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Demand Forecasting
Case Studies
Demand Forecasting
Customer Detail
Problem Statement
Challenges
Industry - Chemicals (Fragrances and Flavours)
Location - India
The supply chain team was using traditional
methods of forecasting. They were generating a
huge error in their forecasting and production
planning and wanted a robust forecasting solution.
1) High number of SKUs.
2) Some external factors weren’t captured by the
team.
Technology
MySQL Qlik
Python
Django App
PyTorch
Solution
Business Impact
● Existing data from SAP and Tally of past 10 years of sales were
taken
● Data engineering, data cleaning, & missing data removal
● Identification of internal and external factors affecting sales
● Designing of Deep Learning model for forecasting using
combination of LSTM and other algorithms
● Creation and connection of dashboard with SAP to get
forecasting in real-time
The forecasting solution was able to forecast the peak and
downfalls for a duration of next 8 months accurately. The error rate
reduced by 10% from the traditional methods.
Our Methodology
Understanding
Requirements
Designing Solutions
Deployment
We understand your
business goals, and get
acquainted with all the
necessary details.
Our team of experts,
starts building solutions
to deliver your business goals.
Once complete
solutions is ready
then we deploy at
your core system.
1
2
3
Thank You
Chirag Tank
Co-Founder & CEO
Jitendra Purohit
Co-Founder & COO
+91 9820080751
+91 7021980537
chirag.tank@datenwissen.com
jitendra.purohit@datenwissen.com

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Demand Forecasting Case Study ppt - pdf

  • 2. Demand Forecasting Customer Detail Problem Statement Challenges Industry - Chemicals (Fragrances and Flavours) Location - India The supply chain team was using traditional methods of forecasting. They were generating a huge error in their forecasting and production planning and wanted a robust forecasting solution. 1) High number of SKUs. 2) Some external factors weren’t captured by the team.
  • 4. Solution Business Impact ● Existing data from SAP and Tally of past 10 years of sales were taken ● Data engineering, data cleaning, & missing data removal ● Identification of internal and external factors affecting sales ● Designing of Deep Learning model for forecasting using combination of LSTM and other algorithms ● Creation and connection of dashboard with SAP to get forecasting in real-time The forecasting solution was able to forecast the peak and downfalls for a duration of next 8 months accurately. The error rate reduced by 10% from the traditional methods.
  • 5. Our Methodology Understanding Requirements Designing Solutions Deployment We understand your business goals, and get acquainted with all the necessary details. Our team of experts, starts building solutions to deliver your business goals. Once complete solutions is ready then we deploy at your core system. 1 2 3
  • 6. Thank You Chirag Tank Co-Founder & CEO Jitendra Purohit Co-Founder & COO +91 9820080751 +91 7021980537 chirag.tank@datenwissen.com jitendra.purohit@datenwissen.com