How Do I Enhance My Supply Chain Management System (SCM) With AI?
Building Intelligent Supply Chain Management Systems
In the age of Industry 4.0 and e-commerce, Supply Chain & Logistics has emerged as a strategic competitive advantage. The entire process of the supply chain has been revolutionized in the last decade with advancements in technology. The arrival of powerful Supply Chain Management Systems has also helped organizations in automating tasks, getting 360-degree visibility of the process and driving coordination between various components of the supply chain ecosystem. Data Science and Intelligence can further power Logistics & Supply Chain systems or software to enhance their capabilities and sync with evolving industry needs. In the supply chain and logistics, data science technologies like AI, Machine Learning, Computer Vision, etc., are proving to be a game-changer. According to a McKinsey report, businesses are expected to gain between $1.3tr and $2tr a year by leveraging AI only in their supply chains.
AI & Supply Chain- A Powerful Combo
With the digitalization of the supply chain process, enabled by IT and IoT, a supply chain software today generates and collects a vast amount of data. The challenge today is how businesses can best use the data residing on their supply chain management software. Data science technologies can help process this data and extract actionable data intelligence to provide new capabilities and features to a supply chain management system. A data-driven, smart supply chain management network can help businesses in-
- Predicting risks and taking proactive measures to minimize losses.
- Make supply chain automated and self-learning.
- Drive real-time coordination between various components of the supply chain network.
- Make data-driven decisions
- Drive innovation
How Can AI Help Your Supply Chain Management Software?
Data capabilities are not new to supply chain management systems. Most of the software today has some data analytics features embedded into it. However, AI goes much deeper to recognize patterns, induce self-learning and decision-making capabilities to a network. Here are a few ways AI can empower your Supply chain management system to influence every part of the entire supply value chain –
Planning
- Decision Making
- Risk Management
- Forecasting
- Demand Analysis
Sourcing
- Cost Modelling
- Budgeting
- Demand/Supply Balancing
Warehousing
- Space Optimization
- Asset Tracking
- Workload Optimization
- Resource Allocation
Logistics
- Route Optimization
- Delivery Scheduling
- Fleet Maintenace
- Energy efficiency
Stores
- Shelf Optimization
- Stock Optimization
- Product Mix
- Demand/Sales forecasting
Customers
- Fraud Detection
- Price Optimization
- Returns forecasting
- Damage forecasting
How Can Qualetics Help You Enhance Your SCM with AI?
Qualetics is our on-demand AI Management System (AIMS) Platform that can help Supply Chain software vendors quickly embed advanced Data Analysis methodologies into their product in a much simpler manner than traditional methods. Solutions in the market put the onus of achieving success with implementing AI & ML solutions on the Software Developers without realizing the cost overhead it introduces. Our platform and advanced APIs allow for easy integration of insights and data-based Intelligence into your Products & Systems to better serve you and your customer needs without breaking the bank.
In order to implement a seamless solution to analyze the data captured by your Supply Chain software, the following are key components that Qualetics offers-
Secure and stable Data Management
Qualetics has developed its proprietary data ingestion API that can transmit extremely high volumes of data. Our clients are provided with secure credentials and some specific configuration that allows data to be transmitted to the servers.
Data Virtualization to store, clean and transform vast amounts of data
Data ingested through our API is stored in high volume storage after going through several stages of transformation that involves data validation and deduplication. This will provide an in-depth understanding of the intrinsic value of the captured data and transforming it into information.
Data Analysis to identify features, build and train models
With the data securely stored in the storage layer, models that are designed and developed, specific to the incoming data structures are applied automatically to analyze the data in real-time and render the results to our output layer. Certain use cases require continuous analysis of historic data as well, which is conducted in the same system.
Data Delivery & Visualization platform
Results generated through the analysis layer are available through our dedicated customer portal which contains several features for viewing results such as filtering, sharing, subscribing to changes in data and also exporting the analyzed results into different formats, thus providing an opportunity to see hidden patterns.
In addition to a visualization platform, the portal also provides an API for developers who wish to integrate the visualizations or raw results natively into their applications. Doing so allows the developer to control the entire user experience of its users to the application features and advanced analytical results natively within a single client application.