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- What is supplychainpy?
- What is it For?
- What problem does supplychainpy Solve?
- What are the principles of supplychainpy?
Supplychainpy is a Python library for supply chain analysis, modelling and simulation. The library assists a workflow that is reliant on Excel and VBA. Supplychainpy provides APIs for modelling data for:
- Pareto Analysis
- Demand Planning
- Forecasting
- Recommendation Generator
- Monte Carlo Simulation
- Chat Bot
The library also contains a set of quick visualisations and reports to supercharge your analysis and gets the most out of a small set of data.
Many of the first modules developed were low hanging fruit. Supply Chain management is not only about inventory management and optimisation. There is every intention of implementing production scheduling and capacity planning, warehouse optimisation and logistics optimisation features (see roadmap for more details).
Big data tools are 'so hot right now' but many of the insights that can be made with a substantially smaller dataset are often left to bespoke spreadsheets.
Supplychainpy is a library for modelling and analysing data typically associated with operations and supply chain management. The library can be used with a data source like a Pandas DataFrame or a source file like '.csv'. At present '.csv' and pandas DataFrames are supported as sources.
Supplychainpy aims to get an analyst further into the analysis as quickly as possible by eliminating repetitive tasks, so an analyst can quickly start making decisions. Traditional enterprise tools do have some of these functionalities, however, these tools require company-wide integration and sometimes analysts need tools that assist their workflow and autonomy.
Initially, the library focused on the low hanging fruit:
- Inventory Management
- Demand Planning
- Forecasting
- Monte Carlo Simulation (modelling demand)
However, Supply Chain Management is a broad field of enquiry. Supplychainpy also aims to support some manufacturing, production and logistics computations.
Quite often Demand Planners, Buyers, Supply Chain Analysts and BI Analysts have to create their tools in Microsoft Excel for one reason or another. Supplychainpy aims to:
- Reduce the amount of repetition of common computations e.g. Pareto Analysis, Demand planning, Forecasting, Inventory planning.
- Alleviate the reliance on the spreadsheet.
- Provide a space for innovation and implementing advancements in the domain.