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Introduction To Demand Forecasting Business Essay

Paper Type: Free Essay Subject: Business
Wordcount: 4627 words Published: 1st Jan 2015

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Introduction to Demand Forecasting:

Forecasting provides an estimate of future demand and the basis for planning and sound business decisions. Since all organizations deal with an unknown future, some error between a forecast and actual demand is to be expected. Thus, the goal of a good forecasting technique is to minimize the deviation between actual demand and forecast. Since a forecast is a prediction of the future, factors that influence demand, the impact of these factors, and whether these factors will continue influence future demands must be considered in developing an accurate forecast. In addition, buyers and sellers should share all relevant information to generate a single consensus forecast so that the correct decision on the supply and demand can be made. The benefits of a better forecast are lower inventories, reduce stock outs, smoother production plans, reduced costs and improved customer service. (Wisner, Tan, & Leong, 2008)

The impact of a poor communication and inaccurate forecast resonates all along the supply chain and results the bull whip effects causing stock outs, lost sales, high cost of inventory and obsolesce, material shortages, poor responsiveness to market dynamics, and poor profitability. (Wisner, Tan, & Leong, 2008)

Matching Supply And Demand:

The concept of matching supply with demand is straightforward. Just strike the right balance between what your customers want and the inventory investment required to meet that demand. Demand forecasting may be used in making pricing decisions, in assessing future capacity requirements, or in making decisions on whether to enter a new market.

Now a day business scenario is completely change & revived. Demand, supply, logistics, whole supply chain management. Now we have consumer who are more focused & demanding. Whole buying behavior is turn into pull behavior where suppliers are more concern about consumers demand. Now a day retailer if supplier do not full fill the target requirement of retailer of right quantity, right time & right price that retailer would not wait long for supplier to fulfill requirement rather prefer to switch supplier. (Wisner, Tan, & Leong, 2008)

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Here matching supply & demand forecast help any company to slice the threat of stock out, sales, customer relationship, business loyalities.in order to achieve sound supply chain, supplier must have forecast the future conditions so they can meet the expected targets & deliver right commodities to its customers in a timely manner & cost effective approach. (Wisner, Tan, & Leong, 2008)

Of course, it’s not that easy. Buying too much wastes time, money and space-and exposes you to potential losses from liquidating overstocks. Underestimating demand leads to backorders, cancellations and unsatisfied customers who turn to your competitors. Incorporating SCM successfully leads to a new kind of competition on the global market where competition is no longer of the company versus company form but rather takes on a supply chain versus supply chain form. (decisioncraft.com)

The primary objective of supply chain management is to fulfill customer demands through the most efficient use of resources, including distribution capacity, inventory and labor. In theory, a supply chain seeks to match demand with supply and do so with the minimal inventory. Various aspects of optimizing the supply chain include liaising with suppliers to eliminate bottlenecks; sourcing strategically to strike a balance between lowest material cost and transportation, implementing JIT (Just In Time) techniques to optimize manufacturing flow; maintaining the right mix and location of factories and warehouses to serve customer markets, and using location/allocation, vehicle routing analysis, dynamic programming and, of course, traditional logistics optimization to maximize the efficiency of the distribution side. (decisioncraft.com)

The effects that inventory levels have on sales. In the extreme case of stock-outs, demand coming into your store is not converted to sales due to a lack of availability. Demand is also untapped when sales for an item are decreased due to a poor display location, or because the desired sizes are no longer available. (Wisner, Tan, & Leong, 2008)

Demand for an item will likely rise if a competitor increases the price or if you promote the item in your weekly circular. The resulting sales increase reflects a change in demand as a result of consumers responding to stimuli that potentially drive additional sales. In this case demand forecasting uses techniques in causal modeling. Demand forecast modeling considers the size of the market and the dynamics of market share versus competitors and its effect on firm demand over a period of time.

No demand forecasting method is 100% accurate. Combined forecasts improve accuracy and reduce the likelihood of large errors. (Wisner, Tan, & Leong, 2008)

Purposes of Forecasting:

Purposes of Short-Term Forecasting

Appropriate production scheduling.

Reducing costs of purchasing raw materials.

Determining appropriate price policy

Setting sales targets and establishing controls and incentives.

Evolving a suitable advertising and promotional campaign.

Forecasting short term financial requirements.

Purposes of Long-Term Forecasting

Planning of a new unit or expansion of an existing unit.

Planning long term financial requirements.

Planning man-power requirements.


Length of Forecasts:

Short-term forecasts – up to 12 months, e.g., sales quotas, inventory control, production schedules, planning cash flows, budgeting.

Medium-term – 1-2 years, e.g., rate of maintenance, schedule of operations, and budgetary control over expenses.

Long-term – 3-10 years, e.g., capital expenditures, personnel requirements, financial requirements, raw material requirements.(Most uncertain in nature) (webcache.com)

Control Demand or Management of Demand:

The key to management of demand is the effective management of the purchases of final consumers.

The management of demand consists in devising a sales strategy for a particular product. It also consists in planning a product, or features of a product, around which a sales strategy can be built. Product design, model change, packaging and even performance reflect the need to provide what are called strong selling points. (webcache.com)

Forecasting Techniques:

Understanding that the forecast is very often inaccurate does not mean that nothing can be done to improve e the forecast. Both quantitative and qualitative forecast can be improved by seeking inputs from trading partners. Qualitative forecasting methods are based on opinions and intuition whereas quantitative forecasting methods use mathematical models and relevant historical data to generate forecast.

Qualitative Methods:

The qualitative methods are subdivided into. The four common qualitative forecasting models are,

Jury Of Executive Opinion:

Qualitative forecasting in which a group of senior management executives who are knowledgeable about the market, competitors, and the business environment collectively developed the forecast.

Delphi Method:

Qualitative forecasting in which a group of internal and external experts are surveyed during several rounds in term of future events and long term forecasts of demand; the group members do not physically meet.

Sales Force Composite:

Qualitative forecast generated based on the sales force’s knowledge of the market and estimates of the customers need.

Consumer Survey:

A questioner administered through telephone, mail, internet, or personal interviews that seeks inputs from customers on important issues such as future buying habits, new product ideas, and opinions about existing products. (Wisner, Tan, & Leong, 2008)

Quantitative Methods:

Time series forecasting is based on the assumptions that the future is an extension of the past, thus, the historical that can be used to predict future demands. The components of time series data are,

Trend Variations:

Either increasing or decreasing ,movements over many years that are due to factors such as population growth, population shifts, cultural changes, and income shifts.

Cyclical Variations:

Wave like movements that are longer than a year and influenced by macro economic and political factors.

Seasonal Variations:

Peaks and valleys that repeat over a constant interval such as hours ,days, weeks, months, years, or seasons.

Random Variations:

Random peaks and valleys those are due to unexpected or unpredictable events such as natural disasters (hurricanes, tornadoes, fire) strikes, and wars.

(Wisner, Tan, & Leong, 2008)

Collaborative Planning, Forecasting and Replenishment (CPFR):

Voluntary Inter industry Commerce Standards (VICS),a New Jersey based Association defines Collaborative Planning, Forecasting and Replenishment(CPFR) as, “a business practice that combines the brainpower of two or more trading partners in planning the ways to fulfill the customer demand.” They also explained the relationship that CPFR links best practices of sales and marketing, such as category management, to the implementation of supply chain planning and completion process, “to increase availability while reducing inventory, transportation and logistics costs.”

Basically CPFR is an approach that deals with the requirements for good demand management. The most involved industries with CPFR are consumer products and food and beverage. (Collaborative Planning,Forecasting & Replenishment CPFR)

Objective of CPFR:

The objective of CPFR is to “optimize” the supply chain process by:

Improving accuracy of forecasting demand

Delivering the right product at the right time to the right location

Reducing inventory

Avoiding stock outs

Improving customer service

But the most important fact on which the achievement of objective and activities of CPFR depend is to have collaborative trading partners who share risk and information mutually in the whole process.

Without Collaborative planning and forecasting between the trading partners will make the supply chain “suboptimal”, thus will result in less-than-maximum supply chain profits. (Wisner, Tan, & Leong, 2008)

Real value of CPFR:

It is observed that forecasting developed only by firm tends to be inaccurate most of the time so therefore in CPFR when both the buyer and seller collaborate in forecasting, then it makes possible to match buyer needs with supplier production plans, thus ensuring competent replenishment. CPFR also helps in avoiding expensive corrections after the fact when demand or promotions have changed. (Wisner, Tan, & Leong, 2008)

Benefits of CPFR:

Strengthens supply chain partner relationships

Provides analysis of sales and order forecast which improves the forecast accuracy

Manage the demand chain and proactively eliminate problems before they appear

Allow collaboration on future requirements and plans

Combine planning, forecasting and logistic activities

Provides efficient category management and understanding of consumer purchasing patterns (Wisner, Tan, & Leong, 2008)

Example 1:

West Marine is one of the companies that has greatly benefited by implementing CPFR.They had CPFR relationships with 200 suppliers, 85 percent forecast accuracy, and 80 percent on-time shipments.

For CPFR success collaboration with external part is important, and it is equally important that effective collaboration within the company is emphasized. For example: logistics, planning and replenishment personnel must work closely together.

Example 2:

CPFR was also implemented by ITT’s Jabsco division, West Marine’s largest customer. During the process they experienced a reduction in cycle time from twenty-five days to three days, an increase in total sales of 11 percent, and a great improvement in on-time deliveries from 74 to 94 percent.

Example 3:

Wal-Mart is one of the early implementer of CPFR. CPFR enabled Wal-Mart to move into Just-in-Time (JIT) system that resulted in significant savings in inventory carrying costs for Wal-Mart, as well as its suppliers.

Example 4:

In late 1990’s, most of the large American-based multinational companies such as Procter & Gamble (P&G) and Wal-Mart enter into a system called Collaborative Planning, forecasting and Replenishment. (Williams)

Challenges for CPFR implementation

There are top three difficulties faced by organizations in implementing CPFR:

Making internal changes: Internal changes must always be tackled by top management as change is always difficult but if the top management is dedicated to the project and in educating employees about the benefits of CPFR then there are more chances of getting a successful internal change.

Total implementation cost: Although cost is an important factor to be considered always but companies must determine whether they are at a competitive disadvantage.

Trust: is one of the biggest hurdles in general implementation of CPFR as many retailers are unwilling to share the information required to implement CPFR. For example: Wal-Mart may be willing to share their sensitive data with the Wal-Mart only as they do not want other suppliers to know their information.

(Wisner, Tan, & Leong, 2008)

Emerging Trends:

Companies are finding new and innovative ways to collaborate. For example, Procter and Gamble has implemented CPFR not only with some of its retail customers, but also with its suppliers, and even inside the company, between functions and divisions. (Sheffi, 2002)

Standard CPFR Trading Partner Processes

Source: ©2008 Hypatia Research, LLC.

(Collaborative Planning,Forecasting & Replenishment CPFR)

CPFR: Key Tenets

The consumer is the ultimate focus of all efforts

Buyers” (retailers) and “sellers” (manufacturers) collaborate at every level

Joint forecasting and order planning reduces surprises in the supply chain

The timing and quantity of physical flows is synchronized across all parties

Promotions no longer serve as disturbances in the supply chain

Exception management is systemized (Edward, 2003)

CPFR Process Model:

The CPFR reference model provides a framework for planning, forecasting and replenishment process. Figure below represents the framework components. A buyer and a seller work as Collaboration Partners and work together to satisfy the customer demand which at the centre of the model.


The key CPFR activities to enhance performance of Collaboration partners are –

1. Strategy & Planning – Establish the rules for collaborative relationship. Determine the product mix and develop event plans for the period.

2. Demand and Supply Management – Project consumer (POS) demand, as well as order and shipment requirements over the planning period.

3. Execution – Place orders, prepare and deliver shipments, receive and stock products in retail stores, record sales transactions and make payments.

4. Analysis – Monitor planning and execution activities for exception conditions. Aggregate results and calculate KPI’s. Share insights and adjust plans for better performance. (www.ncsm.edu)

CPFR Tasks in Detail:

To understand in greater detail what businesses and their trading partners need to plan as part of their collaboration activities we need to analyze the tasks under each of the four identified Collaboration Activities.  The collaborations tasks and their mapping to collaboration activities is given in the table below –

CPFR Activity Task Mapping:

CPFR Activity


Trading Partners

Strategy & Planning

Collaboration Arrangement Joint Business Plan

Manufacturer, Retailer

Demand & Supply Management

Sales Forecasting

Order Planning/Forecasting

Manufacturer, Retailer


Order Generation

Order Fulfillment

Manufacturer, Retailer


Exception Management

Performance Assessment

Manufacturer, Retailer



CPFR in Action

Organizations can begin with successful CPFR with cooperation and timely plans. This combined approach helps all the trading partners such as retailers and manufacturers to unite in a formal agreement to perform the supply chain processes and establish a joint business plan. The CPFR software’s enables manufacturers, distributors and retailers to make the right decision about the material, stock and other resources required before placing the final order.

CPFR is one of the powerful tools as it supports the whole supply chain process followed by nine steps defined as: (Edward, 2003)

Phase I – Planning

In this phase, the emphasis is on developing element of trust between the people so that they give devoted work at different stages and processes. All types of barrier should be removed by the company’s top management such as cultural barriers so that employees may feel comfortable working with them and will remain motivated towards their task performance.

Firstly, the trading partners must clearly share their identities and processes in order to make a stronger bond between them, thus, the strong relationship will later help in setting a standard benchmark with mutual acceptance making more chances to be successful in achieving their organization targets. (Edward, 2003)

There are two major steps that make up a front-end agreement and a joint business plan.

Step 1: Developing Collaboration Agreement

The Business Intelligence modules allow partners to define and measure specific KPIs. Web Planning ensures that all partners have access to the information simultaneously, while the Portal makes all the data and information visible across the supply chain. (Edward, 2003)

The buyers and sellers must agree on the objectives of collaboration, ground rules, for resolving disagreements, confidentiality of information to be shared, sales forecast exception criteria, review cycle, time frame, and frozen time period with acceptable tolerance, financial incentives and success metrics. (Wisner, Tan, & Leong, 2008)

Step 2: Crafting a Joint Business Plan

A joint business plan is developed by sharing the companies’ business strategies and plans. The plan typically involves developing a joint product category and promotional plan in which the appropriate category strategies inventory policies, promotional activities’, and pricing policies are specified. (Wisner, Tan, & Leong, 2008)

The front-end agreement should produce a long-term pact spanning the life of the business. Obviously, an enormous amount of information will flow between partners. Who should get what? When? Where? How much should they get (Edward, 2003)

Phase II – Forecasting

The J.D. Edwards CPFR solution begins with a collaborative forecast of end-user demand and continues through all aspects of supply chain planning, providing support for both long-term and day-to-day decisions. In Phase II, an organization creates the sales forecast, which then feeds into the order forecast. (Edward, 2003)

Step 3: Forecasting Sales

Using the Demand Forecasting application, organizations can build multi-dimensional models, which may include product hierarchies, geographies, channels, and specific customers. Causal variables such as pricing, promotions, and new store openings can also be completely integrated. In addition, historical data can be combined with near real-time variations in the channel to get the most accurate forecast. (Edward, 2003)

Either partner or both partners may generate the sales forecast. The forecasting techniques’ used can be qualitative or quantitative. When both partners each generate a forcast, middleware is used to highlight the difference, based on predetermined exception criteria previously agreed upon by the partners. (Wisner, Tan, & Leong, 2008)

Steps 4 and 5: Collaborating to Develop a Shared Forecast

Beginning with Demand Forecasting’s statistical forecast, users can make changes to an existing forecast or import their own forecast based on the most up-to-date information.

Multiple forecasts can be reconciled using a powerful algorithm that takes into account the historical accuracy of different forecast contributors. Exceptions are easily identified and messages are sent to reconcile unusual items.

Examples of sales forecast exception criteria are: retail in stock is less then 95 %, sales forecast error is greater the 20 %, the difference in sales forecast from the same period of the previous year is greater then 10%, or any changes that have occurred in timing of promotional active stores, The real-time joint decision making reduces the risk & increase the confidence in the single forecast. (Wisner, Tan, & Leong, 2008)

Each contributor (partner, supplier, and customer) becomes an integral part of the real-time collaborative process. The final enterprise forecast is the combination of the most accurate and timely information available.

(Edward, 2003)

Step 6: Forecasting Orders

The order forecast relies on point-of-sale (POS) data, causal information, and inventory strategies to generate a specific forecast that supports the shared sales forecast. Actual volume numbers are time-phased and reflect inventory objectives sorted by product and receiving location. The order forecast allows the manufacturer to allocate production capacity against demand while minimizing safety stock.

J.D. Edwards supports this process by systematically aligning production capacity and scheduling items to give retailers increased confidence that orders will be delivered. With Production and Distribution Planning, it is possible to break down the sales forecast by sales period, sales region, and to more specific levels, such as individual stores. The order forecast integrates the sales forecast with order requirements to develop specific demand at retail level. Production and Distribution Planning ensures that the right product is built and delivered to the right aisle of the right store at the right time.

In turn, Production and Distribution Planning works with Production Scheduling, breaking down production requirements on a daily or even hourly basis to ensure that the correct capacity and throughput are optimized to fill the necessary order. Operating through real-time collaboration reduces the uncertainty between trading partners and leads to consolidated supply chain inventories.

Inventory levels are decreased, customer responsiveness is increased, and a platform for continual improvement among trading partners is established.

(Edward, 2003)

Steps 7 and 8: Identifying and Resolving Exceptions

Identifying exceptions, determines what items fall outside the order forecast constraints established by the partners. The result is a list of exception items that are identified using the criteria established in the front-end agreement.

Step eight, resolving exceptions, involves the process of investigating order forecast exceptions by querying shared data and submitting results to changes in the order forecast. Once again, the guidelines set down in the front-end agreement (or negotiations among partners) determine how those exceptions are resolved. (Edward, 2003)

Phase III – Executing

During the final CPFR phase, front-end planning and forecasting come together with supply chain execution. Through J.D. Edwards’ collaborative CPFR solution, the order is generated and committed to delivery, enabling successful order delivery execution.

Step 9: Generating Orders

The final step in the CPFR process is generating the order and promising the delivery. The essence of maintaining positive relationships with partners and customers is to deliver on promises.

Order Promising “tags” inventory (or raw materials) and addresses production schedules and transportation constraints to ensure that the product is ready when needed. Using Order Promising, companies can instantly determine where orders can best be satisfied – from inventory at any location, planned production orders, or purchase receipts. When there is a promotion (such as a new store opening or product launch), Order Promising allows companies to quote future delivery dates or other key information related to the event. (Edward, 2003)

Step 10: Executing to the CPFR Plan

Although order generation is the ninth and final step of the formal CPFR model, the process doesn’t end there. In effect, there is a tenth step involving execution of the order. This is where

J.D. Edwards distinguishes itself. Once CPFR planning is complete, the model can feed data directly into J.D. Edwards Supply Chain Execution applications. Manufacturing, warehousing, order fulfillment, and transportation plans are completely synchronized into an integrated package to monitor and ensure on-time execution of the order delivery process.

(Edward, 2003)


Proper demand forecasting enables better planning and utilization of resources for business to be competitive. Forecasting is an integral part of demand management since it provides an estimate of the future demand and the basis for planning and making sound business decisions. A mismatch in supply and demand could result in excessive inventory and stock outs and loss of profit and goodwill. Both qualitative and quantitative methods are available to help companies forecast demand better. Since forecasts are seldom completely accurate, management must monitor forecast errors and make the necessary improvement to the forecasting process.

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Forecast made in isolation tend to be inaccurate. Collaborative planning, forecasting, and replenishment are an approach is which companies work together to develop mutually agreeable plans and take responsibility for their actions. The objectives of CPFR is to optimize the supply chain by generating a consensus demand forecast, delivering the right product at the right time to the right location, reducing inventories, avoiding stock outs, and improving customer services. Major corporations such as Wall-Mart, Warner-Lambert, and Proctor & Gamble are early adopters of CPFR. Although the benefits of CPFR are well recognized, wide spread adoption has not materialized.


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