6 Data Science Technologies You Need to Build Your Supply Chain Pipeline
Here are some of the data science technologies needed to build a comprehensive and smooth supply chain pipeline.
A supply chain pipeline is a combination of different processes to produce and distribute products and services to customers. There is a wide range of activities that flows through the supply chain. The diagram below shows a bird’s-eye view of a supply chain pipeline:
Image by the author
Companies worldwide are working continuously to increase efficiency in the supply chain pipeline to satisfy customers by providing value. This can be achieved through data science by making data-driven judgments and decisions. According to this post, employees spend over 100 million hours per year on phone calls and emails to move data back and forth between their trade partners, costing nearly $2B to UK companies. This vast amount of wasted hours can be reduced by automating communication using technology. Here are some of the data science technologies needed to build a comprehensive and smooth supply chain pipeline.
1. Big Data
To be able to make data-driven decisions, you need data. This data can be structured, unstructured, or semi-structured, which is either machine or human-generated. But where does this data come from? It could be sensor data generated from weather stations, ships, and containers.
To build a solution for big data to get valuable insights, consider the following four areas:
- Volume: The amount of data that is being generated e.g., 100 petabytes/year, 500 terabytes/month
- Variety: The types of data are being generated e.g., text, image
- Velocity: The frequency of data that needs to process and stored pro e.g. 1000 images/minute or 4000 gigabyte/minute
- Veracity: The quality of the data that is being generated.
Once you have covered these four areas, you can use a cloud-based solution to process, store and analyze the data. For example, Amazon Simple Storage Service (Amazon S3) can store data that is scalable, secured, and efficient. After that, you can plug these data sources into other services such as Amazon QuickSight to create interactive Business Intelligence dashboards. There are other cloud providers and services which offer similar products. Companies can choose a service provider depending on the existing technology, which will help them with easier integrations.
2. Machine Learning
You can use big data and add layers on top of it to create valuable insights which can be translated into actions. By using machine learning and artificial intelligence, you can increase customer satisfaction by showing relevant products. On the other hand, you can use prediction algorithms to forecast customer demands. Also, the forecast data can help automate warehouse operations to increase the inventory turnover rate.
This way, companies can compete with other businesses and introduce new products into the market quickly. Finally, supply chain manager can plan and act on these predictions and forecasts and make mission-critical decisions to increase the growth of the business.
The Internet of Things, most commonly known as IoT, helps companies increase visibility by providing more control over their operations. Real-time decisions can be made when you tag items using IoT sensors. For example, a business can track and monitor ships and re-route them based on traffic to make a reliable and faster transit, which will help reduce shipping delays. Moreover, companies can avoid losing money by monitoring temperature data from refrigerated shipping containers in the case of technical malfunction.
IoT can add reliability to the supply chain pipeline. Companies can easily track missing or misplaced containers to process disputes faster. Businesses can add value to the customers by giving them real-time updates about the products they have purchased.
4. Cloud computing
Cloud computing allows businesses to deploy their supply chain pipeline software such as Customer relationship management (CRM). The benefits of cloud computing are endless. They can scale up depending on the traffic. Also, based on the Service Level Agreements (SLAs), the applications will have guaranteed uptime (high availability). Cloud platforms such as AWS makes their services reliable, secure, and cost-effective. Moreover, the pay-as-you-go model helps businesses save money.
Not only customer-facing applications, but businesses can also deploy other applications to track and monitor inventory systems. Also, BI dashboards can increase visibility across companies.
Businesses can integrate with other third-party vendors to provide services like authentication (auth0), SMS (twilio), analytics (powerbi), messaging (intercom), documentation (confluence), etc.
6. Frameworks like React
If your business has multiple software teams working on the application, they can build micro front-ends with module federation instead of a monolithic application. It will provide complete freedom to design and build independently without breaking the whole application. For example, N number micro front-ends can serve services like tracking, analytics, authentication, reports, etc.
As technology has improved, SCPs have adopted some of the cutting-edge techs to optimize and strengthen the pipeline that pretty much every human being relies on. These six technologies, once novel, are now a critical part of supply chain pipelines. Supply chain managers should look into these data science technologies and start integrating them sooner than later. It will help businesses to make an efficient and cost-effective supply chain pipeline and increase customer satisfaction.
Zulie Rane is a freelance writer and coding enthusiast.