During the pandemic, the foundations on which retailers, brands and Consumer Products companies rely to determine trade volumes, pricing and promotions have been shaken and, in some cases, broken.
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.
Jul 06, 2020 Comments (0)
May 13, 2020 Comments (0)
Blue Yonder has announced that capital goods company CNH Industrial has selected Luminate Control Tower, along with several supply chain planning solutions such as forecasting and replenishment, as the backbone of its customer-centric aftermarket supply chain for its parts business.
Dec 12, 2019 Comments (0)
Tuesday 14th January 2020 - Birmingham,UK
This Supply Chain Event is a free educational morning dedicated to leading manufacturers who want to review best practices and lessons from the front line to implementing S&OP (Sales & Operations Planning) and IBP (Integrated Business Planning).
Dec 11, 2019 Comments (0)
The latest demand and supply chain planning software features a new intuitive web planning experience, collaborative planning process controls and is powered by artificial intelligence and advanced supply chain analytics
Nov 29, 2019 Comments (0)
REGISTER for Webinars - 10th & 12th December.
Businesses that manage supply chains have to be able to adapt to the changing political, economic, social and technology landscape all the time.To cope with all this change globally, companies need to put together a different business operating model, which allows them to continuously update plans in a controlled manner in the light of changing economic circumstances.
QAD DynaSys recognised as a major player in the IDC MarketScape Worldwide for Supply Chain Demand Planning 2019 vendor assessment
Nov 20, 2019 Comments (0)
This research is a quantitative and qualitative assessment of the characteristics that explain a vendor's success in the supply chain demand planning space and helps assess its current and anticipated performance in the marketplace.
Oct 18, 2019 Comments (0)
November 05 - 06, 2019.
QAD DynaSys is bringing two days of Demand & Supply Chain Planning thought leadership to your office. Hear manufacturers’ success stories and feedback, best practices, supply chain development narratives, and more on S&OP / IBP, Machine Learning, Advanced Analytics, DDMRP, DDS&OP, etc.
Oct 16, 2019 Comments (0)
Fleury Michon, one of France’s leading food suppliers to supermarkets, healthcare facilities and airlines, has implemented forecasting technology from FuturMaster to help anticipate future demand and the daily production requirements for its cold meats, ready meals and snacks.
Sep 04, 2019 Comments (0)
Haribo, the European manufacturer of sweets including jelly babies, gum bears and liquorice, has 19 production sites and 10 distribution centres around the world.
QAD DynaSys recognised as a challenger in Gartner 2019 Magic Quadrant for Sales and Operations Planning Systems of Differentiation
Aug 28, 2019 Comments (0)
QAD DynaSys, provider of demand and supply chain planning solutions, has announced that Gartner, Inc. has named QAD DynaSys a Challenger in Gartner’s May 2019 Magic Quadrant for Sales and Operations Planning Systems of Differentiation. QAD DynaSys is a division of QAD Inc.
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