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432: Discover the Future of Forecasting, with Manhattan Associates

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Manage episode 447224698 series 2108400
Inhalt bereitgestellt von Sarah Barnes-Humphrey. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Sarah Barnes-Humphrey oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

Jeff Beadle of Manhattan talks about their Unified Forecasting Method; how the hybrid approach is different; & the benefits to supply chain planning.

IN THIS EPISODE WE DISCUSS:

[06.28] An introduction to Jeff, his role at Manhattan, and how, as a physicist coming from a job at the “applied chaos lab,” he found his way to supply chain.

“As a data scientist, there’s not a better sandbox than supply chain – and especially at Manhattan, given the breadth of solutions we have across the space.”

[09.10] Why unification is key to both Manhattan’s approach to helping clients and to improving the industry; and its importance in forecasting.

“By unifying demand forecasting methods into a single composite model, it elevates capability, robustness, adaptability, and accuracy – and therefore all of the optimization of supply chain processes, and applications that are consuming that output.”

[12.32] An overview of UFM, how its hybrid forecasting approach differs from more traditional statistical models and standalone machine learning models, and why Manhattan have combined these approaches into one model.

“Hybrid forecasting combines statistical time series models with machine learning algorithms offering a uniquely powerful and balanced approach to demand forecasting.”

[17.38] The challenges with machine learning, and the benefits that UFMs hybrid approach brings to supply chain planning.

“There are still shortcomings to machine learning, and high failure rates… Machine learning builds knowledge strictly from the data it observes. So if it has an incomplete aspect of the data model… it can lead to misleading results.”

[23.56] How UFM allows organizations to make decisions that have benefits across all business areas.

“That combined hybrid approach takes on an inside-out, outside-in demand planning approach… this provides a very adaptive, accurate mechanism… and that impacts all cross-functional processes.”

[27.07] An overview of how UFM continuously learns and updates its forecasts in real-time.

[30.07] The low-management nature of UFM, and how that frees up teams to take on the more strategic and creative work.

“It’s very autonomous and hands-free – it doesn’t require special staffing or oversight.”

[33.30] The ideal client for Manhattan’s UFM.

“The better plans and forecasts we have, the less we have to react through execution systems – that’s sub-optimal. You want a better plan, a better projection, and the more accurate and tighter that is, the better the overall downstream impact.”

RESOURCES AND LINKS MENTIONED:

Head over to Manhattan’s website now to find out more and discover how they could help you too. You can also connect with Manhattan and keep up to date with the latest over on LinkedIn, YouTube, Facebook and X (Twitter), or you can connect with Jeff on LinkedIn.

If you enjoyed this episode and want to hear more from Manhattan, check out 430: Unify Your Supply Chain Systems, with Manhattan Associates.

  continue reading

492 Episoden

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iconTeilen
 
Manage episode 447224698 series 2108400
Inhalt bereitgestellt von Sarah Barnes-Humphrey. Alle Podcast-Inhalte, einschließlich Episoden, Grafiken und Podcast-Beschreibungen, werden direkt von Sarah Barnes-Humphrey oder seinem Podcast-Plattformpartner hochgeladen und bereitgestellt. Wenn Sie glauben, dass jemand Ihr urheberrechtlich geschütztes Werk ohne Ihre Erlaubnis nutzt, können Sie dem hier beschriebenen Verfahren folgen https://de.player.fm/legal.

Jeff Beadle of Manhattan talks about their Unified Forecasting Method; how the hybrid approach is different; & the benefits to supply chain planning.

IN THIS EPISODE WE DISCUSS:

[06.28] An introduction to Jeff, his role at Manhattan, and how, as a physicist coming from a job at the “applied chaos lab,” he found his way to supply chain.

“As a data scientist, there’s not a better sandbox than supply chain – and especially at Manhattan, given the breadth of solutions we have across the space.”

[09.10] Why unification is key to both Manhattan’s approach to helping clients and to improving the industry; and its importance in forecasting.

“By unifying demand forecasting methods into a single composite model, it elevates capability, robustness, adaptability, and accuracy – and therefore all of the optimization of supply chain processes, and applications that are consuming that output.”

[12.32] An overview of UFM, how its hybrid forecasting approach differs from more traditional statistical models and standalone machine learning models, and why Manhattan have combined these approaches into one model.

“Hybrid forecasting combines statistical time series models with machine learning algorithms offering a uniquely powerful and balanced approach to demand forecasting.”

[17.38] The challenges with machine learning, and the benefits that UFMs hybrid approach brings to supply chain planning.

“There are still shortcomings to machine learning, and high failure rates… Machine learning builds knowledge strictly from the data it observes. So if it has an incomplete aspect of the data model… it can lead to misleading results.”

[23.56] How UFM allows organizations to make decisions that have benefits across all business areas.

“That combined hybrid approach takes on an inside-out, outside-in demand planning approach… this provides a very adaptive, accurate mechanism… and that impacts all cross-functional processes.”

[27.07] An overview of how UFM continuously learns and updates its forecasts in real-time.

[30.07] The low-management nature of UFM, and how that frees up teams to take on the more strategic and creative work.

“It’s very autonomous and hands-free – it doesn’t require special staffing or oversight.”

[33.30] The ideal client for Manhattan’s UFM.

“The better plans and forecasts we have, the less we have to react through execution systems – that’s sub-optimal. You want a better plan, a better projection, and the more accurate and tighter that is, the better the overall downstream impact.”

RESOURCES AND LINKS MENTIONED:

Head over to Manhattan’s website now to find out more and discover how they could help you too. You can also connect with Manhattan and keep up to date with the latest over on LinkedIn, YouTube, Facebook and X (Twitter), or you can connect with Jeff on LinkedIn.

If you enjoyed this episode and want to hear more from Manhattan, check out 430: Unify Your Supply Chain Systems, with Manhattan Associates.

  continue reading

492 Episoden

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