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Brewing Solutions: Analytics at Milo’s Tea with Derek Camp
In this podcast episode, we sit down for a chat with Derek Camp from Milo’s Tea Company. Derek is the Senior Manager of Operational Analytics at Milo's Tea. Tune in as he shares his journey at Milo's, where he's grown from a replenishment analyst to leading a team of analysts across logistics, supply chain, operations, and quality.
Derek discusses how his team leverages data to drive efficiencies and improve decision-making. He also offers valuable insights on the practical applications of operations analytics, team collaboration, and overcoming challenges in scaling data efforts across multiple production sites.
In this episode you will learn:
⛛ How Derek's team uses analytics across logistics, supply chain, and production to drive operational improvements.
⛛ The value of cross-functional collaboration with subject matter experts for deeper problem-solving.
⛛ How Derek's team has scaled analytics efforts over time.
⛛ The importance of managing relationships with stakeholders and addressing pushback on analytics-driven suggestions.
Quote
💬 “If our team is doing these three things, we're doing our job really well: reporting, automating, and generating actionable insights.”
Featured in This Episode
Derek Camp, Senior Manager of Operational Analytics, Milo's Tea
Derek Camp is the Senior Manager of Operational Analytics at Milo’s Tea Company, bringing over a decade of experience in supply chain, sales, logistics, replenishment, and quality assurance analytics. Throughout his career at Milo's, he has held several key roles, including Supply Chain Analytics Manager and Senior Operations Analyst, playing an integral role in optimizing operational efficiency. Based in Birmingham, Alabama, Derek is a data-driven leader, passionate about leveraging analytics to drive business outcomes. A speaker at multiple conferences, Derek is always open to sharing his insights on operational analytics and supply chain optimization.
LinkedIn: linkedin.com/in/derek-camp
Evan Wimpey, Director of Analytics Strategy | Elder Research
Company website: elderresearch.com
LinkedIn: linkedin.com/in/evan-wimpey
Chapters
00:00 Intro to Milo’s Tea and Derek’s role in analytics
01:27 How data supports supply chain at Milo’s
05:41 The importance of communicating across teams
07:52 How to deal with pushback on data analysis
10:07 Evolution of data analytics at Milo’s Tea
13:19 The team composition at Milo’s Tea
15:59 Qualities Derek looks for in new team members
20:41 Derek’s dream project for the future
23:51 Wrapping up the show
Find more show notes, transcripts, & more episodes at:
www.elderresearch.com/resource/podcasts/
มุมมอง: 27

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ความคิดเห็น

  • @kevon217
    @kevon217 3 หลายเดือนก่อน

    Very cool quote. Graphs are king.

  • @kevon217
    @kevon217 3 หลายเดือนก่อน

    Nice analogy mom! Great, quick overview, thanks!

  • @emmanuelifeanyi3678
    @emmanuelifeanyi3678 3 หลายเดือนก่อน

    Thanks so much. I am currently working on this project and i hope to get more videos. Please. Do you have any material with respect to this particular video?

  • @jerkmeo
    @jerkmeo 3 หลายเดือนก่อน

    nice example. It looks like we need to "mine" the graph relations to find out abnormal relations. Is there any recommendation to do it at scale?

  • @mathieusherburne2607
    @mathieusherburne2607 3 หลายเดือนก่อน

    This was super interesting. Great job explaining your thinking.

    • @elderresearch
      @elderresearch 3 หลายเดือนก่อน

      Glad you enjoyed the video, Mathieu!

  • @LuckyBouncePickleball
    @LuckyBouncePickleball 4 หลายเดือนก่อน

    Super cool!

  • @jailynsusana7358
    @jailynsusana7358 5 หลายเดือนก่อน

    'Promosm'

  • @muslimahmukbang417
    @muslimahmukbang417 6 หลายเดือนก่อน

    how are you getting the numbers -0.05, 0.10 and so on?

    • @elderresearch
      @elderresearch 6 หลายเดือนก่อน

      Thanks for your question! Here's what Jericho had to say about how he got those numbers: Isolation forests use a large number of randomized attempts to separate the data and count how many cuts it takes in each attempt to separate each datapoint. From that collection of counts for each record, scores are calculated. Since this is not straightforward to show by hand, I used the scikit-learn Python package and the wine dataset to calculate the scores, limiting the wine dataset to flavonoids and malic acid features. Then I took some example points from the outer edges and one from the middle of the real results and illustrated them as closely as possible in the whiteboard example. --- Here are the links to the scikit-learn and Python resources: scikit-learn.org/stable/modules/generated/sklearn.ensemble.IsolationForest.html archive.ics.uci.edu/dataset/109/wine

  • @Bentley642
    @Bentley642 6 หลายเดือนก่อน

    Great video, explained in a very intuitive way!

    • @elderresearch
      @elderresearch 6 หลายเดือนก่อน

      Glad you enjoyed the video!

  • @RobertAllen-w6g
    @RobertAllen-w6g 8 หลายเดือนก่อน

    Good stuff.

    • @elderresearch
      @elderresearch 8 หลายเดือนก่อน

      Thank you! Glad you enjoyed the podcast!

  • @srem1971
    @srem1971 8 หลายเดือนก่อน

    That's a great explanation, thank you!

    • @elderresearch
      @elderresearch 6 หลายเดือนก่อน

      You're welcome! Glad it was helpful!

  • @JoshFairchild-q4p
    @JoshFairchild-q4p 8 หลายเดือนก่อน

    Great job, Marco!

  • @EricSiegelPredicts
    @EricSiegelPredicts 11 หลายเดือนก่อน

    Heck yes!

  • @elhairachmohamedlimam9640
    @elhairachmohamedlimam9640 ปีที่แล้ว

    Thank you a lot go ahead!

  • @anita2464
    @anita2464 ปีที่แล้ว

    So nice to hear about the path you took over the last 30 years Gerhard! And wonderful to see you!