Demand forecasting mistakes in the retail industry

Dec 27, 2018  |  4 min read

Consumer goods companies rely on forecasts to support inventory planning and distribution across their sales channels. Building accurate demand forecasts requires more than just an understanding of the latest machine learning techniques; it also requires the right data and an understanding of the potential costs of incorrect estimates.

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Shared supply chain control towers: Key features and considerations

Dec 20, 2018  |  3 min read

As we join the year end recap bonanza, we can’t miss one of our highlights of 2018: a joint Professional Development Event with the APICS Golden Gate chapter. We welcomed members and guests to our San Francisco office in November to discuss “Implementing a Shared Supply Chain Control Tower."

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An interview with Amelia Hardjasa, Engineering

Dec 12, 2018  |  4 min read

Amelia Hardjasa is a Data Engineer in Alloy's Vancouver office. Previously, she has worked as a data scientist at several different companies, including Boeing Vancouver and Pulse Energy. She holds an MSc from the University of British Columbia.

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Webinar recap: Uses and best practices for end-customer demand

Dec 5, 2018  |  3 min read

In October, Alloy was a featured guest on a webinar hosted by APICS Atlanta and Supply Chain Now Radio, “The Power of Connecting to End-Customer Demand.” Through the presentation and Q&A, we defined downstream demand, why it’s important, and how brands can efficiently use this data to their advantage. You can find the full recording of the webinar here, but here’s a quick summary of the key points

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Choosing the “right” demand forecasting model

Nov 28, 2018  |  5 min read

When building demand forecasts for your supply chain, there’s a variety of algorithms you can use, from longstanding best practices to cutting-edge methodologies. While each have their pros and cons, at their core, every method is ultimately using historical data to try to predict future demand. The complexity, assumptions, and types of data inputs used in a given model type — and how they are weighted — will vary, but the basic ingredients are similar across the board.

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An interview with Nick Singarella, Sales

Nov 14, 2018  |  4 min read

Nick Singarella is an Account Executive in Alloy's SF office

He’s originally from Southern California and went to college at NYU (go Violets!).Taking advantage of NYU’s international campuses, Nick lived in both Florence and Buenos Aires while studying international politics. After graduation, he worked in the Los Angeles District Attorney’s office and in finance before making his way to San Francisco with the goal of entering the tech sector. Nick found his way into the industry through sales, and worked at Wiser (e-commerce analytics) before joining Alloy.

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