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Summary Chapter 11 Operations Management

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A good summary of chapter 11 based on the book Operations Management by Slack including the supplement of chapter 11.

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  • Hoofdstuk 11
  • 11 januari 2021
  • 22
  • 2020/2021
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Chapter 11 Capacity Management
What is capacity management?
 Capacity management: the activity of understanding the nature of product or service
demand, and effectively planning and controlling capacity.

Capacity decisions are taken across multiple time horizons. They are also made within the
constraints of the operation, the ability of its suppliers to supply, the availability of staff, and so on.
As such, each level of capacity decision is made within the constraints of a higher level. In the other
direction, short-term decisions provide important feedback for planning over longer-term time
horizons.




Aggregate planning of demand and capacity
The important characteristic of capacity management is that it is concerned with setting capacity
levels over the medium and short terms in aggregated terms. Aggregated means – different
products and services are bundled together in order to get a broad view of demand and capacity.
This may mean some degree of approximation, especially if the mix of products or services being
created varies significantly.

Capacity management performance objectives
Decisions taken by operations managers in devising their capacity plans will affect several different
aspects of performance:

- Costs will be affected by the balance between demand and capacity. Capacity levels in
excess of demand could mean under-utilization of capacity and therefore high units cost.
- Revenues will also be affected by the balance between demand and capacity, but in the
opposite way. Capacity levels equal to or higher than demand at any point in time will
ensure that all demand is satisfied and no revenue lost.

, - Working capital will be affected if an operation decides to build up finished goods inventory
prior to demand. This might allow demand to be satisfied, but the organization will have to
fund the inventory until it can be sold.
- Quality of services might be affected by a capacity plan that involves large fluctuations in
capacity levels, by hiring temporary staff for example. The new staff and the disruption to
the routine working of the operation could increase the probability of errors being made.
- Speed of response to customer demand could be enhanced either by the deliberate
provision of surplus capacity to avoid queuing, or through the build-up of inventories.
- Dependability of supply will also be affected by how close demand levels are to capacity. The
closer demand gets to the operation’s capacity ceiling, the less able it is to cope with any
unexpected disruptions and the less dependable its deliveries of goods and services could
be.
- Flexibility, especially volume flexibility, will be enhanced by surplus capacity. If demand and
capacity are in balance, the operation will not be able to respond to any unexpected
increase in demand.

A framework for capacity management
There are a series of activities involved in capacity management:

1. Involves selecting from a range of qualitative and quantitative tools to support more
accurate prediction of demand. It also requires balancing between investments in between
better forecasts and investments in greater operations flexibility.
2. Involves measuring the capacity to deliver products and services. The impacts of product or
service mix, timeframe and output specification should be considered.
3. Consider if and how to manage demand using demand management and yield management
techniques.
4. To manage the supply side by determining the appropriate level of average capacity and
then deciding whether to keep this constant of the timeframe or to adjust capacity in line
with changing demand patterns.
5. Operations managers must understand the consequences of different capacity management
decisions for both the demand side and supply side of the framework. Using cumulative
representations, principles of queuing and a longitudinal perspective can all help in the
decision-making process.

, How is demand measured?
The first task of capacity management is to understand the patterns of demand for products and
services. Knowing the rate of change is often vital for business planning. So the key questions when
considering demand include:

- What is the overall demand for a product or service over a period of time?
- How much does demand change?
- Are the total requirements and/or the changes in demand easy or difficult to predict?
- In any period of time, how much does demand change, and how accurate is forecast
demand likely to be?

Qualitative approaches to forecasting
Three popular qualitative forecasting methods are:

1. The panel approach
2. Delphi method
3. Scenario planning

Panel approach
The panel acts like a focus group allowing everyone to talk openly and freely. Although, more
reliable than one person’s views, the panel approach still has the weakness that everybody, even the
experts, can get it wrong.

Delphi method
This is a more formal method which attempts to reduce the influences from procedures of face-to-
face meetings. One refinement of this approach is to allocate weights to the individuals and their
suggestions based on, for example, their experience, their past success in forecasting, and other
people’s views of their abilities. The obvious problems associated with this method include
constructing an appropriate questionnaire, selecting an appropriate panel of experts, and trying to
deal with their inherent biases.

Scenario planning
This is usually applied to long-range forecasting again using a panel. Unlike the Delphi method,
scenario planning is not necessarily concerned with arriving at a consensus but looking at a range of
options and putting plans in place to try to avoid the ones that are least desired and taking action to
follow the most desired.

Quantitative approaches to forecasting
Managers sometimes prefer to use quantitative methods to forecast demand. Two key approaches
are:

1. Time series analysis
2. Causal modelling techniques

Time series examine the pattern of past behavior of a single phenomenon, over time, taking into
account reasons for variation in the trend, in order to use the analysis to forecast the phenomenon’s
future behavior.

Causal modelling is an approach which describes and evaluates the complex cause-effect
relationships between the key variables.

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