From Predicting Demand to Prescribing Action: Operationalizing Prescriptive Analytics in the Enterprise

Combining Machine Learning (ML) and Operations Research and Management Science (OR/MS) allows for using big data to prescribe optimal decisions in daily operations. We explore the suitability of various Statistical Machine Learning techniques to predict outcomes, and a way to compute how effective variables are at informing optimal decision making. To demonstrate the power of this approach in a real-world setting we study an inventory management problem faced by the distribution arm of an international media conglomerate, which ships an average of 1 billion units per year to retail stores. We leverage both internal data and public data scraped from IMDb, Rotten Tomatoes, and Google to prescribe operational decisions that outperform baseline measures.

Nikki Hallgrimsdottir is a co-founder and Chief Evangelist of Algomus where she works with enterprises in the manufacturing, distribution, and retail sectors to leverage Artificial Intelligence and Data Analytics to transform their business. Nikki believes that pairing Human and Machine Intelligence is imperative to the growth and success of any company in a world of rapid change and technological innovation.

Nikki has worked for 10+ years helping companies effectively use automation technology, both hardware and software, previously holding positions with CST of America, Festo, and Keyence.  She knows enough to be dangerous in the areas of Big Data, Analytics, Artificial Intelligence, IoT Hardware, Machine Vision, Supply Chain Traceability, Industrial Automation, and Multiphysics Simulation to name a few.