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.

RSS

Being prepared - Planning & Forecasting report May 2011

Being prepared - Planning & Forecasting report May 2011

Manufacturing & Logistics IT spoke to a number of key spokespeople within the Planning & Forecasting vendor and process management community about the current talking points and key developments within to this mission-critical technology space.

Pernod Ricard drinks to Supply Chain success with Hughenden Consulting

Pernod Ricard drinks to Supply Chain success with Hughenden Consulting

Rmi Ameline, Supply Chain Planning Director at Pernod Ricard Group, spoke to Hugh Williams, Managing Director of Hughenden Consulting, about the company's Supply Chain education process

HMV UK selects TXT e-solutions to strengthen demand forecasting and replenishment processes

HMV UK selects TXT e-solutions to strengthen demand forecasting and replenishment processes

With a turnover of 1.1 billion, HMV UK is the leading specialist retailer in the UK and Ireland for music, DVD/video, computer games and related products.

Smarter system development: a systems engineering white paper from IBM

Smarter system development: a systems engineering white paper from IBM

Trade studies help us ensure that a proposed solution best meets conflicting performance and cost requirements. But many of us dont know that you can analytically and objectively conduct your trade studies well before you engineer anything.

An integrated approach to requirements and quality management

An integrated approach to requirements and quality management

This white paper outlines the many benefits of an integrated approach to requirements and quality management, as well as offer best practices for effective requirements-driven testing.

Create the forecasting and planning experience you want with DSX

Create the forecasting and planning experience you want with DSX

Manufacturing & Logistics IT spoke with Demand Solutions president Bill Harrison about the recent launch of DSX the companys new Supply Chain Planning software product.

BASF Orgamol plans and schedules its production with OMP Plus

BASF Orgamol plans and schedules its production with OMP Plus

BASF Orgamol Pharma Solutions SA has selected OMP Plus from OM Partners for the production planning of exclusive and generic Active Pharmaceutical Ingredients (APIs), advanced intermediates and fine chemicals.

Cathay Pacific Airways and JDA Software Embark on a Comprehensive Revenue

Management Project to Improve Cargo Business Profitability

JDA Software Completes Acquisition of i2 Technologies

strengthening market position with more than 6,000 global customers offering unparalleled supply chain optimization solutions spanning from materials to the consumer.

Manhattan Associates unveils first forecasting method for intermittent and seasonal demand

Carrying the right amount of inventory is a delicate balance for retailers, who must anticipate the demand for particular products based on seasonal and intermittent market trends throughout the calendar year.

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

Editorial: +44 (0)1892 536363
Publisher: +44 (0)208 440 0372
Subscribe FREE to the weekly E-newsletter