- Data Categories
Agriculture Data 
B2B Data 
Biometric Data 
Company Data 
Conservation Data 
Demographic Data 
Economic Data 
Environmental Data 
Geospatial Data 
Healthcare Data 
Individual Data 
Industry-Specific Data 
Internet of Things (IoT) Data 
Legal and IP Data 
People and Employment Data 
Political Data 
Psychology Data 
Real Estate Data 
Retail & Commerce Data 
Social Data 
Space Exploration Data 
Sports & Entertainment Data 
Web Data
- Data Categories
- Agriculture Data
- B2B Data
- Biometric Data
- Company Data
- Conservation Data
- Demographic Data
- Economic Data
- Environmental Data
- Geospatial Data
- Healthcare Data
- Individual Data
- Industry-Specific Data
- Internet of Things (IoT) Data
- Legal and IP Data
- People and Employment Data
- Political Data
- Psychology Data
- Real Estate Data
- Retail & Commerce Data
- Social Data
- Space Exploration Data
- Sports & Entertainment Data
- Web Data
Supply Chain Management
How Is External Data Used in Supply Chain Management?
AI in supply chain management depends on road quality, distribution centers, weather, and the capabilities of suppliers and third parties. Monitoring and updating these data sources is therefore crucial for any operation.
Additional data includes foot and store traffic, future events, and competitor analysis. Competitor analysis, in particular, impacts product demand, forecasting, and new technologies that a company may consider utilizing themselves.
How are Machine Learning Models Used in Supply Chain Management?
Machine learning models can develop and run algorithms that predict product needs by individual stores and the best traffic routes. However, they do not limit themselves to making predictions; they can also analyze spending and vehicle status in order to reduce fuel and repair costs.
Which Companies Lead the Way in Building Advanced Analytics and Machine Learning Products in This Field?
IBM Sterling
IBM’s Sterling platform uses AI in supply chain management to optimize every aspect of the product journey. It also offers solutions to industry-specific problems with both transparency and security.
SAP Digital Supply Chain Management
SAP offers a suite of supply chain solutions, with IoT technology and predictive analytics via machine learning models. Additional services include warehouse management, a certified supplier network, and manufacturing capabilities.
Oracle Supply Chain Management (SCM) and Manufacturing
Oracle offers clouds solutions for supply chain management that integrate with its other business services. It also provides product trend and other supply chain-related predictive capabilities powered by AI.
Connected Datasets
PipeCandy eCommerce Leads & Insights for Fulfillment
PipeCandy eCommerce Leads & Insights for Fulfillment tracks company data and company shipping details: shipping volume, which companies they use to ship products, whether they ship internationally or not, and so on. You can find company leads easily with this dataset with filter capabilities.
Wikiroutes Transit Data
Wikiroutes Transit Data provides public transport information—routes, stop points, and more—via crowd-sourcing. The data is constantly updated and can be easily converted and integrated into your own software system.
Wikiroute’s Transit Data is used by individuals, private companies, and government agencies of all types and sizes.
TrackStar Predictive Credit Technology
TrackStar’s Predictive Credit Technology uses fifteen years of financial dispute data to create predictive models of future borrowing potential. With this data and AI technology, your bank or other lending company can mitigate the risk of fraud, improve existing customer relations, and reduce your operating costs.