Modern supply chain analytics is more than just KPIs and aggregations, and more advanced statistical approaches such as inventory optimization, production scheduling, segmentation, and forecasting can drastically cut costs and increase efficiency.
But how many supply chain teams have a robust data stack and team to deliver internal data products which deliver these insights? More often than not, they find themselves stuck between legacy Business Intelligence platforms and point solutions, which are inflexible, uncustomizable, and slow and expensive to integrate. Instead of creating statistically-backed reports and insights which drive value, they are waiting for central IT to integrate data into 90s-era software.
Python and the wider open-source ecosystem provides the most powerful and flexible way to analyze data, and is the best solution for answering complex questions from supply chain datasets, but is inaccessible to end-users and impossible for teams to operationalize.
The NStack Platform bridges this gap by providing everything modern supply chain analytics teams need to build internal supply chain analysis products.
- Integrate with supply chain platforms and internal data sources such as files and warehouses
- Choose from a rich library of pre-built supply chain analytics modules which can be customised in Python -- or build your own from scratch using your favorite libraries and tools
- Programmatically build ad-hoc or automated reports which can be shared directly with non-technical end-users
- Create self-service interactive web applications with forms, dynamic inputs, and file uploading
- Automate and surface reporting through email, Slack, and Teams
Result: Supply Chain teams are empowered to build and operationalize advanced data applications which can be consumed by the entire company and make an outsized impact.
Example Reports and Metrics
- What will be the demand for my product in the next quarter based on historical sales data?
- How will an upcoming holiday or event affect the demand for my products?
- How does customer behavior impact the demand for different products?
- What is the impact of external factors like economic indicators or weather patterns on product demand?
Supply Chain Optimization:
- How can I identify and resolve bottlenecks in my supply chain?
- What are the most efficient transportation routes for my products?
- How should inventory be distributed across my various warehouses for maximum efficiency?
- Can the packing process be optimized to save time and resources?
- What are the potential risks and disruptions that could affect my supply chain?
- How might delays in raw material supply impact my production schedule?
- How can I prepare for a sudden increase in demand for my products?
- What strategies should I have in place to deal with unforeseen events like natural disasters affecting my supply chain?
- How can I predict future customer needs based on past behavior?
- How should I adjust my supply chain operations to ensure popular items are always in stock?
- How can I ensure on-time delivery of products to enhance customer satisfaction?
- How can I reduce the carbon footprint of my supply chain operations?
- What are the optimal routes for transportation to minimize fuel consumption?
- How can I ensure my suppliers are adhering to sustainable practices?
- How can I detect defects in my production process early?
- How can I use predictive models to improve the quality of my final product?
- What strategies can be implemented to reduce waste in the production process?
- How can I adjust product prices based on fluctuating demand?
- How should prices change based on the season or upcoming events?
- What strategies can be used to stay competitive in pricing while maximizing profits?
Data and Integration
Unrestricted by proprietary connectors, NStack's data layer can connect to any internal database, data warehouse, file, or directly into systems of record such as:
- Microsoft Dynamics
- Zoho CRM
- SAP Ariba
- Oracle SCM Cloud
- Infor SCM
- JDA TMS
- Oracle Transportation Management
- Manhattan WMS
- SAP EWM
- Oracle WMS