using
multi-voting) for the causes that they believe should be the focus for further analysis.
Causal maps should not be confused with concept maps, knowledge maps, and mindmaps that nearly
always show similarities (but not causality) between objects. For example, monkeys and apes are very similar,
but monkeys do not cause apes. Therefore, a knowledge map would show a strong connection between monkeys
and apes, but a causal map would not.
Hill (2011b, 2011c) provides more detail on this subject.
See 5 Whys, affinity diagram, Analytic Hierarchy Process (AHP), balanced scorecard, brainstorming, C&E
Diagram, C&E Matrix, current reality tree, decision tree, Failure Mode and Effects Analysis (FMEA), fault tree
analysis, future reality tree, hoshin planning, ideation, impact wheel, issue tree, lean sigma, MECE, mindmap,
Nominal Group Technique (NGT), Pareto Chart, Pareto’s Law, parking lot, process map, quality management,
Root Cause Analysis (RCA), root cause tree, sentinel event, seven tools of quality, strategy map, Total Quality
Management (TQM), value stream map, Y-tree.
Desired effect:
Profit up
Sales
up
Costs
down
Customer satisfaction
up
Margins
up
Capacity
up
Customer lead time
down
Time-sensitive
customer demand up
Ability to drive out
waste up
Inventory carrying
cost down
Finished goods
inventory down
Lower
cycle time
Process visibility up
Work in process
inventory down
MTS
MTO for
some products
Leadtime for FG
inventory down
Batchsize, variance,
& queues down
Scrap and rework
down
First pass yield up
Defects down
Early detection of
defects up
Need for complex IT
down
So ur ce:
Professor
Arthur V. Hill
ptg6843605
cause and effect diagram − cellular manufacturing
Page 65 The Encyclopedia of Operations Management
cause and effect diagram – See causal map.
cause map – A trademarked term for a causal map coined by Mark Galley of ThinkReliability.
Cause mapping is a registered trademark of Novem, Inc., doing business as ThinkReliability
(www.thinkreliability.com).
See causal map.
caveat emptor – A Latin phrase that means “buyer beware” or “let the buyer beware.”
This phrase means that the buyer (not the seller) is at risk with a purchase decision. The phrase “caveat
venditor” is Latin for “let the seller beware.”
See service guarantee, warranty.
CBT – See Computer Based Training (CBT).
c-chart – A quality control chart used to display and monitor the number of defects per sample (or per batch, per
day, etc.) in a production process.
Whereas a p-chart controls the percentage of units that are defective, a c-chart controls the number of defects
per unit. Note that one unit can have multiple defects. The Poisson distribution is typically used for c-charts,
which suggests that defects are rare.
See attribute, control chart, Poisson distribution, Statistical Process Control (SPC), Statistical Quality
Control (SQC), u-chart.
CDF – See probability density function.
cell – See cellular manufacturing.
cellular manufacturing – The use of a group of machines dedicated to processing parts, part families, or product
families that require a similar sequence of operations.
Concept – In a traditional functional (process) layout, machines and workers are arranged in workcenters by
function (e.g., drills or lathes), large batches of parts are moved between workcenters, and workers receive
limited cross-training on the one type of machine in their workcenter. With cellular manufacturing, machines
and workers are dedicated to making a particular type of product or part family. The machines in the cell,
therefore, are laid out in the sequence required to make that product. With cells, materials are moved in small
batches and workers are cross-trained on multiple machines and process steps. Cells are often organized in a U-
shaped layout so workers inside the “U” can communicate and help each other as needed. The figure below
contrasts functional and cellular layouts showing that cells can have a much higher value added ratio.
Advantages of a cell over a product layout – The advantages of a cell over a product layout include
reduced cycle time, travel time, setup time, queue time, work-in-process inventory, space, and materials handling
cost. Reduced cycle time allows for quicker detection of defects and simpler scheduling. When firms create
cells, they often cross-train workers in a cell, which leads to better engagement, morale, and labor productivity.
Some firms also implement self-managed work teams to develop workers, reduce overhead, and accelerate
process improvement.
Queue Queue Queue Queue
Work-
station 1
Work-
station 2
Work-
station 3
Work-
station 4
Functional (process) layout
5 days
½ day
5 days
½ day
5 days
½ day
5 days
½ day
Queue
Work-
station 1
Work-
station 2
Work-
station 3
Work-
station 4
Cellular layout
½ day ½ day
½ day
½ day
½ day
Queue
½ day
Functional layout value added ratio
Total cycle time = 22 days
Value added time = 2 days
N
on-value added time = 20 days
Value added ratio = 2/22 = 9%
Cellular layout value added ratio
Total cycle time = 3 days
Value added time = 2 days
N
on-value added time = 1 day
Value added ratio = 2/3 = 67%
Source: Arthur V. Hill