Measuring Delivery Accuracy in Supply Chain
A Conceptual Analysis
Petri Suomala, Jari Paranko
Tampere University of Technology
Tampere, Finland
ABSTRACT
Recent years have shown a growing interest towards non-financial and balanced
performance measurement systems. Time, quality and price – these are the factors that
create the competitive advantage and should also be measured. Delivery accuracy
(DA) combines the first two of these. Both time and quality related aspects are
considered in the measures of DA.
Constructing a DA measure that is to be used to improve performance requires a
profound understanding of the factors and their interdependencies influencing
delivery time as well as the factors determining delivery time objectives. A
conceptual analysis considering DA and delivery time is presented in this paper. The
analysis forms the basis for the model used in delivery accuracy measurement.
Delivery accuracy can be determined as the relationship between the deliveries
satisfying customer requirements and all deliveries during the same period of time.
Customer requirements should be fulfilled both in terms of quality and delivery time.
The model presented provides a framework that supports delivery accuracy
measurement in manufacturing industry. The model features performance monitoring
on the team or activity level enabling DA development in the whole internal supply
chain. The model introduced consists of three parts: the main elements in DA, a
concept map associated with the concept of DA; in addition, list of the declaring and
measurable factors of DA is included in order to enhance the possibilities of DA
development at company level.
Key Words: Delivery accuracy, measurement
Introduction
During the recent years, in addition to the traditional financial measures of success,
practical and non-financial 1 performance measures and measurement systems have
gained publicity both in the academic world and the business world. (See e.g. Kaplan
and Norton 1992; Kaplan and Norton 1996 or Lynch and Cross 1995) The growing
interest in non-financial performance measurement can partly be attributed to the
current realisation that financial measures alone cannot provide sufficient information
for running an organisation. (See Johnson and Kaplan 1987 or Uusi-Rauva 1986)
Companies aiming to be profitable in the long run have to track not only financial
performance but also other variables, such as customer satisfaction, quality,
innovation, flexibility, the efficiency and effectiveness of processes, and the linkages
between departments or units and the measurements used for each (Brinker 1997).
Delivery accuracy (DA) is one of the important operational performance measures. In
general, time, quality and price are considered to be factors that create competitive
advantage for a company. Delivery accuracy combines the non-financial elements,
namely time and quality.
The present state of the performance measurement in the Finnish metal industry was
assessed in 1992. The first part of the study concentrated on the future development
areas of the companies. The researchers found that the respondents considered
customer satisfaction to be the primary development area in the future. The second
important area was to improve production lead-times. The second part was intended
to identify the performance factors that are the most important for the success of the
company. Delivery performance was found to be the first and production lead-time
was the sixth most important factor. (Andersin, Karjalainen et al. 1994, pp. 22-23)
DA is regarded as the company's ability to fulfill the requirements of customer order
in terms of delivery time. Furthermore, although quality is not explicitly mentioned in
the definition above, it is implicit in the DA measure. This is because a delivery
cannot be accurate or complete if the following conditions are not met (Lehtonen and
Marttila 1996):
• The quantity of the products in the delivery is consistent with the order
• The attributes of the products are consistent with the order
• The delivery is complete with all the features and accessories agreed upon in
the order
• The implementation of the delivered goods is problem-free
Taking into account the longer time scale, delivery accuracy can be defined as the
relationship between the deliveries satisfying customer requirements and all deliveries
during the same period of time. Customer requirements should be fulfilled both in
terms of delivery time and quality as clarified above.
1
Non-financial and operational performance measures are used in this study as synonyms. An
operational measure is a numerical or graphical representation of a non-financial attribute of a process.
For instance: time, temperature, speed, quality and delay are examples of measures associated with any
process (Schneiderman 1996).
1
Constructing a DA measure intended to improve supply performance requires a
profound understanding of the factors and their interdependencies influencing
delivery time as well as the factors determining delivery time objectives. A
conceptual analysis of DA and delivery time forms the basis for the model used in
delivery accuracy measurement.
In an industrial environment where low inventories and Just-In-Time operations are of
primary interest, the significance of short and accurate delivery time is increasing.
Delays in deliveries may immediately cause halts in the production process. In a
supply chain a delivery delay affects not only to the individual buyer or supplier but
also the whole chain. Slowness and delays accumulate across the chain and corrective
actions require efforts from all the supply chain members. In other words, a single
supplier may cause problems to the whole chain but no single buyer or supplier can
remove or compensate the problem alone.
When assessing the external efficiency of the outbound logistics materials flow in
relation to the customers, it is of crucial importance to monitor the same things that
the customers do. These may be factors relating to deliveries, quality and reliability,
and packing errors. (Lehtola 1997, p. 108)
The first objective of this paper is to construct a conceptual model for analysing
delivery lead-time and delivery accuracy in a supply chain. The second objective is to
discuss the implications of such a model for delivery accuracy measurement and
delivery accuracy improvement.
Delivery accuracy
Lead-time is the time measured in days that is needed to complete a certain phase of
work or a series of several phases. Production lead-time, for instance, consists of all
phases of work needed to manufacture the product. It includes not only the activities
adding value to the product but also the non-value-adding phases such as queuing
time. Delivery lead-time is the time period that starts from the customer order and
ends when the customer has received the products or the services ordered. Delivery
accuracy is the company's ability to fulfill the agreed delivery lead-time. In other
words, it is the company's ability to deliver the goods to the customer within the
acceptable time window. (Lehtonen and Marttila 1996)
The concept of delivery accuracy can be utilised both inside one company and
between two companies in a supply chain. In external delivery accuracy the focus is
on the deliveries to another company – to an external customer. On the other hand,
internal delivery accuracy considers the customer to be internal. Internal delivery
accuracy is measured between functions, teams or departments that are members of an
order delivery process of the company.
2
External DA
External delivery accuracy is an attribute that describes a certain area of the
company's performance when it is viewed as a black box. Figure 1 illustrates the
principle of external DA. External delivery accuracy indicates to what extent a
company can satisfy the delivery requirements of its external customer.
The Supply Chain
Company A
Company B
Company C
External del ivery accuracy
Figure 1. External delivery accuracy in a supply chain
Some enterprises have connected delivery accuracy closely to customer satisfaction. It
is seen as a means of improving customers' satisfaction and loyalty. However, care
should be taken that DA improvement and maintenance are also combined with the
other goals of a company. To prevent a situation of eroding goals2 delivery accuracy
should be improved hand in hand with shortening the lead-time between the order and
the delivery. Schneiderman has described the development process of metrics in a
middle-sized semiconductor manufacturer. To improve customer satisfaction the
company established a customer service commitment that consisted of three points:
(Schneiderman 1996, p. K3-2)
• To deliver all orders to all customers complete and when promised. In
addition, to minimise lateness whenever this fails.
• To meet customers' delivery requirements – always
• To offer shorter lead times if doing so would give the company a competitive
advantage by reducing total systems costs in the supply chain.
The commitment combines the core components of delivery accuracy improvement.
Firstly, both time and quality aspects are taken into account. Secondly, whenever the
customer requirements cannot be met exactly, delay or other failure is minimised.
Thirdly, the reference value for delivery accuracy – delivery lead-time – is improved
at the same time if this is consistent with market demand. Naturally, with a shorter
lead-time, a certain level of delivery accuracy is harder to maintain. Shorter lead-time
2
Eroding goals is a term, a system archetype, used by Senge in his book "The fifth discipline". (Senge
1990) The idea is that when focusing on a single measure one might end up by changing the reference
value behind the measure instead of changing and improving the actual condition, which has caused the
decline of the measure. The result is that a goal might be achieved but the achieved goal is no longer
the same one that was originally defined.
3
allows fewer problems and internal delays. In such a situation, steady process
performance is a strong enabling factor for delivery accuracy.
On the other hand long-lead times make managing the production difficult.
Production schedules, for example, can scarcely be frozen if production lead-time
exceeds 6 or 12 months. If this is the case, customers expect to be able to change
already scheduled orders or to place new orders with a much shorter response time.
(Harmon and Peterson 1990, p. 215)
Internal DA
Internal delivery accuracy perceives the company as a system rather than a black box.
It takes the internal supply chain under assessment and states that every employee or
team has at least one internal customer in addition to the external one. Delivery
accuracy thus also has an internal dimension. This is presented in
Figure 2.
From the management point of view, internal delivery accuracy lacks significance if
external DA is of no interest. In that sense, internal DA can be seen as a supporting
idea for the improvements in the external area. On the other hand, external delivery
accuracy cannot really be managed without likewise considering the internal
perspective.
The Supply Chain
Team a
Team b
Team c
Company B
Internal del ivery accuracy
Figure 2. Internal delivery accuracy in a supply chain
Regarding internal delivery accuracy the fundamental definitions of the concept do
not differ from those of delivery accuracy in general. Only the concept of internal
customer is introduced.
4
Measuring delivery accuracy
The big picture
Measuring delivery accuracy as such does not significantly generate additional value
either to the company or to the customer. Just like the other measures, delivery
accuracy justifies itself by increasing relevant knowledge that can be utilised in
managing the company's operations. In other words, measuring delivery accuracy
must somehow lead to improving performance. The ultimate target is not 100%
delivery accuracy, but delivery performance that is continuously improving as a
whole. A company is not an isolated system, indeed, it is always surrounded by some
kind of competitive environment. Delivery accuracy should be improved taking the
competitive situation into account. Measurement is a tool that can help in achieving
the improvement goal.
It is suggested that businesses today have to choose one of three propositions on
which to compete: product leadership, operational excellence, or customer intimacy.
The one chosen defines the company in the eyes of the customer. Choosing one
strategy does not, however, mean that the others can be sacrificed. Good industry
standard level should be achieved with them, too. (Hope and Hope 1997, pp. 48-49)
Objectives such as delivery accuracy are primarily categorised under operational
excellence.
Delivery date
requested by customer
Delivery date offered
by supplier
Actual delivery date
Best delivery date
offered by competitor
Time
Delivery accuracy
Delivery performance
related to competitive
situation
Figure 3. Delivery accuracy and competitive situation (adapted from Rahiala
1985)
Figure 3 shows some interpretations of the possible gaps between a company's
performance and customers' expectations or market situation. Delivery accuracy (or
5
the lack of it) is the gap between offered and actual delivery date. Delivery
performance can be assessed by examining the gaps between offered and both
requested and best possible delivery dates. In order to improve the operational
excellence, the gaps should be reduced as far as possible.
Common measures
A typical measure for delivery accuracy is a percentage where the numerator is ontime or late deliveries and the denominator is all the deliveries during the same time
period. One figure is easy to use but it lacks some relevant information. For instance,
it would be beneficial likewise to use a measure that shows to what extent the delayed
deliveries have exceeded the requested delivery date.
Schneiderman introduced metrics for the order fulfillment process at a case company.
He included four perspectives that can also be assessed in the context of delivery
accuracy. The first perspective and the highest level measure associated with the order
fulfillment process is lateness – the degree to which order commitments are met. In
other words, what percentage of the time the shipment is made within an acceptable
window around the agreed delivery date. The second perspective was the degree to
which the commitments match the customer needs in the first place. Is the agreed
delivery date same as the date the customer requested and if not, what is the
difference between the customers' requests and company's ability to deliver? Thirdly,
metrics included aspects regarding severity. If an order was late or too early, the
question still remains how late or early that order would be. From the customer point
of view, one day's delay might cause significantly fewer problems that a one-week
delay. The last perspective associated with the metrics of order fulfillment process is
what is called responsiveness. What is the time between order entry and the
communication of delivery date to the customer? For instance, if a product contains a
substantial amount of purchased material, a decision-maker might be tempted to delay
making any commitment until all the materials have been received. This kind of
behaviour may reduce actual production lead-time but meanwhile lengthen the whole
delivery lead-time. (Schneiderman 1996, pp. K4-1 - K4-3)
Key issues to be solved
Many attributes can be set for a good measure, but it should reach satisfactory level at
least in validity, reliability and relevance (See e.g. Santori and Anderson 1987, pp.
141 -147; Lecklin 1997, p. 169; Andersin, Karjalainen et al. 1994, pp. 91-93; or
Vehmanen 1979). Constructing a measure that would be applicable in practical
solutions requires some basic definitions regarding, for example, timeliness of
measure, concept of complete lot or order, and readjusting delivery dates.
If the delivery accuracy measure is used for some other purpose than just collecting
historical data, the timeliness of the measure should be considered. DA measure
containing up-to-date information is useful for scheduling the operations and setting
priorities for different orders. Three time-related alternatives are possible regarding
6
the data collection for the measure: One could measure only those orders that are
already delivered, in which case the measure is purely retrospective. Secondly, one
might also include data related to orders that were supposed to be delivered by the day
data is collected for the measure. The third option is to include delivery accuracy
forecasts in the measure if there is relevant information available regarding the
present state of the orders and schedule of following work phases. In this case, DA
measure is a prospective tool that can be utilised for rescheduling or possible
adjustment related to resource allocation.
To be able to measure delivery accuracy one should define precisely what is meant by
accurate delivery. What is really delivered? Is it all the lines in the order or is it one
specific line? Accurate delivery may even be only one item of the order line. It is
essential to construct a measure that is consistent with the customer need. Some
customers could be satisfied with partial deliveries while others may require the
complete order to be delivered. In the former case, the measurement would be based
on the order lines. In the latter case, only one delivery date is defined and one missing
item is enough to cause non-accurate delivery.
One of the interesting definitions of the DA measure concerns the delivery date
adjustments that are made after the original delivery date is set. The need for
adjustments arises either from the customer or from the supplier and his
subcontractors. If the customer initiates the change, can the change be made to the DA
measure as well. In that case, the DA measure is used to assess the company's
performance in relation to the customer's up-to-date expectations. If, however, the
company refuses to make any changes to the delivery date in the DA measure, it is
probably using the DA measure to evaluate its performance in relation to its original
self-set goals.
If the products of the company are heterogeneous, calculating the delivery accuracy
separately for different product lines might be beneficial. Analogously, if each of the
products is a project in nature, an aggregate DA measure would be unlikely to
successfully utilised in performance management.
The DA model
The delivery accuracy model was developed in a case company where delivery
accuracy was seen as an essential objective, however, it was at the time at an
unsatisfactory level. Measurement of DA at company level (external DA) was
considered to be fairly easy, but the company lacked team-level measures that would
support and guide teams' efforts towards the overall goal. Thus, the objective for
developing a DA measure for cross-functional order-delivery -process was as follows:
"How to measure delivery accuracy in such way that company level delivery targets
are visible for all the teams in the supply chain." And further: "How to develop such
measures that would enable delivery performance improvements across the supply
chain."
7
Constructing the model
Model construction was begun by examining the processes in the company's supply
chain. A rough process analysis3 was conducted to determine the current state of the
supply process. The main tools for the analysis were interviews and monitoring
sessions that took place mainly in the shop floor. As such, analysing the concept of
delivery time and accuracy, which was the main part of the project and the basis for
any measures, can be described as a mental process. The final model introduced in
this paper was developed incrementally by several researchers during an eight-month
period. To ensure that the model would be consistent with the real production
environment it was developed in co-operation with the case company representatives.4
Concept map
The idea of the concept map is that by identifying all the essential factors influencing
delivery accuracy, a comprehensive set of measures can be defined to track both the
effects and causes of delivery accuracy fluctuations. The two main factors
determining DA in a supply chain are visualised in the following figure. The complete
concept map (with underlined measurable factors) is presented in Appendix 1.
DELIVERY LEAD-TIME
FLEXIBILITY
Goal
SYSTEMATIC Approach
- planned flexibility
Promised
delivery date
Actual
Actual
delivery date
DELIVERY ACCURACY
Figure 4. Main factors of delivery accuracy
3
Process analysis is a tool that traces resource consumption to activities or steps within a crossfunctional process (Euske, Frause et al. 1998, p. 99).
4
Detailed description of the research project is presented in the report "Designing performance
measurement system for industrial enterprise (In Finnish)." (Suomala 1999)
8
According to Figure 4 when delivery accuracy or delivery lead-time is being
measured, both the goal and the actual condition should be taken into consideration.
The goal is generally the promised delivery date that is communicated to the customer
as well. It is usually known before the goods in the order are started to manufacture.
The actual delivery date is the one that is realised. It is not exactly known before the
order is delivered to customer.
To reach a better understanding of processes regarding the goal setting and the
realisation of the actual delivery date both these factors were analysed profoundly in
the concept map. The aim was to find such factors that influence the delivery
accuracy and that could be measured. It was found that to be able to improve delivery
accuracy in the long term, both the goal setting and the operating processes have to be
organised, managed and measured keeping the overall DA objective in mind.
Two general factors affecting both the goal and the actual delivery accuracy were also
identified and are presented in the figure. Flexibility and a systematic way of
conducting the operations were seen as essential. Flexibility is an attribute that helps
the company to adjust to random or surprising fluctuations regarding for example
market situation or customers' needs. A systematic way of doing business is, for
instance, that the company is able to design its systems and processes in such a
manner that flexibility is possible. Without targets and schedules there is no
flexibility, only chaos.
Measurable factors
Measurable factors are attributes that are associated with the two main factors
affecting delivery accuracy. Further, there is a group of possible measures defined for
each of these factors. A detailed list of measures is presented in Appendix 2.
Measurable factors for the DA, goal and actual dimension are, respectively:
Delivery accuracy
• On-time delivered lines and orders
• Flexibility
• Systematic approach
Goal
• Need
• Load
• Materials availability
• Rules of the game: Goal
Actual
• Delivery lead-time
• Production lead-time
• Goods in stock and purchases
• Productive time
• Non-productive time
• Rules of the game: Actual
9
The attributes above are measured in order to be able to track the causes behind
delivery accuracy fluctuations, and, to enable improvements in DA by gaining
relevant information concerning the DA as a general phenomenon.
Measurement in action
Delivery accuracy measurement takes place at two levels. The first level is a graphical
measure of DA that shows both the internal delivery accuracy in the supply chain and
the external DA at the plant level. Team level measurement is based on a schedule
that is made according to some rules of thumb at the stage when the order is activated
in the information system of the plant. The principle of the graphical measure is
presented in Figure 5.
T2
T2
T3
C1
C2
C3
C5
C4
Figure 5. Graphical DA measure
Each team and cell has its own objective defined in the schedule, and different colours
are used to demonstrate whether the team or cell has reached its objective or not. This
kind of schedule is defined for each delivery lot. Green indicates that the team has
done its work according to the schedule so that the plant level DA is not
compromised. Yellow indicates that the team has reached its objective regarding the
lead-time but that some earlier phase in the chain has delayed the order so that the
plant level target seems not feasible at the moment. Red points out that the team has
not reached its targets and the plant level DA target is compromised. The colour of the
last team in the internal supply chain indicates if the external delivery accuracy of that
order is OK or not.
The second level of measurement consists of sets of measures that are chosen for team
level. The set of measures is collected from the list of measurable factors. DA
fluctuations can be understood and interpreted by examining the fluctuations of the
measurable factors at team level.
It depends on the industrial environment which measurable factors influencing DA
would be most suitable to explain the fluctuations of the delivery accuracy at the plant
level. An essential part of the implementation process of this kind of measure is thus
collection of experience regarding the behaviour of the specific environment. At the
initial stage, this type of measurement helps essentially to understand the phenomenon
of delivery accuracy. At the second stage, DA can be effectively improved.
10
Conclusions
Constructing a DA measure that is to be used to improve performance requires a
profound understanding of the factors and their interdependencies influencing
delivery time as well as the factors determining delivery time objectives.
The first objective of this paper was to establish a conceptual model for analysing
delivery lead-time and delivery accuracy in the supply chain. The second objective
was to discuss the implications of such a model for delivery accuracy measurement
and delivery accuracy improvement.
Delivery accuracy and DA measurement can be divided into two sections: internal
and external delivery accuracy. External delivery accuracy describes a company's
ability to satisfy the delivery requirements of its customers. Internal delivery accuracy
is a prerequisite for external DA, and it indicates how well the internal supply chain
members can satisfy the delivery needs of the other internal actors.
A typical measure for delivery accuracy is a percentage where the numerator is ontime or late deliveries and the denominator is all the deliveries at the same time
period. The advantage of this type of measure is simplicity: one figure is fairly easy to
understand and easy to read. However, there is also other relevant information related
to delivery accuracy that cannot be expressed with a single figure. The degree of
possible lateness and the severity of that lateness to the customer, for instance, are
factors that should also somehow be measured. In addition, in order to be able to
understand and to improve DA one should also measure factors that explain the
fluctuations of delivery accuracy.
Measurable factors influencing delivery accuracy were divided into two subgroups:
those that affect the process of defining delivery time target and those that affect the
realisation of the actual delivery time. A suitable set of measures should be tailored
taking into account the individual nature of any environment.
A delivery accuracy measurement system contains measures at two levels. The first
level is the graphical measure that shows both the internal and the external DA, or
lateness, in the supply chain. The second level consists of measures that help to
understand the behaviour of DA so that it can be effectively improved.
11
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12
Appendices
Appendix 1: DA model as a concept map
Appendix 2: List of measurable factors
APPENDIX 1
DELIVERY LEAD-TIME
FLEXIBILITY
Goal
SYSTEMATIC Approach
- planned flexibility
Promised
delivery date
Actua
Actual
delivery date
DELIVERY ACCURACY
Order
properties
What does the delivery time cost?
Need
∑
- Customer
- Product
- Price
- Amount
- Requested
delivery date
- Who decides
- Who will be informed
- Priorisation
- customer
- orders
- The effect of lead-time
through the process
Company
performance
Load
- Load without
the order
- Load caused
by the order
- The effect on
the present
schedule
Actual
DELIVERY LEAD-TIME
Rules of the game
Materials
availability
DESIRED DELIVERY
LEAD-TIME
FEASIBLE DELIVERY
LEAD-TIME
-
Rules of the
game
- Overtime work
- Re-arrangements
- Job rotation
- Absences
Purcha
ses
APPENDIX 2
Delivery accuracy
• On-time delivered lines and orders
• Team/production cell accuracy
Flexibility
• Deviations from the production plan/schedule
• Production cells
• Number of production plan rescheduling
• Production and managing teams
• Amount of overtime
• Teams and cells
• Job rotation
• Production cells
• Number of "special orders" compared with delivery accuracy
• Production
• Number of setups
• Production cells
Systematic approach
• DA goal/actual, Production load goal/actual
• Plant level, production cells
• Length of coarse scheduling period
• Production management
• Length of production period
• Production management
• Purchasing orders late/on time
• Planning and managing teams
• Negotiable margin with customer: time and price
• Selling teams
• Load fluctuations
• Production teams
• Delayed orders/all active orders
• Production and managing teams
1/4
APPENDIX 2
Goal
Need
• The importance of the customer
• Selling and managing teams
• The type of product ordered
• Selling and managing teams
• Requested delivery date
• Managing team
• The importance of the delivery date to the customer
• Managing teams
Load
• The load caused by the order per each team/cell
• Production cells
• The production load without the order
• Production cells
• The number of rescheduled orders if a new one is accepted
• Production, Plant
• The number of delayed orders if a new one is accepted
• Production, Plant
Materials availability
• Items is stock
• Planning and managing teams
• Standard delivery time for the needed material
• Planning and managing teams
• Critical materials
• Planning and managing teams
Rules of the game: Goal
• What is the promised delivery date based on?
• Planning and managing teams
• Who was involved in the process that led to promising a certain delivery date
• Managing team
• The number of "exceptional" delivery dates accepted
• Managing team
• The communication of exceptional delivery times to teams
• Managing team
2/4
APPENDIX 2
• The effects of speeding up the orders
• Planning, production and managing teams
• Self-assessment: Are the rules of the game obeyed?
• Planning, production and managing teams
Actual
Delivery lead-time
• The development of lead-time
• Plant
• Production lead-time/delivery lead-time
• Plant
• The number of exceptional lead-times
• Plant
• The number of changes regarding lead-times
• Planning team
• Delivery lead-time compared to production load
• Plant
Production lead-time
• The development of production lead-time
• Production
• Production cells lead-time and the development
• Production cells
• Teams lead-time and the development
• Planning and managing teams
• Lead-time and production load
• Production cells
• Deviation from the standard lead-times
• Planning, production and managing teams
Goods in stock and purchases
• Inventory value and development
• Plant
• Inventory turnover and development
• Plant
• The number of items
• Plant
• On-time purchases
• Planning and managing teams
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APPENDIX 2
• Purchases arriving on-time
• Planning and managing teams
• The DA of the suppliers and plant DA
• Planning and managing teams
Productive time
• Planning and designing time
• Planning team
• Machine time
• Production teams
• Project hours
• Production teams
• Faults and halts
• Production teams
• Halts caused by delayed material supplies
• Production teams
Non-productive time
• Measurements
• Production teams
• Tool shifts
• Production teams
• Jig shifts
• Production teams
• Specifying inquiries
• Production teams
• Quality defects
• Production teams
Rules of the game: Actual
• Overtime arrangements
• Plant
• The amount of overtime
• Plant
• Deciding a schedule objective for individual team, flexibility of the others
• Plant
• Job rotation inside cell
• Production cells
• Job rotation between cells
• Production cells, Plant
• Absences and vacations
• Plant
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