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Advancing the Art of Pricing with Science
Companies in search of a better, more precise method to determine the best prices for their products and to meet their margins, should harness statistical

statistical  user enterprises can harness statistical science to analyze transactions and other customer data to more accurately explore the cause-and-effect relationship between prices and purchase decisions. The idea here is to be able to discern customers' willingness to pay, and set take-it-or-leave it prices where companies will make the maximum revenue. Using mathematical formulas and massive databases of sales records, companies can forecast their sales plans, and test pricing and demand elasticity under Read More...
Business Intelligence (BI)
Business intelligence (BI) and performance management applications enable real-time, interactive access, analysis, and manipulation of mission-critical corporate information. These applications pro...
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Documents related to » statistical


ToolsGroup-Going Back to Its SCP Roots
What has ToolsGroup, the expert in demand-driven SCP, been doing to address demand and supply variability? Read P.J. Jakovljevic’s article and see how

statistical  tail refers to the statistical property that a larger share of a population rests within the tail of an exponential probability distribution than observed under a “normal” (or Gaussian distribution), which is symmetrical in nature. In a vast majority of industrial sectors, planners have now to keep under control a much higher number of SKU locations, all characterized by a more volatile stochastic behavior, which is rather difficult to model. The typical “normal” (Gauss) distribution assumption Read More...
Predictive Analytics; the Future of Business Intelligence
Business intelligence (BI) is evolving as it grows in popularity. Within BI, there is a shift from traditional analytics to predictive analytics, and predictive

statistical  data is collected, a statistical model is formulated, predictions are made, and the model is validated (or revised) as additional data become available. Predictive analytics combine business knowledge and statistical analytical techniques to apply with business data to achieve insights. These insights help organizations understand how people behave as customers, buyers, sellers, distributors, etc. Multiple related predictive models can produce good insights to make strategic company decisions, like where Read More...
Teknetix Selects InfinityQS ProFicient
InfinityQS International, Inc., a provider of real-time manufacturing intelligence (MI) and enterprise quality software, today announced that Teknetix, Inc. has

statistical  implement process control and statistical process control (SPC) methodologies to improve product quality. Based in Parkersburg, West Virginia, with a 60,000-square-foot facility, Teknetix is a provider of assembly services to the mid-volume, high-mix original equipment manufacturer (OEM) electronic manufacturing market. InfinityQS’ enterprise quality hub, ProFicient, is powered by a centralized SPC engine. The manufacturing quality software, which can be deployed on premises and in the cloud, also leve Read More...
IBM SPSS-Making the World Smarter with Predictive Analytics
I recently had the opportunity to speak with IBM and take a closer look at the vendor’s SPSS product portfolio, some if its main functions and features, and how

statistical  information technology (IT) infrastructures. Statistical Product and Software Solutions, known simply as SPSS, was a dominant player in the software space for statistical analysis, predictive analysis, and data mining for more than 40 years, with the very first version released in 1968. The company competed with the likes of Fico, SAS, and Statsoft prior to acquisition by IBM in 2009. SPSS has since been a core element of IBM’s analytics strategy and has continued to evolve as a set of software applicat Read More...
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