Demand Forecasting, S&OP, CPFR

Demand Forecasting is a process of estimating the service or product quantity required by end customers. Demand forecasting techniques include the use of current or historical sales data to anticipate future demand. Other factors taken into consideration in make the final forecast are seasonal trends or 'events' trends. Data from finance, sales & marketing and production are all usually considered. The demand forecast that is arrived at is based on this combined information once fully assessed. Other software functionality elements include Sales & Operations Planning (S&OP). This is a business management process that takes into consideration data from both the business/finance and operational aspects of a company to reach determine a forecast or plan that best serves the whole organisation, rather than a segment of it.

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7 methods that improve forecast accuracy - a Logility White Paper

7 methods that improve forecast accuracy - a Logility White Paper

Gartner reports demand forecast accuracy creates high responsiveness and cuts cost throughout the supply chain. Companies that are best at demand forecasting average 15% less inventory, 17% stronger perfect order fulfilment and 35% shorter cash-to-cash cycle times, while having the tenth of the stock-outs of their peers.

The full view - Planning/Forecasting/S&OP technology report - June 2013

The full view - Planning/Forecasting/S&OP technology report - June 2013

Manufacturing & Logistics IT spoke with a number of spokespeople from the supply chain planning vendor community about some of the key developments and innovations that are currently enhancing and broadening the planning, forecasting and S&OP landscape.

Demand Solutions Offers Fully Integrated Sales & Operations Planning on a Single, Common Platform

Demand Solutions Offers Fully Integrated Sales & Operations Planning on a Single, Common Platform

Demand Management Inc., the global resource for supply chain management solutions, has announced its new Sales & Operations Planning (S&OP) module for its DSX supply chain software that fully integrates sales and operations planning with demand forecasting and requirements planning.

Advanced Planning & Scheduling Techniques..a white paper from Demand Solutions

Advanced Planning & Scheduling Techniques..a white paper from Demand Solutions

Many theories and commercial software solutions for Advanced Planning and Scheduling, known as APS, have appeared over the years. Ultimately, scheduling systems strive to answer the question of “When should this task be scheduled, and what resources should accomplish the work?” This paper examines the available methods for quickly creating production plans and schedules for manufacturers to meet their business objectives.

SAS Analytics takes guesswork out of forecasting

SAS Analytics takes guesswork out of forecasting

For manufacturers launching new products, the ability to more accurately answer "What will happen if ...?" is a significant competitive advantage. SAS, the leader in business analytics, delivers that advantage with enhanced SAS Demand-Driven Forecasting software that helps manufacturers create more accurate sales and operations plans bolstered by efficient distribution networks.

Woolworths South Africa selects JDA Software Solutions to optimise its retail supply chain

Woolworths South Africa selects JDA Software Solutions to optimise its retail supply chain

JDA Software Group, Inc., has announced that South African retail chain Woolworths has selected a number of JDA solutions in the fourth quarter of 2011.

Optimum ensures professional user training for ASSA ABLOY's Dynamics AX rollout

Optimum ensures professional user training for ASSA ABLOY's Dynamics AX rollout

Optimum Technology Transfer Ltd., the IT user engagement consultancy, has been selected by ASSA ABLOY to support the implementation of their new Dynamics AX business system in the UK.

Reinert Logistic equipped to optimise route planning for Lafarge, with the help of Ortec

Reinert Logistic equipped to optimise route planning for Lafarge, with the help of Ortec

When European logistics service provider, Reinert Logistic GmbH & Co. KG, was tasked with initiating a transport optimisation programme for its client, Lafarge Gypsum (part of the global Lafarge Group), the LSP looked to Ortec to supply and implement the optimal solution.

JDA FocusConnect 2011 - 25th-27th October, Sofitel Hotel, Heathrow.

JDA FocusConnect 2011 - 25th-27th October, Sofitel Hotel, Heathrow.

This annual Supply Chain Excellence conference hosts supply chain experts from Manufacturing, Retail and Wholesale Distribution all under one roof. In 2010, over 400 delegates attended over 70 sessions during the 3 days, so mark your calendar now for 2011!

Is Advanced Planning and Scheduling Right for You?

Is Advanced Planning and Scheduling Right for You?

For companies that require APS capabilities, the impact can be significant in terms of increased efficiency, improved customer service levels and increased visibility across departments.

Forecasting demand is an important task for just about any type of business. Accurately projecting the demand for specific goods and services helps companies to order raw materials and schedule production of those products in a timely manner, making it possible to fill consumer orders quickly and efficiently without the need to build up a large inventory that adds to the tax burden of the business.

 

Demand Forecasting is the activity of estimating the quantity of a product or service that consumers will purchase. Demand forecasting involves techniques including both informal methods, such as educated guesses, and quantitative methods, such as the use of historical sales data or current data from test markets. 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.

 

Collaborative Planning, Forecasting and Replenishment (CPFR, a trademark of the Voluntary Interindustry Commerce Standards (VICS) Association), is a concept that aims to enhance supply chain integration by supporting and assisting joint practices. CPFR seeks cooperative management of inventory through joint visibility and replenishment of products throughout the supply chain. Information shared between suppliers and retailers aids in planning and satisfying customer demands through a supportive system of shared information. This allows for continuous updating of inventory and upcoming requirements, making the end-to-end supply chain process more efficient. Efficiency is created through the decrease expenditures for merchandising, inventory, logistics, and transportation across all trading partners.

 

Demand forecasting is used to determine the number of products or services that will be purchased by consumers in the future. Numerous methods can be used when integrating demand forecasting into any business.

 

Most demand forecasting methods fall under four basic categories or methods –

1)      Quantitative,

2)      Qualitative,

3)      Time series methods

4)      Casual method.

 

Quantitative Methods: These methods forecast demand levels based on analysis of historical time series i.e quantities sold in the past to forecast how much will be sold in the near future. This is usually a forecast that will provide numbers for the next sales year. Some examples of quantitative forecasting methods include last period demand, multiplicative seasonal indexes, and simple and weighted moving averages. Each of these use quantities sold in different types of mathematical formulas to determine how many products or services will be sold at the same times in the future year’s sales that is being predicted.

 

Qualitative Methods: These methods rely on experts who try to quantify the level of demand from the available qualitative data.

The two most widely followed methods are:

  • Jury of execution opinion method:  Opinions of a group of experts is called for and these are then combined to arrive at the estimated demand.
  • Delphi Method: In this method a group of experts are sent questionnaires through mail. The responses received are summarised without disclosing the identities. Further mails are sent for clarification in cases of extreme views. The process is repeated till the group reaches to a reasonable agreement.

 

Time Series methods:  Demand forecasting typically does use strategies in the time series method to forecast the demand of products and services. The time series method can be split up into two different types of methods. These include frequency domain methods and time domain methods. Even though the frequency domain method is classified as a time series method, it is not based on time, but on frequency of the occurrence happening or a product being bought. Time domain will show quantities purchases with respect to time.

 

Casual methods. These methods work under the assumption that underlying incidents can affect sales numbers of products and services. Examples of casual methods include seasonal activities such as ice cream sales or sales of gardening products. These casual methods also may use linear relationships between sales and another components that remain consistent over time. If the linear relationship remains consistent, then it is a safe prediction.

 

Demand forecasting encompasses many types of methods and is not limited to those listed here. This forecasting helps those in businesses to determine projected quantities of products or labour needed to provide services for future sales. In addition, demand forecasting can be an effective tool for those new to certain business industries. These methods can assist in writing business plans and obtaining the funds needed to fund a new business venture.

 

Sales and Operations Planning (S&OP) provides an updated forecast that leads to a sales plan, production plan, inventory plan, customer lead time (backlog) plan, new product development plan, strategic initiative plan and resulting financial plan. Variations in frequency of the plan depend on the type of manufacturing industry. Short product life cycles and high demand volatility require a tighter S&OP planning than steadily consumed products

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