Hill A.V. The Encyclopedia of Operations Management: A Field Manual and Glossary of Operations Management Terms and Concepts
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Economic Order Quantity (EOQ)
–
Economic Order Quantity (EOQ)
The Encyclopedia of Operations Management Page 116
Economic Order Quantity (EOQ)
– The optimal order quantity (batch size or lotsize) that minimizes the sum of
the carrying and ordering costs.
If the order quantity is too large, the firm incurs too much carrying cost; if the order quantity is too small, the
firm incurs too much ordering (setup) cost. The EOQ model can help managers make the trade-off between
ordering too much and ordering too little (Harris 1913, 1915; Wilson 1934). The EOQ finds the Fixed Order
Quantity that minimizes the sum of the ordering and carrying costs.
Define D as the annual demand in units, Q as the order quantity in units, S as the order cost per order, i as the
carrying charge per dollar per year, and c as the unit cost. A firm with a fixed order quantity of Q units and an
annual demand of D units will have
/
D Q orders per year and a total annual ordering cost of ( / )D Q S . The
average
cycle inventory
14
is / 2Q units and the annual
carrying cost
is ( / 2)Q ic . Therefore, the total
incremental annual cost is ( / ) ( / 2)TIC D Q S Q ic .
Taking the first derivative of the total incremental cost function and setting it to zero yields
2
/2 0
dTIC
DQ S ic
dQ
, which means that
2
2 2DS DS
Q EOQ
ic ic
. The second derivative of the TIC
is
3
2DQ S
, which is greater than zero for all 0Q . This proves that the Economic Order Quantity
2 / ( )
E
OQ DS ic
is the order quantity that has the global minimum total increment cost. Note that the
optimal solution (the EOQ) will always be where the annual ordering and annual carrying costs are equal.
The graph below shows that the annual carrying cost increases with Q and the annual ordering cost decreases
with Q. The optimal Q (the EOQ) is where the annual carrying cost and ordering cost are equal. In this example,
the parameters are demand D = 1200 units, ordering cost S = $54, carrying charge i = 12%, and unit cost c = $50.
The EOQ is 147 units and total annual carrying cost and total annual ordering cost are both $440.91, which
means that the total incremental cost is $881.81.
The EOQ model is
considered to be of limited
practical value for three
reasons. First, it is very
difficult to estimate the four
parameters in the model. As a
joke, the EOQ can be written
as
2 ??/ (??)EOQ
. Second,
even with perfect estimates of
the four parameters, the total
incremental cost function is
usually flat near the optimal
solution, which means that the
total incremental cost is not
sensitive to errors in the EOQ.
Third, managerial intuition is
usually good at finding the
EOQ without the equation. It
is fairly obvious to most
managers that high-volume,
expensive items should be
ordered more often than low-volume inexpensive items.
14
Cycle stock is also called the lotsize inventory. This is inventory in the “saw-toothed” graph that goes up when an order is
received and then goes down over time as units are drawn out of inventory. The lotsize inventory does not include the safety
stock, which is the inventory below the “saw-toothed” graph.
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Economic Value Added (EVA) − economy of scope
Page 117 The Encyclopedia of Operations Management
On the positive side, the EOQ model has several benefits. First, it helps people get a better understanding of
lotsizing issues and can help students and managers refine their thinking about the managerial economics of the
lotsizing problem. Second, in some cases, the trade-offs can have significant economic impact, especially when
accumulated over many items. Third, the EOQ model is the foundation for several other models, such as the
quantity discount model and the Economic Lot Scheduling Problem (ELSP).
See ABC classification, aggregate inventory management, carrying charge, carrying cost, cycle stock,
Economic Lot Scheduling Problem (ELSP), fixed order quantity, instantaneous replenishment, inventory
management, lotsize, lotsizing methods, marginal cost, Period Order Quantity (POQ), quantity discount, safety
stock, time-varying demand lotsizing problem.
Economic Value Added (EVA) – A financial performance metric for the true economic profit of an enterprise
from the shareholders’ point of view; closely related to economic profit.
EVA is the net operating profit minus an appropriate charge for the opportunity cost of all capital invested in
an enterprise. As such, EVA is an estimate of true “economic” profit, or the amount by which earnings exceed or
fall short of the required minimum rate of return that shareholders and lenders could get by investing in other
securities of comparable risk. The capital charge is the most distinctive and important aspect of EVA. Economic
profit is similar to EVA, but is not adjusted in the same way as EVA.
Under conventional accounting, most companies appear profitable. As Drucker (1995) argues, “Until a
business returns a profit that is greater than its cost of capital, it operates at a loss. Never mind that it pays taxes
as if it had a genuine profit. The enterprise still returns less to the economy than it devours in resources … Until
then it does not create wealth; it destroys it.”
EVA corrects this error by explicitly recognizing that when managers employ capital, they must pay for it,
just as if it were a wage. By taking all capital costs into account, including the cost of equity, EVA shows the
dollar amount of wealth a business has created or destroyed in each reporting period. In other words, EVA is
profit the way shareholders define it. If the shareholders expect, say, a 10% return on their investment, they
“make money” only to the extent that their share of after-tax operating profits exceeds 10% of equity capital.
Stern Stewart & Company owns a registered trademark for the name EVA for a brand of software and
financial consulting/training services. Their proprietary component makes adjustments related to amortization of
goodwill, capitalization of brand advertising to convert economic profit to into EVA.
See financial performance metrics, goodwill.
economics – The social science that studies how people and groups (families, businesses, organizations,
governments, and societies) choose to produce, distribute, consume, and allocate limited goods and services.
Economics deals primarily with supply and demand of scarce goods and services and how people and
societies assign prices to these goods and services to allocate them in some rational way.
The word “economics” is from the Greek for house (οίκος = oikos) and custom or law (νόμος = nomos); in
other words, economics is about the “rules of the house(hold).” (This definition from the Greek is adapted from
http://en.wikipedia.org/wiki/Economics, February 26, 2008).
See demand, double marginalization, economy of scale, economy of scope, elasticity, opportunity cost,
Pareto optimality, production function, sunk cost.
economy of scale – An economics principle that refers to situations where the cost per unit goes down as the
production volume increases; also called economies of scale.
Stated in more precise terms from the field of economics, economies of scale is the decrease in the marginal
cost of production as a firm’s scale of operations increases. Economies of scale can be accomplished because, as
production increases, the cost of producing each additional unit falls. The increase in efficiency often comes by
means of allocating the fixed costs over a larger number of units.
See big box store, commonality, core competence, cross-docking, diseconomy of scale, economics, economy
of scope, marginal cost, mergers and acquisitions (M&A), network effect.
economy of scope – A concept from economics that states that the cost per unit declines as the variety of products
increases.
In other words, economies of scope arise from synergies in the production of similar goods. A firm with
economics of scope can reduce its cost per unit by having a wide variety of products that share resources. Scope
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ECR – Efficient Consumer Response (ECR)
The Encyclopedia of Operations Management Page 118
economies exist whenever the same investment can support multiple profitable activities less expensively in
combination than separately.
Economies of scope can arise from the ability to eliminate costs by operating two or more businesses under
the same corporate umbrella. These economies exist when it is less costly for two or more businesses to operate
under centralized management than to function independently. Cost savings opportunities can stem from
interrelationships anywhere along a value chain.
See commonality, economics, economy of scale, mass customization.
ECR – See Efficient Consumer Response (ECR).
EDI – See Electronic Data Interchange (EDI).
effective capacity – See capacity.
effectiveness – Capability to produce a desired result, without respect to efficiency.
For example, the maintenance engineers in a milk plant found that a particular disinfectant was very effective
in killing bacteria in a vat that was used to produce cottage cheese. However, if the disinfectant was very
expensive and required significant time to apply, the firm might be able to find another more efficient approach
that was equally effective. In summary, effectiveness is about getting the right job done and efficiency is about
getting the job done using the minimum resources.
See efficiency, Overall Equipment Effectiveness (OEE).
effectivity date – The calendar date that an engineering change order for the bill of material (BOM) will come into
effect; sometimes called the effective date.
Nearly ERP systems include software for managing the BOM. In addition to storing the current product
structure, these systems are usually also able to store future product structures that will be implemented at some
future date (the effectivity date). When the effectivity date is reached, the second structure comes into effect.
The effectivity date may be determined by the effectivity quantity. With an effectivity quantity, the
engineering change comes into effect when the current inventory has fallen to zero or to a specified quantity.
However, one problem with this approach is that the inventory position usually does not fall to zero
instantaneously. When this is the case, the replenishment system may generate a new purchase order for the old
item. A second problem is that the small quantity of remnant stock that remains may be uneconomical to use,
leading to its scrap.
See bill of material (BOM), Engineering Change Order (ECO), Materials Requirements Planning (MRP).
effectivity quantity – See effectivity date.
efficiency – (1) Industrial engineering: The ratio of the standard processing time to the average actual processing
time; a process that can perform at a very low cost compared to some standard. (2) LEI’s Lean Lexicon
(Marchwinski & Shook 2006): Meeting exact customer requirements with the minimum amount of resources.
(3) Economics: The amount of resource products per unit of resource consumed. (4) Finance: An efficient
market is one that quickly and accurately incorporates information into prices.
The industrial engineering definition is the most widely accepted definition in the operations field.
Efficiency is calculated as the ratio (earned hours)/(actual hours) during a period. For example, a workcenter has
a standard time of one hour per unit. It worked eight actual hours today and earned ten hours (i.e., it produced
then units). Therefore, the efficiency of this workcenter is (earned hours)/(actual hours) = 10/8 = 125%. Earned
hours is similar to the practice of earned value management in project management.
The above economics definition is indistinquishable from the definition of productivity.
See 8 wastes, earned hours, effectiveness, operations performance metrics, Overall Equipment Effectiveness
(OEE), productivity, standard time, utilization.
Efficient Consumer Response (ECR) – A consumer goods initiative aimed at reducing inefficient practices and
waste in the supply chain.
Efficient Consumer Response (ECR) is an application of lean thinking to retail distribution, primarily in fast
moving consumer goods supply chains. ECR is defined by the Joint Industry Project for Efficient Consumer
Response (1994) as follows:
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eight wastes − Electronic Product Code (EPC)
Page 119 The Encyclopedia of Operations Management
A strategy in which the grocery retailer, distributor, and supplier trading partners work closely together to
eliminate excess costs from the grocery supply chain. ECR focuses particularly on four major opportunities to
improve efficiency:
1. Optimizing store assortments and space allocations to increase category sales per square foot and inventory
turnover.
2. Streamlining the distribution of goods from the point of manufacture to the retail shelf.
3. Reducing the cost of trade and consumer promotion.
4. Reducing the cost of developing and introducing new products.
See Collaborative Planning Forecasting and Replenishment (CPFR), continuous replenishment planning,
Fast Moving Consumer Goods (FMCG), lean thinking, Quick Response Manufacturing.
eight wastes – See 8 wastes.
eighty-twenty rule – See Pareto’s Law.
e-kanban – See faxban.
elasticity – An economics term used to describe the sensitivity of the demand to a change in price.
For example, Target is a major discount retailer in North America. When the inventory analysts at Target
want to clear (dispose) end-of-season inventory, they want to know the elasticity (sensitivity) of the demand to a
reduced price. They use a linear model based on percentages that relates the percent increase in demand to a
percent decrease in price (e.g., a 5% decrease in price will result in a 10% increase in the average demand).
The three main approaches for modeling the price-elasticity of demand include the linear model, the power
model, and the exponential model. The linear model is ( )
D
p p
, where ( )
D
p is the demand at price p
and
and
are the parameters of the model to be estimated from historical data. The power model is
( )D p p
. The exponential model is
( )
p
D p e
. The
parameter is the elasticity parameter for all
three models. All three models show that the demand decreases as the price increases. The linear model is the
easiest to use, but the power and exponential models generally make more sense. For the power model, the
demand is infinite when price is zero; for the exponential model, the demand is
when the price is zero.
Therefore, the exponential model makes the most sense for most operations/inventory/pricing models.
See booking curve, demand, economics, forecasting.
Electronic Data Interchange (EDI) – A system and related set of standards that firms can use to communicate
routine business transactions between computers without human intervention.
EDI transactions can include information for inquiries, planning, purchasing, acknowledgments, pricing,
order status, scheduling, test results, shipping and receiving, invoices, payments, and financial reporting. The
simplest form of EDI is to send purchase orders to suppliers. More advanced forms of EDI include sending
invoices, electronic payments, and planned orders (requirements). The advantages of EDI include:
• Reduced transaction cost – Electronic transactions are cheaper than manual/paper ones.
• Reduced transaction time – Electronic ordering is nearly simultaneous, versus days or weeks for a
manual/paper transaction sent via mail.
• Improved forecast accuracy – Forward visibility of the customer’s requirements can dramatically improve
forecast accuracy. For many firms, this is the most important benefit.
• Improved data quality – Sending information electronically can improve quality because it eliminates almost
all the human data entry from the process.
With the rapid growth of e-commerce, many expect that the phrase “EDI” will soon die. E-commerce will,
of course, serve the same purposes as EDI and will have to include the same functionality.
See Advanced Shipping Notification (ASN), Enterprise Resources Planning (ERP), firm order, forward
visibility, invoice, Over/Short/Damaged Report, purchase order (PO), purchasing, Transportation Management
System (TMS), XML (eXtensible Markup Language).
Electronic Product Code (EPC) – A number used to identify products using RFI technology in a supply chain.
Like the Universal Product Code (UPC), the EPC is used to identify item numbers (SKUs) for products
moving through a supply chain. Unlike the UPC, the EPC uses radio frequency (RFID) technology rather than
Optical Character Recognition (OCR) technology and provides a serial number that can be referenced in a
database. The serial number enables the specific item to be tracked as it moves through the supply chain.
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Electronics Manufacturing Services (EMS) – engineer to order (ETO)
The Encyclopedia of Operations Management Page 120
The EPC number can be from 64 to 256 bits and contains at least the (1) EPC version, (2) company
identification number assigned by EPCglobal, (3) product number (object class), and (4) unique serial number.
A 96-bit EPC is capable of differentiating 68 billion items for each of 16 million products within each of 268
million companies. For example, an EPC can differentiate between the first and the thousandth can in a shipment
of cans of soup.
See barcode, Optical Character Recognition (OCR), part number, Radio Frequency Identification (RFID),
traceability, Universal Product Code (UPC).
Electronics Manufacturing Services (EMS) – See contract manufacturer.
emergency maintenance – See maintenance.
empathy – A service quality term that refers to the amount of caring and individualized attention shown to
customers by the service firm.
According to Parasuraman, Zeithaml, and Berry (1990), empathy involves the provision of caring and
individualized attention to customers that includes access, communication, and understanding the customer.
See service quality, SERVQUAL.
employee turnover – The average percentage of employees who exit a firm per year.
For example, the turnover for hotel staff is very high, often on the order of 100%. This means that the
number of employees exiting a firm in a year (voluntarily or involuntarily) equals the number employed.
Employee turnover can be greater than 100% (e.g., 200% employee turnover means an average tenure of six
months). Employee turnover is a surrogate measure of employee satisfaction.
See inventory turnover, turnover.
empowerment – The practice of granting decision rights to subordinates.
Empowerment often helps people build confidence, develop self-reliance, and derive greater job satisfaction.
In a service context, empowerment often results in better customer service because the workers closest to the
customer can make better decisions on the customer’s behalf. Empowerment can also increase the absorptive
capacity of an organization.
See absorptive capacity, customer service, High Performance Work Systems (HPWS), human resources,
jidoka, job design, job enlargement, service quality.
EMS (Electronics Manufacturing Services) – See contract manufacturer.
energy audit – The process of inspecting and analyzing the energy use in a facility with the intention of reducing
energy consumption, cost, and pollution while increasing safety and comfort.
An energy audit might consider issues such as repairing or replacing heating and cooling systems, insulation
and weatherization, location of heating/cooling losses, safety, and comfort. These audits are often conducted by
qualified inspectors who use benchmark data to support engineering analyses. Opportunities are often found
with new lighting, better control systems, more efficient systems, and better use of solar and wind energy.
See carbon footprint, green manufacturing, sustainability.
engineer to order (ETO) – A customer interface strategy with engineering done in response to a customer order;
sometimes called design to order.
Examples of engineer to order (ETO) products include custom-built homes, the space shuttle, plastic molds,
and specialized capital equipment. With an ETO customer interface, engineering work usually needs to be done
before any specialized components can be purchased or fabrication can begin. This means that ETO customer
leadtime is the sum of the engineering, procurement, fabrication, assembly, packing, and shipping time.
Although some assemblies and components may be standard items stored in inventory, some items may be
designed specifically to the customer’s order. Standard items do not need to be stocked unless their procurement
leadtime is longer than the leadtime for the engineering effort. Purchase orders may be pegged (assigned) to
specific customer orders. The ERP system may treat the engineering organization as a workcenter in the factory.
Actual costing is used because many items are purchased or manufactured just for that one customer order.
In an ETO system, the main challenges are often in (1) making reasonable promise dates and keeping them
up to date as the situation changes (ask any owners of a custom-built home if their home was completed on time),
(2) managing Engineering Change Orders (ECOs) to support design changes, and (3) developing modular
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Engineering Change Order (ECO) − entitlement
Page 121 The Encyclopedia of Operations Management
designs, where many of the components are standard with standard interfaces with other components that can be
“mixed and matched” to meet a wide variety of customer requirements and reduce engineering time and effort.
See commonality, configurator, Engineering Change Order (ECO), make to order (MTO), mass
customization, respond to order (RTO).
Engineering Change Order (ECO) – A request for a change in a product design; also called an engineering
change request.
The Engineering Change Order (ECO) should include the reason for the change, level of urgency, affected
items and processes, and an evaluation of the costs and benefits. The engineering change review board, with
representatives from engineering, R&D, manufacturing, and procurement, evaluates the cost, benefits, and timing
before an ECO is implemented. Improving the ECO process can be a good opportunity for improvement in
many firms. ECOs tend to be complicated and error-prone. Most ERP systems allow the system to implement
an ECO when the inventory position of the older component goes to zero.
See bill of material (BOM), effectivity date, engineer to order (ETO), Integrated Product Development
(IPD), Materials Requirements Planning (MRP), version control.
engineering change review board – See Engineering Change Order (ECO).
Enterprise Resources Planning (ERP) – Integrated applications software that corporations use to run their
businesses.
ERP systems typically handle accounts payable, accounts receivable, general ledger, payroll, Materials
Requirements Planning (MRP), purchasing, sales, human resources, and many other interrelated systems. One of
the key concepts for an ERP system is that the firm stores data in one and only one location. In other words, the
organization has only a single database that all departments share. SAP and Oracle are the two main ERP
systems vendors currently on the market.
ERP systems grew out of Materials Requirements Planning (MRP) systems that were developed in the 1970s
and 1980s. The Materials Requirements Planning module in an ERP system supports manufacturing
organizations by the timely release of production and purchase orders using the production plan for finished
goods to determine the materials plan for the components and materials required to make the product. The MRP
module is driven by the master production schedule (MPS), which defines the requirements for the end items.
The three key inputs to the MRP module are (1) the master production schedule, (2) inventory status records, and
(3) product structure records.
See Advanced Planning and Scheduling (APS), bill of material (BOM), Business Requirements Planning
(BRP), Distribution Requirements Planning (DRP), Electronic Data Interchange (EDI), human resources,
implementation, legacy system, Materials Requirements Planning (MRP), SAP, turnkey.
entitlement – A lean sigma term used as a measurement of the best possible performance of a process, usually
without significant capital investment.
Entitlement is an important process improvement concept that is particularly useful in project selection. It is
usually defined as the best performance possible for a process without significant capital investment. However,
some firms define it as the performance of the perfect process. As the term implies, the organization is “entitled”
to this level of performance based on the investments already made.
Knowing the entitlement for a process defines the size of opportunity for improvement. If entitlement is 500
units per day and the baseline performance is 250 units per day, the process has significant room for
improvement. If higher production rates are needed, a search for a totally new process may be in order (i.e.,
reengineering or DFSS).
Entitlement should be determined for all key process performance measures (yield, cost of poor quality,
capacity, downtime, waste, etc.). Entitlement may be predicted by engineering and scientific models, nameplate
capacity provided by the equipment manufacturer, or simply the best prolonged performance observed to date.
Entitlement can also be predicted from empirical relationships. In one instance, it was observed that a
process operating at a cost of $0.36/unit had at one time operated at $0.16/unit (correcting for inflation). This
suggests that the process entitlement (as determined by best prolonged performance) should be $0.16/unit. On
further investigation, it was observed that there was a linear relationship between defects and cost/unit of the
form: Cost = $0.12 + 3(defects)/1,000,000. Therefore, if defects could be reduced to very low levels, the true
process entitlement may be as low as $0.12/unit.
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EOQ
–
Erlang distribution
The Encyclopedia of Operations Management Page 122
The following steps should be followed when using entitlement for project selection:
1.
Look at the gap between baseline performance (current state) and entitlement (desired state).
2.
Identify a project that will close the gap and can be completed in less than four to six months.
3.
Assess the bottomline impact of the project and compare it to other potential projects.
The gap between the baseline and entitlement is rarely closed in the course of a single project. It is common
for several projects to be required.
Keep in mind that process entitlement can, and often does, change as more is learned about the process.
After a few lean sigma projects, processes are sometimes performing beyond the initial entitlement level.
See benchmarking, lean sigma.
EOQ – See Economic Order Quantity (EOQ).
EPC – See Electronic Product Code (EPC).
e-procurement – A Web-based information system that improves corporate purchasing operations by handling the
specification, authorization, competitive bidding, and acquisition of products and services through catalogs,
auctions, requests for proposals, and requests for quotes.
See acquisition, Dutch auction, e-auction, e-business, purchasing, reverse auction.
ergonomics – The scientific discipline concerned with the understanding of interactions among humans and other
elements of a system and the profession that applies theory, principles, data, and methods to design to optimize
human well-being and overall system performance; ergonomics is also called human factors.
Source: This is the approved definition of the International Ergonomics Association, www.iea.cc,
representing 19,000 ergonomists worldwide, and was provided by Jan Dul, Professor of Ergonomics
Management, Department of Management of Technology and Innovation, Rotterdam School of Management,
Erasmus School of Business, Erasmus University, Rotterdam.
See error proofing, human resources, job design, process design.
Erlang C formula – See queuing theory.
Erlang distribution – A continuous probability distribution useful for modeling task times.
The Erlang is the distribution of the sum of k independent identically distributed random variables each
having an exponential distribution with mean β.
Parameters:
The shape parameter (k), which must be an integer, and the scale parameter (β).
Density and distribution functions:
The Erlang density and distribution functions for x > 0 are:
1
/
( )
( 1)!
k
k
x
x
f x
k
e
and
1
/
0
( )
( ) 1
!
j
k
x
j
x
F x
j
e
Statistics:
Range [0, ∞), mean kβ, variance kβ
2
, and mode (k−1)β.
Graph:
The graph below is the Erlang density function with parameters β =1 and k = 1, 2, and 3.
Parameter estimation:
Given the sample mean (
x
) and
sample standard deviation (s), the
k parameter can be estimated as
2 2 2
/ 1/k x s c
, where
/c s x
is the sample
coefficient of variation.
Excel:
In Excel, the density
and distribution functions are
GAMMADIST(x, k, β, FALSE)
and GAMMADIST(x, k, β,
TRUE).
Excel simulation:
In an
Excel simulation, Erlang random
variates can be generated with
the inverse transformation
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ERP
−
error proofing
Page 123 The Encyclopedia of Operations Management
method using x = GAMMAINV( 1-RAND(), k, β, TRUE). Alternatively, Erlang random variates can be
generated by taking advantage of the fact that the Erlang is the sum of k independent exponential variates, i.e.,
1
ln( )
k
j
j
x r
, where r
j
is a random number.
Relationships to other distributions:
The exponential is a special case of the Erlang with k = 1. The
Erlang distribution is a special case of the gamma distribution with parameters k and β, where k is an integer.
History:
The Erlang distribution was developed by Danish mathematician A. K. Erlang (1878-1929) to
examine the waiting times for telephone calls.
See coefficient of variation, exponential distribution, gamma distribution, inverse transform method,
probability density function, probability distribution, random number.
ERP – See Enterprise Resources Planning (ERP).
error function – A mathematical function that is useful for dealing with the cumulative distribution function for the
normal and lognormal distributions; also called the Gauss error function.
The error function is defined as
2
0
2
( )
z
t
t
erf z e dt
or
1
2
0
0 1
2
( , )
z
t
t z
erf z z e dt
and the complementary
error function is defined as ( ) 1 ( )erfc x erf x . The normal distribution CDF is then
2 2
( ) /(2 )
2 2
1 1
( ) ( ) 1 erf
2
2 2
t x
t
t
x
F x P X x e dt
and the lognormal distribution CDF is
2
2
(ln )
2
1 1 ln
( ) 1 erf
2
2 2
t
t x
t
x
F x e dt
t
. Excel offers the functions ERF(z), ERF(z0,z1), and
ERFC(z). The error function has no closed form, but numerical methods are available with as much precision as
allowed by the computer. Winitzki (2003) developed useful closed-form approximations for both erf(x) and its
inverse. The error function can also be computed from the gamma function.
See gamma function, lognormal distribution, normal distribution.
error proofing – The process of identifying likely causes of a failure and preventing the failure or at least
mitigating the impact of the failure; also known as mistake proofing, fool proofing, idiot proofing, and fail
safing, making fault tolerant and robust; the Japanese phrase “poka yoke” (
ポカヨケ
) means to avoid mistakes.
Error proofing principles can improve both product and process design in all types of organizations. Ideally,
error proofing devices are (1) simple and cheap, (2) deployed close to where the work is being done, and (3)
result in what Shingo calls “100%” inspection and zero errors.
Product design
– An error-proof product design can reduce errors to improve quality, efficiency, and safety
in the manufacturing process and in the use of the product by the customer. For example, the gas fueling system
in a typical automobile integrates different error proofing devices (see the photo below). The plastic tether keeps
the gas cap from getting lost, the gas cap has a ratchet to signal proper tightness
and prevent over-tightening, the filler hole is too small for the leaded-fuel nozzle,
the gas cap has warning messages on it, and the fuel pump will shut off when the
tank is full
15
.
Process design
– An error-proof process design prevents errors in the process
that produces goods or services. Error proofing can be applied to all types of
processes to improve safety, which is a major issue in nearly all industries in all
countries. In 2006, in the U.S., OSHA recorded 4,085,400 non-fatal workplace
injuries and 5,703 fatal workplace injuries (source: www.bls.gov/iif/home.htm#News, December 7, 2007).
15
This example was motivated by a similar one from Professor John Grout. Professor Grout has many other interesting
examples of error proofing on his website at http://facultyweb.berry.edu/jgrout/everyday.html (April 17, 2011).
Source: Professor Arthur V. Hill
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ESI
–
EurOMA
The Encyclopedia of Operations Management Page 124
Application of error proofing principles is the key to improving these sad statistics. Error proofing can also be
applied to assembly operations to improve efficiency.
Error proofing methods can also be classified as either
prevention
or
detection/warning
. Whereas,
prevention makes it impossible (or nearly impossible) for the error to occur, detection/warning only signals that
an error is about to occur or has already occurred. For example, a microwave will not work if the door is open (a
prevention device) and many cars will sound an alarm if the key is left in the ignition (a detection/warning
device). Prevention methods can be further broken into three types:
1. Control
– An action that self-corrects the problem, such as an automatic spell-checker that automatically
corrects a misspelled word.
2. Shutdown
– A device that shuts down the process when the error condition occurs, such as a home iron that
shuts off after ten minutes of non-use.
3.
Human factors
– Use of colors, shapes, symbols, sizes, sounds, and checklists to simplify a
process to make it less error-prone for human operators. An example is a
shadow board
for
a tool, which is an outline of the tool painted on a pegboard to signal to the worker where the
tool belongs. Another example is the use of symbols for hazardous materials. For example,
the symbol on the right is for radioactive materials.
Detection/warning methods
detect a problem and warn the operator when an error is about to occur or has
already occurred. Unlike prevention methods, detection/warning methods do not control or shut down the
system. A car’s oil light is a good example. Prevention is almost always better than detection/warning because
detection/warning relies on human intervention and warnings can be ignored, whereas prevention is automatic
without any human intervention.
Failure Mode and Effects Analysis (FMEA)
is a more formal approach to error proofing and risk
management. FMEA is a process used to identify possible causes of failures (failure modes) and score them,
helping establish which failure modes should be addressed first. Business continuity planning applies error
proofing concepts at a more strategic level.
See 5 Whys, adverse event, andon light, autonomation, Business Continuity Management (BCM), Business
Process Re-engineering (BPR), checklist, ergonomics, fail-safe, Failure Mode and Effects Analysis (FMEA),
fault tree analysis, Hazard Analysis & Critical Point Control (HACCP), inspection, jidoka, muda, multiple-
machine handling, Murphy’s Law, Occupational Safety and Health Administration (OSHA), Pareto’s Law,
prevention, process, process design, process improvement program, quality management, risk mitigation, robust,
Root Cause Analysis (RCA), safety, sentinel event, service recovery, shadow board, stamping, work
simplification.
ESI – See Early Supplier Involvement (ESI).
ethnographic research – An approach for gathering qualitative cultural and behavioral information about a group
of people.
Ethnography is based almost entirely on fieldwork where the
ethnographer
goes to the people who are the
subjects of the study. Ethnography studies what people actually say and do, which avoids many of the pitfalls
that come from relying on self-reported, focus group, and survey data. Ethnographers sometimes live among the
people for a year or more, learning the local language and participating in everyday life while striving to
maintain objective detachment. Ethnographers usually cultivate close relationships with
informants
who can
provide specific information on aspects of cultural life. Although detailed written notes are the mainstay of
fieldwork, ethnographers may also use tape recorders, cameras, or video recorders. Ethnography is closely
related to anthropology.
Businesses have found ethnographic research helpful in understanding how people live, use products and
services, or need potential products or services. Ethnographic research methods provide a systematic and holistic
approach so the information is valued by marketing researchers and product and service developers.
See voice of the customer (VOC).
ETO – See engineer to order.
Euclidean distance – See Minkowski distance.
EurOMA – See European Operations Management Association.
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European Operations Management Association (EurOMA) − experience engineering
Page 125 The Encyclopedia of Operations Management
European Operations Management Association (EurOMA) – Europe’s leading professional society for
operations management scholars and practitioners.
EurOMA was formed in the UK in 1984 and rapidly grew into Europe’s leading professional association for
those involved in operations management. The Europe-wide European Operations Management Association was
founded in October 1993. EurOMA is an international network of academics and managers from around the
world interested in developing operations management. It is a European-based network, with rapidly developing
international links, where people can get together to communicate experience and ideas. It is also a network that
bridges the gap between research and practice. EurOMA publishes the International Journal of Operations &
Production Management (IJOPM). The website for EurOMA is www.euroma-online.org.
See operations management (OM).
EVA – See Economic Value Added (EVA).
Everyday Low Pricing (EDLP) – A pricing strategy and practice designed to create a more level (more stable)
demand by keeping prices at a constant low price rather than using sporadic temporary pricing promotions;
closely related to value pricing.
EDLP often promises customers the lowest available price without coupons, pricing promotions, or
comparison shopping. This practice tends to reduce the seller’s administrative cost to change prices and process
coupons, reduce safety stock inventory (due to lower variability of demand), and increase customer loyalty.
See bullwhip effect, forward buy, safety stock.
executive sponsor – See champion.
expatriate – (1) Noun: A person who has taken residence in another country; often shortened to expat. (2) Verb:
To force out or move out a country.
The word “expatriate” comes from the Latin expatriātus (from ex “out of”) and patriā (“country, fatherland”).
An expatriate is any person living in a country where he or she is not a citizen. The term is often used to describe
professionals sent abroad by their companies. In contrast, a manual laborer who has moved to another country to
earn money is called an “immigrant” or “migrant” worker.
See offshoring, repatriate.
expedite – See expediting.
expediting – The process of assigning a higher priority to a job (order or task) so it gets started and done sooner; de-
expediting is the process of assigning a lower priority to a job.
When priorities for jobs change, some jobs should be given higher priority. However, when all jobs are
given a higher priority, expediting has no value. Schedulers should realize that expediting one job will de-
expedite all other jobs. For example, when an ambulance comes down a highway with its lights and sirens on, all
other vehicles must move to the side. Expediting the ambulance, therefore, de-expedites all other vehicles on the
road at that time.
See buyer/planner, dispatching rules, job shop scheduling.
experience curve – See learning curve.
experience economy – See experience engineering.
experience engineering – The process of understanding and improving customer sensory and emotional
interaction and reaction to a service or a product.
Two quotes highlight the main point of experience engineering:
• “Consumer preference and motivation are far less influenced by the functional attributes of products and
services than the subconscious sensory and emotional elements derived by the total experience.” – Professor
Gerald Zaltman, Harvard University, Procter & Gamble’s Future Forces Conference, Cincinnati, Ohio 1997
(Berry, Carbone, & Haeckel 2002).
• “We need to look at our business as more than simply the building and selling of personal computers. Our
business is the delivery of information and lifelike interactive experiences.” – Andrew Grove, Chairman,
Intel, 1996 COMDEX computer show (Pine & Gilmore 1998).