Archive for Demand Management

Demand Management Solutions Continue to Consume More and More Data!

There are a lot more demand forecasts being made today at companies then their used to be. Many of these forecasts depend upon having more data. Traditionally, demand management applications used order shipment history to make forecasts. But gradually new data sets were added that improved the forecasting accuracy. A demand management application can truly be a Big Data solution today.

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The Peril of Circular Reasoning in Machine Learning and Forecasting

Machine learning engines can take data on forecast accuracy and use that data to automatically improve the forecast model. However, three is a rub. Lost sales is a key piece of data on the accuracy of the forecast, but lost sales is generated with a demand forecast. This is circular reasoning. But that does not mean this analysis is without value.

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The Arms Race to Leverage Machine Learning in Supply Chain Planning

Artificial intelligence (AI) is hot.  Over $4 billion in venture capital has been invested in AI firms just in the US. But supply chain planning software companies, with their cadre of operations research Ph.Ds who have been modeling complex problems for decades, may be better poised to solve many complex business problems than the hot new Silicon Valley firms.

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Advanced Demand Management and Process Optimization at a Water Distribution Network in Brazil

A water purification company in Brazil can have the demand for their water treatment and sewage services increase as much as four times on a sunny day on a weekend.  To more accurately forecast demand, they count the number of vehicles driving into the community.  Demand analysis also relies on a forecast of weather conditions and historical tourism data. They are also prototyping IoT, Big Data, machine learning, and predictive analytics for process optimization.

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Robust Benchmarking of the Demand Management Process is Possible

Robust benchmarking is difficult. It is now possible to do robust benchmarking of the demand management process. That is much harder to do than you might think.

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Demand Management Applications Need to Be Flexible

Demand management solutions need to be flexible! Over time, companies often go on a journey where their forecast accuracy is improved by using more and more data and by forecasting at a more granular levels. Demand forecasting applications need to be able to support this journey.

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What Does Demand Sensing Teach Us About IoT Projects?

If demand management teaches us anything about learning to leverage the Big Data generated by sensors, it is that leveraging IoT data is likely to be a lengthy maturation process.

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Xilinx Outsources their Demand Management Process

Outsourcing is very common in supply chain management. But one thing very few companies outsource is demand management. In fact, until I talked to Lori Pouquette, the vice president of global customer operations at Xilinx, I had never heard of a company outsourcing demand management processes.

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Supply Chain Planning – Graduating From Demand Forecasting 101

I am currently updating ARC’s Global Supply Chain Planning (SCP) market study, as I stated in my LV post two weeks ago. The study divides the SCP market into four application functionality areas, one of which is demand management. Demand management applications offer a comprehensive set of functionality. They are used to organize, structure, manage and perform analysis on a large amount of data that is typically too unwieldy for spreadsheets. The analytical capabilities in […]

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The Toughest Forecasting Problem: Demand Management in Oil & Gas Industry

“Oil is becoming increasingly difficult and costly to recover, and the problem of managing the supply chain and profits has become more complex than ever. After weathering the economic downturn, the industry must boost capacity for future demand, and keep a close eye on the economics of oil and gas production.” So wrote my colleague Allen Avery, in a recent ARC Insight report titled “In an Uncertain Economy, Oil & Gas Industry Spending Must Stay […]

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