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Demand Sensing
Demand sensing is a demand forecasting method that uses data mining and real-time data capture to create a forecast of demand based on the current realities of the supply chain. Traditionally, forecasting accuracy was based on time series In mathematics, a time series is a series of data points indexed (or listed or graphed) in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time. Thus it is a sequence of discrete-time data. ... techniques which create a forecast based on prior sales history and draws on several years of data to provide insights into predictable seasonal patterns. Demand sensing uses a broader range of demand signals, (including current data from the supply chain) and different mathematics to create a forecast that responds to real-world events such as market shifts, weather changes, natural disasters and changes in consumer buying behavior. References Demand Supply chain analytics {{Business-st ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Demand Forecasting
Demand forecasting, also known as ''demand planning and sales forecasting'' (DP&SF), involves the prediction of the quantity of goods and services that will be demanded by consumers or business customers at a future point in time. More specifically, the methods of demand forecasting entail using predictive analytics to estimate customer demand in consideration of key economic conditions. This is an important tool in optimizing business profitability through efficient supply chain management. Demand forecasting methods are divided into two major categories, qualitative and quantitative methods: *Qualitative methods are based on expert opinion and information gathered from the field. This method is mostly used in situations when there is minimal data available for analysis, such as when a business or product has recently been introduced to the market. *Quantitative methods use available data and analytical tools in order to produce predictions. Demand forecasting may be used in resou ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Data Mining
Data mining is the process of extracting and finding patterns in massive data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information (with intelligent methods) from a data set and transforming the information into a comprehensible structure for further use. Data mining is the analysis step of the " knowledge discovery in databases" process, or KDD. Aside from the raw analysis step, it also involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating. The term "data mining" is a misnomer because the goal is the extraction of patterns and knowledge from large amounts of data, not the extraction (''mining'') of data itself. It also is a buzzwo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Supply Chain
A supply chain is a complex logistics system that consists of facilities that convert raw materials into finished products and distribute them to end consumers or end customers, while supply chain management deals with the flow of goods in distribution channels within the supply chain in the most efficient manner. In sophisticated supply chain systems, used products may re-enter the supply chain at any point where residual value is recyclable. Supply chains link value chains. Suppliers in a supply chain are often ranked by "tier", with first-tier suppliers supplying directly to the client, second-tier suppliers supplying to the first tier, and so on. The phrase "supply chain" may have been first published in a 1905 article in ''The Independent (New York City), The Independent'' which briefly mentions the difficulty of "keeping a supply chain with India unbroken" during the British expedition to Tibet. Overview A typical supply chain can be divided into two stages namely, produ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Time Series
In mathematics, a time series is a series of data points indexed (or listed or graphed) in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time. Thus it is a sequence of discrete-time data. Examples of time series are heights of ocean tides, counts of sunspots, and the daily closing value of the Dow Jones Industrial Average. A time series is very frequently plotted via a run chart (which is a temporal line chart). Time series are used in statistics, signal processing, pattern recognition, econometrics, mathematical finance, weather forecasting, earthquake prediction, electroencephalography, control engineering, astronomy, communications engineering, and largely in any domain of applied science and engineering which involves temporal measurements. Time series ''analysis'' comprises methods for analyzing time series data in order to extract meaningful statistics and other characteristics of the data. Time series ''f ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Demand
In economics, demand is the quantity of a goods, good that consumers are willing and able to purchase at various prices during a given time. In economics "demand" for a commodity is not the same thing as "desire" for it. It refers to both the desire to purchase and the ability to pay for a commodity. Demand is always expressed in relation to a particular price and a particular time period since demand is a flow concept. Flow is any variable which is expressed per unit of time. Demand thus does not refer to a single isolated purchase, but a continuous flow of purchases. Factors influencing demand The factors that influence the decisions of household (individual consumers) to purchase a commodity are known as the determinants of demand. Some important determinants of demand are: The price of the commodity: Most important determinant of the demand for a commodity is the price of the commodity itself. Normally there is an inverse relationship between the price of the commodity and ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
