How data science can enable better demand forecasting and planning

| August 3, 2018

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In a previous post, we talked about how tough it can be to get the various parts of a business — operations, sales, finance, etc. — to “sing in harmony” to achieve better demand forecasting and planning. It’s like getting a group of singers to perform together with each one singing the right part, at the right time, in the right key. Using a mix of advanced analytics tools, backed by machine learning, is crucial for achieving that. But let’s extend the metaphor: if those singers are joined onstage by an orchestra, who supplies the instruments and keeps them in tune? Answer: the data science team. Data science duties for better demand forecasting and planning. Whether they work within a line of business or as a standalone, centralized function, data science teams are responsible for making sure that internal customers can optimize demand planning and forecasting. That applies no matter which data sources are used — even when the data is siloed, and regardless of whether it lives on-prem, in the cloud, or both. Oh, and it all must be done while explicitly demonstrating adherence to any requirements for security or regulatory compliance.

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Data IQ Argentina

Dedicated to Business Intelligence Solutions, Data IQ is composed of experts in the areas of strategy, sales, information technology and marketing, who share one objective: Satisfying the Customer. First-line companies such as La Caja, Fernet Branca, Coca Cola, Roche, Los Grobo, Cargill, MSD, OSDE and Pfizer, among others, have already proven why QlikView's "in memory" technology, implemented by Data IQ, allows speed up the time of information processing. Since 2006, Data IQ is a QlikView Master Reseller for Argentina, Uruguay and Mexico, and one of the fastest growing companies in the market, with a remarkable ability: "Implementing Business Intelligence in a quarter of the time that would lead to other options of the market, half the price and generating double the value. "

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