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Jun 20, 2018

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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May 31, 2018

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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May 23, 2018

The User Experience Paradox

Supply Chain Management (SCM) systems feature complex user interfaces. Among them, demand forecasting subsytems are not only complex but complicated as well. Better user inferfaces are needed to tackle this complexity.

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May 2, 2018

The Data Scientist in Supply Chain

Supply chain challenges are frequently quantitative and data driven. This makes them a good fit for a data science practice. However, understanding the business is a frequently overlooked aspect of the data science practice in supply chain.

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Apr 17, 2018

Artificial Intelligence

Artificial Intelligence (AI) is an umbrella term that covers many high-dimensional statistical methods such as Deep Learning or Differentiable Programming. These methods can be used in various ways to improve the operational performance of supply chains. However, both problems and solutions differ vastly from mainstream AI problems such as Natural Language Processing (NLP).

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