What is the most popular demand planning software?

Jan 15, 2019  |  5 min read

Given how important demand planning is for consumer goods makers, you’d think teams are using really advanced tools for it, right? Especially in consumer electronics, where many of the companies are based in Silicon Valley and are pushing the boundaries of technology in their own products.

Late last year, Kristin Markworth, one of Alloy’s strategic advisors, set out to help us research this hypothesis, and the result was surprising, if not unexpected. Kristin is a 20+ year veteran in consumer electronics, and was most recently the VP of Sales and Sales Operations at GoPro, where she had gone on her own journey implementing planning processes and tools. To answer this question, she met with demand planners at a half-dozen consumer electronics companies, from Fortune 100 brands to digital-native upstarts, and heard a consistent story at each.

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Managers Club interview with Evan Goldenberg, CTO at Alloy

Jan 14, 2019  |  5 min read
This series asks engineering managers to share their experiences with the intent of helping other engineering managers learn and improve.

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Announcing intelligent demand forecasting

Jan 8, 2019  |  4 min read

We’re thrilled to be starting off the year at Alloy on an exciting note by announcing the release of our new intelligent demand forecasting capability. Powered by the granular sales and inventory data gathered into our platform, this feature allows brands to continuously forecast demand using the most up-to-date and consumer-driven information available. Our customers have found it helps them more quickly respond to consumer demand — minimizing lost sales due to out-of-stocks, preventing losses from overstocks, improving overall customer service levels, and growing sales.

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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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