Demand management → Focused efforts to estimate and manage customers’ demand, with the
intention of using this information to shape operating decisions. The essence of demand management
is to further the ability of firms throughout the supply chain to collaborate on activities related to the
flow of products, services, information, and capital.
Desired end result → Create greater value for the end user or consumer.
Common problems in demand management are:
1. Lack of coordination between departments
2. Too much emphasis placed on forecasts of demand, with less attention on the collaborative
efforts and plans needed to be developed from the forecasts
3. Demand information is used more for tactical and operational purposes than for strategic ones
Ways in which effective demand management will help to unify channel members with the common
goals of satisfying customers and solving customer problems:
1. Gather and analyze knowledge about consumers, their problems, and their unmet needs.
2. Identify partners to perform functions needed in demand chain.
3. Moving the functions that need to be done to the channel member that can perform them most
effectively and efficiently.
4. Sharing with other supply chain members knowledge about consumers and customers,
available technology, and logistics challenges and opportunities.
5. Developing products and services that solve customers’ problems.
6. Developing and executing the best logistics, transportation, and distribution methods to deliver
products and services to consumers in the desired format.
,Phases are:
1. Product launch:
- High demand for the new product
- Availability is limited, creating true shortages
- Over-ordering by distributors adds to phantom demand
2. Production and sales:
- Production increases, sales happen at a premium
- Growing inventories lead to price competition and returns
3. Final phase:
- End-user demand decreases, resulting in oversupply
- Most sales occur during declining profit period
Effective demand management supports business strategy:
1. Perform ‘what if’ analysis on total industry volume to measure how specific mergers
and acquisitions might leverage market share.
Growth strategy
2. Analyze industry supply/demand to predict changes in product pricing structure and
market economics based on mergers and acquisitions.
1. Create new product development/introduction plans based on life cycle.
Portfolio strategy
2. Ensure diversification of product portfolio through demand forecasts.
1. Manage sales through each channel based on demand and product economics.
Positioning strategy
2. Define capability to supply for each channel.
1. Determine whether to add manufacturing capacity.
Investment strategy 2. Manage capital investments, marketing expenditures, and R&D budgets based on
demand forecasts of potential products and maturity of current products.
Four methods to manage imbalance between supply and demand:
1. External balancing methods → Change the manner in which the customer orders:
- Price → Decrease when demand is less than inventory levels.
- Lead time → Increase when demand exceeds current supply.
2. Internal balancing methods → Utilize internal processes to manage the gap:
- Inventory → Producing product to a forecast that includes safety stock minimizes the
number of changeovers but also results in high inventory levels.
- Production flexibility → Allows to quickly and efficiently change production lines from
one product to another. Able to react quickly to changing demand. Tradeoff between
production changeover costs and safety stock costs.
Use and level of implementation will be determined by nature of the product and cost of stocking out.
Key to successful forecasting is to minimize the error between actual demand and forecasted demand.
Forecasts serve as a plan for both marketing and operations to set goals and develop execution
strategies.
,There are two types of demand:
1. Independent demand → Demand for the primary item
2. Dependent demand → Directly influenced by the demand for the independent item
Forecasting will usually be done at the independent demand item level. Normally demand for
independent demand items is known as base demand (normal demand). All demand is subject to
certain fluctuations:
1. Random fluctuation → A development that cannot be anticipated and is usually the cause to
hold safety stock to avoid stockouts
2. Trend fluctuation → Gradual increase or decrease in demand over time for an organization
3. Seasonal fluctuation → Seasonal patterns that will normally repeat themselves during a year
4. Demand fluctuations can be caused by normal business cycles, usually driven by a nation’s
economy and can be growing, stagnant, or declining. Usually over periods of more than 1 year
Key to successful forecasting is to choose the technique that provides the least amount of forecast
error. Types of forecast error measures can be used:
1. Cumulative sum of forecast errors (CFE) → Calculates the total forecast error for a set of data,
taking into consideration both negative and positive errors.
2. Mean squarred error (MSE) → Squares each period error so the negative and positive errors
do not cancel each other out.
3. Mean absolute deviation (MAD) → Takes absolute value of each error, so the negative and
positive signs are removed. Most popular measure because it is easy to understand and
provides a good indication of the accuracy of the forecast.
4. Mean absolute percent error (MAPE)
5. Tracking signal → Can be used to measure forecast errror, especially good at identifying if a
bias exists in the forecast errors (CFE / MAD).
All statistical techniques used to generate forecasts require accurate data and rely on the assumption
that the future will repeat the past. The key to good forecasting is to minimize forecast error by utilizing
a forecasting technique that best fits the nature of the data. Three common forecasting techniques are:
1. Simple moving average → Makes forecasts based on recent demand history and allows for
the removal of random effects.
- Pros → Quick and easy to use.
- Cons → Does not accommodate seasonal/trend/business cycle influences.
2. Weighted moving average → Assigns a weight to each previous period with higher weights
usually given to more recent demand.
- Pros → Allows emphasis on more recent demand as a predictor of future demand.
- Cons → Not easily accommodate seasonal demand patterns.
, 3. Exponential smoothing → One of most commonly used because of simplicity.
- Pros → Simplicity and limited requirements for data, good for relatively constant demand.
- Cons → Forecasts will lag actual demand. Not appropriate for highly seasonal demand
patterns or patterns with trends.
It is necessary for an organization to arrive at a forecast internally that all functional areas agree upon
and can execute. A process that can be used to arrive at this consensus forecast is called sales and
operations planning (S&OP). Preliminary demand forecast → S&OP → Internal consensus forecast.
Prelimary demand forecast consists of marketing, financial, distribution, and manufacturing forecast.
1. Run sales forecast reports → Requires development of a statistical forecast of future sales.
2. Demand planning phase → Requires sales and/or marketing departments to review the
forecast and make adjustments based on promotions of existing products, introduction of new
products, or elimination of products.
3. Supply planning phase → Requires operations to analyze the sales forecast to determine if
existing capacity is adequate to handle the forecasted volumes.
4. Pre-S&OP meeting → Asks individuals from sales, marketing, operations, and finance to
attend a meeting that reviews the initial forecast and any capacity issues that might have
emerged during step 3.
5. Executive S&OP meeting → Where final decisions are made regarding sales forecasts and
capacity issues. Consensus is critical.
Collaborative planning, forecasting, and replenishment (CPFR) is a method to allow trading partners in
the supply chain to collaboratively develop and agree upon a forecast of sales to enable integrated
operational planning and execution. Trading partners (retailers, distributors, and manufacturers) use
available internet-based technologies to collaborate on operational planning, allowing them to agree to
a single forecast for an item where each partner translates this forecast into a single execution plan.
The four major processes are:
1. Strategy and planning
2. Demand and supply management
3. Execution
4. Analysis
The model includes cooperation and exchange of data among business partners and is a continuous,
closed-loop process that uses feedback as input for strategy and planning. Strength of CPFR is that it
provides a single forecast from which trading partners can develop manufacturing strategies,
replenishment strategies, and merchandising strategies. Benefits are reduced supply chain inventories
and out-of-stocks.
In short → CPFR involves consumers, retailers, and manufacturers to optimize supply chain
processes. It emphasizes shared data, continuous feedback, and a unified forecast for effective
planning, reducing inventories, and improving service and cost performance among partners.
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