None

 
 

Outline/Structure of the Experience Report

None

Learning Outcome

None

Target Audience

Data Scientist, Forecasters, Online Retailers

Prerequisites for Attendees

None

schedule Submitted 4 months ago

Public Feedback

comment Suggest improvements to the Speaker
  • Dr. Vikas Agrawal
    By Dr. Vikas Agrawal  ~  3 months ago
    reply Reply

    Dear Sushrut: Thanks for the proposal! I wonder if you could please add a link to a previous talk video or an introduction to this topic as a video attached or linked to this proposal. Warm Regards, Vikas

    • Sushrut Kulkarni
      By Sushrut Kulkarni  ~  3 months ago
      reply Reply

      Hello Vikas,

      Thanks for the reply. I don't have any recordings of the presentation. if required i need to record it. 

      Pls let me know if an audio record is enough or i need to to video record it.

      Thanks & Regards,

      Sushrut.

      • Naresh Jain
        By Naresh Jain  ~  3 months ago
        reply Reply

        Sushrut, we surely need a video recording.

        • Sushrut Kulkarni
          By Sushrut Kulkarni  ~  2 months ago
          reply Reply

          Hello Naresh, 

          Apologize for late reply.

          Pls find the below link for the video.

          https://photos.app.goo.gl/fQ7V79nvzKsnt4Ri9  

          Thanks & Regards,

          sushrut

           

          • Naresh Jain
            By Naresh Jain  ~  2 months ago
            reply Reply

            Thank you for the video. Would it be possible to compress this into a focused 20 mins experience report? If yes, please update the proposal and the outline accordingly. Also, please provide the time-break up for the topics listed under the outline section.

            • Sushrut Kulkarni
              By Sushrut Kulkarni  ~  2 months ago
              reply Reply

              Hello Naresh,  thanks for the reply.  However,  I couldn't understand what do you mean by compress it to 20 mins?  Is it breaking the report in to 20 mins presentation? 

              • Naresh Jain
                By Naresh Jain  ~  2 months ago
                reply Reply

                Yes, that's right. Can you please see if you can reduce the time to 20 mins for this presentation? Currently we don't have 45 mins slots left in the schedule.


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      Aswin Nair / Raj Mohan - Attribute Based Component Forecasting for High Technology Industry using Machine Learning

      45 Mins
      Case Study
      Intermediate

      The Personal System Business Unit, the flagship unit of HP Inc, is powered by some of the most innovative technologies in the industry and has consistently delivered exceptional results. However, the business has been plagued with recurring shortages and over stocking of slow-moving SKUs & Components owing to poor forecast accuracy. The current forecasting framework uses conventional forecasting methods and basic time series models to arrive at the baseline forecast. This approach works well for certain segments and regions with high predictability and noticeable seasonality but fails for areas with erratic demand and weak seasonal behavior. This created a need for HP to develop a robust forecasting approach/framework to improve the accuracy. In this paper, we propose “Attribute based forecasting framework”, a multi model solution, which uses techniques like Text Analytics, Decision Tree, Random Forest, Support Vector Machine and Artificial Neural Networks in building the prediction models.