This project offers a plug-and-play solution allowing retail analytics teams to forecast the demand of products over a period of time. With easy tailoring of the project through a Dataiku Application and the capacity to adjust the data flow to their needs, the Demand Forecast solution enables retail companies to optimize sourcing and production planning, inventory management, pricing, and marketing strategies, and much more. More details on the specifics of the solution can be found on the knowledge base. This solution is available on installed instances and Dataiku Online.
Business Overview
Predicting how your business will behave in the future, whether being short, medium or long term is hard.
Yet, it is critical for all companies to have the ability to forecast future trends in a reliable manner to answer a broad range of strategic questions – ie.:
- What will be the best sellers in 3 months?
- Why are the sales of some products declining?
- To which areas should the products be shipped to? In which quantities?
- How should I adjust my product purchasing strategy?
- Which marketing channels can help boost product purchases?
- Which discounts and special offers resonate with online visitors?
In order to answer those questions, companies should be able to plan for future trends: how? By having a reliable Demand Forecast set-up.
With this Dataiku Solution, use historical data and personalized sets of parameters (discounts, holidays, marketing events etc.) in order to predict consumption patterns at individual product level as well as what quantity and value this will amount to – and scale across locations, markets, products, with consistency for your whole book of business. With the Dataiku Solution for Demand Forecast, take a fast track to scaling this foundational ML application and quickly more to optimizing sourcing and production planning, inventory management, pricing and marketing strategies and much more.
Highlights
- Easily input required datasets: transactions, Products/SKUs as well as optional retail-specific data: seasonality, store locations, and online/offline events (e.g holidays, marketing etc.)
- Define your forecast settings through a user-friendly Dataiku App: forecast specifications (granularity, time horizon, lookback window), Products/SKUs feature engineering and calendar events feature engineering
- Forecast product sales during the beginning of their lifecycle (e.g new products) using cold start modeling
- Consume the output and forecast the demand of specific product categories or Products/SKUs through an interactive webApp and dashboards
- Rerun the entire data pipeline on new data using a simple application
- Automate the pipeline to rebuild with new/fresh data
Plug and Play with your own Data
Use the Dataiku Application to easily upload your data and adjust parameters to your needs. Flag products that are usually underperforming or which have irregular demand patterns in the Dataiku Application.
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Easily understand and adjust to needs
Thanks to the flow, review the project structure, navigate data transformation steps, and tailor to your specificities as needed.
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Interactive Dashboard For Evaluating, Interpreting Or Monitoring The Forecast Models
Analyze and understand the performances of the models and identify the most important variables. Compare your demand forecast model to other baseline models (e.g. cold start model). In addition, perform a seasonal clustering of your Products/SKUs.
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Look into the future
Build the Demand Forecast scenario of your choice and leverage the interactive webApp to project future sales of selected products. Leverage cold start modeling to forecast product sales during the beginning of their lifecycle.
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Automate the pipeline
Define your automation strategy and set up the full flow automation accordingly.
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