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Jul 19, 2018

Startups: Myth vs. Reality

Developing an innovative technology is the not-entirely-sane undertaking of any startup. The line is thin between visionaries and snake oil salesmen. Olivier Ezratty shares his views on the myth vs reality conundrum faced by startups.

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Probabilistic Forecasting for Supply Chains

Optimizing supply chains relies on having insights about the future. Classic forecasts dismiss uncertainty entirely, and assume that the forecast is perfectly known. In contrast, probabilistic forecasts embrace uncertainty, and reflect that supply chain optimization should remain robust when faced with unexpected events.

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Internet of Things for Supply Chains

For a supply chain management practice to be performant, managers need to have access to the position of every single asset. Unlike classic electronic inventory management, Internet-of-Things (IoT) offers the possibility to gain real-time visibility on all assets, vehicles included.

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Data Preparation in Supply Chain

Properly preparing the data is a requirement to achieve success for any data-driven initiative. When considering supply chain challenges, data preparation is difficult because it involves complex enterprise systems that have not been designed with data science in mind.

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Forecasting Promotions

Forecasting promotional demand is necessary in order to allocate the correct amount of stock. However, time-series forecasting models are typically not a good fit to address pricing-related demand patterns. More complex machine learning forecasting models are needed to properly take into account past promotions, and to reflect the upcoming impact of those that are planned.

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