Bonduelle, the supplier in Europe for canned vegetables and second largest for frozen veg, is close to completion of a supply chain transformation project that has helped the manufacturer reduce wastage and predict with pinpoint accuracy what’s most likely to sell in different parts of the world, following the implementation of demand forecasting software through FuturMaster.
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.
Jun 26, 2019 Comments (0)
Stein Mart, a national specialty off-price retailer, has gained a holistic view of its inventory and a more streamlined approach to merchandise planning with Oracle Cloud.
FuturMaster launches new AI-powered forecasting software to help manufacturers and retailers more successfully launch new products
Jun 12, 2019 Comments (0)
FuturMaster, which provides supply chain planning software for clients including L’Oreal, Heineken and LVMH, is launching a new forecasting solution that uses artificial intelligence (AI) to help companies more successfully launch new products. A recent trial with a Chinese textiles firm found that the new tool, powered by AI, was more accurate in over three-quarters of forecasting scenarios......
Apr 24, 2019 Comments (0)
By Arnaud Gauthier, President & Chief Customer Officer, EMEA at Symphony RetailAI
The ability to quickly and accurately anticipate demand is essential for those who want to remain competitive in the retail industry, where even the slightest variation in production volume, distribution networks, or just the weather can have an immense impact on turnover.
Apr 16, 2019 Comments (0)
DynaSys, a leading provider of demand and supply chain planning solutions, has announced that the company will now be known as QAD DynaSys. QAD DynaSys is a division of QAD Inc.
Apr 03, 2019 Comments (0)
Eurilait, which supplies retailers, wholesalers and food service companies across the UK with cheese, butter, cream and desserts, has halved waste and saved a significant value in the last year following the implementation of supply chain planning software through food industry tech specialists at FuturMaster.
International jeweller and watch retailer Thomas Sabo chooses Quinyx as its workforce management platform
Dec 05, 2018 Comments (0)
Quinyx, the workforce management solutions provider, has entered into a new partnership with Thomas Sabo, the premium-sector jewellery and watch supplier.
Underwear apparel company Hanes rolls out FuturMaster demand planning software to boost global supply chain
Sep 05, 2018 Comments (0)
HanesBrands, the $6.5bn global apparel company that manufactures and sells a number of leading underwear and activewear brands including Wonderbra, DKNY, Playtex and Champion, is deploying a standardised IT system to help with supply and demand forecasting in more than twenty-five countries.
Dec 13, 2017 Comments (1)
The science of supply and demand is not always as clear cut as it may seem at first glance. The system of traditional forecasting is broken, and the only way to fix it is to replace it.
Aug 10, 2016 Comments (0)
DynaSys, provider of demand and supply chain planning (DSCP) solutions, has announced the general availability of DynaSys DSCP 2016, the latest version of the integrated DynaSys DSCP suite.
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 –
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