Enabling Supply Chain Innovation with Emerging Technology
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Posted by Harry E Fowler
- Last updated 11/09/20
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At COLLABORATE 19, Vikash Goyal, Vice President of Product Strategy for Oracle SCM Cloud Applications, spoke about how to enable supply chain innovation with emerging technology – including the Internet of Things (IoT), machine learning, blockchain, and digital assistants.
Today’s Accelerating Pace of Change
The image below shows the current capability gap between the ability to respond and the pace of change in the business world today.
The need to create supply chain innovation today is accelerating. Currently, the capability gap is growing larger as the pace of chain increases at a drastically higher pace than technology’s ability to respond. Digital supply chain looks to address this issue.
Overall, 76 percent of supply chain officers say that their digital transformation projects are not aligned. Additionally, 84 percent of organizations say that AI is the key to getting a competitive advantage, and 58 percent of industrial companies say that IoT is a strategic part of their digital transformation.
The Solution: Supply Chain Innovation
What has been acquired in response to these issues in order to enable the digital supply chain, first of all, is an interconnected set of capabilities:
- Digital innovation to commercialize
- Lead to cash for the digital age
- Unified supply chain planning
- Connected smart factory
- Integrated shipping and logistics
- Digital source to settle
Together, all of these capabilities allow network visibility, asset monitoring, production monitoring, fleet monitoring, remote logistics, real-time analytics, predictive models, tracking and detection, and digital field service. The focus will be supply chain innovation enabled by disruptive technologies in the Cloud.
Current supply chain challenges that these capabilities aim to face include:
- Customer service
- Short production introduction cycle
- Supplier and partner management
- Cost control
- Planning and risk management
- Safety, quality, and compliance
Enabling Supply Chain Innovation with Emerging Technology
Emerging Technology No. 1: Internet of Things
IoT-enabled supply chain management (SCM) applications include:
- Asset Monitoring: Monitor assets, their health, utilization & availability
- Production Monitoring: Manufacturing equipment & production line monitoring & prognostics
- Fleet Monitoring: Monitor shipments, fleet vehicles, driver behavior, and costs
- Connected Worker: Enhance worker safety through monitoring of workers and environment
- Service Monitoring: Automate asset monitoring and customer service to enhance customer experience
The IoT Asset Monitoring Cloud Service is a continuous monitoring of asset health and location for fault detection and performance monitoring. It is pre-integrated with Oracle Maintenance Cloud and Oracle E-Business Suite EAM. It also has the ability to integrate with other apps.
Real-time, custom dashboards in IoT Asset Monitoring Cloud provide packaged templates to quickly create dashboards that show live visualization of asset data and relevant key performance indicators (KPIs). Sensor data points can be visualized in the following modes:
- Live for streaming data
- Last one hour
- Last 24 hours
- Last one week
- Last 30 days history
Support will be added to display data for the custom time period. The system has machine learning, which detects anomalies. They are auto-detected in sensor data and shown visually in the Anomalies section under the Operations Center. Predictions for faults and failures for assets are displayed in the Predictions section under Operations Center.
Digital thread means connected maintenance. For example, IoT Asset Monitoring Cloud predicts failures to automatically generate a service ticket in Maintenance Cloud. The Maintenance Cloud user then initiates action based on the details of the service work order.
Another example of digital thread is connected transportation – the connected nature of supply chain management and IoT applications is evident in the ability to plan shipments Oracle Transportation Management. Here, the user can also track a shipping status. Planned shipments are automatically imported into IoT Fleet Monitoring and appear on the map dashboard. Shipments are tracked in real-time and predict delays. Status events and route deviations are automatically sent to Oracle Transportation Management. This gives the user the ability to take action, like informing the customer, if the shipment is late.
Emerging Supply Chain Innovation Technology No. 2: AI
Current artificial intelligence (AI) is reshaping how business is conducted – from how we interact with customers to how we create new goods and services. With its smart, personalized engagements and insightful recommendations, AI has altered how we operate business in general.
Machine learning requires several skill sets. It requires an individual who understands the business and has the ability to code. It also requires a data scientist.
There are three areas in which Oracle utilizes machine learning:
- Ready-to-Go: AI-powered apps in SaaS suite for business teams
- Ready-to-Build: AI data science platform to build and manage AI-powered solutions
- Ready-to-Work: Embedded AI in Oracle Autonomous Databases
AI has become an integral part of software as a service (SaaS). It incorporates data science, domain expertise, and application development. In fact, it is the easiest way for business users to benefit from machine learning. It is purpose-built, ready-to-use, and fully application integrated.
With embedded machine learning and decision science, AI has the capability to provide recommendations with improvements over time and connect intelligent outcomes across separate functions.
Multi-functions of AI include:
- Data preparation
- Data normalization
- Analytical model selection
- Feature selection
- Model tuning
- Hyper-parameter optimization
- Integration
- Accuracy tracking
Built-in applied machine learning and specialized time-series algorithms include:
- Business KPIs: Reporting key SCM metrics using data aggregation and event processing
- Anomalies: Detecting deviations from normal behavior
- Predictions: Being able to forecast the future state
- Prescriptive Actions: Recommended course of action or identification of a root cause
Connected intelligence across the digital supply chain is evident by the various use cases for ready-to-go. These use cases include:
- Order Management and Logistics: Proactively identify “at-risk” deliveries
- Manufacturing: Yield and quality predictions and insights; genealogy and traceability analysis
- Maintenance and Field Service: Predictive maintenance planning and asset failure detection
- Procurement: Intelligent supplier payment terms and discount rates
- Planning and Collaboration: Predict demand and product optimization
Machine learning-driven preventative maintenance planning provides preventive analytics or anomaly detection using ML. It also provides optimal maintenance scheduling for the factory (i.e. suggested modifications to existing schedule).
Within the Demand Management Cloud, Oracle has been using ML for some time. Other aspects of that include demand prediction. Forecast models are automatically selected and blended to yield an accurate forecast. Here, the forecasting level is automatically selected. Results are explained, complete with a side-by-side visual – each having a forecast model value as well as a blended forecast. ML visualizes a breakdown of the forecast into baseline, trend, seasonality, and causal while additionally attaching rates, which have been calculated based on the sales history of parent-child: CTO.
ML is based on the Bayesian model ensemble, with multiple models analyzing for linear, non-linear, and autoregressive features. It addresses intermittency, co-linearity, anomaly detection, level shifts, and both short and long trend components. ML captures seasonality, trend, holidays, events, and price effects.
In addition to what is already available to users, Oracle plans to add new product optimization (NPO) through the utilization of machine learning techniques to determine a unified attribute model, or demand function, that can “learn” from existing product data. Ideally, NPO would accurately predict product launch demand curve/volume all while gaining deep insights based on product attributes. This would improve the success of new product launches by accurately predicting customer demand during product concept and commercialization. In short, NPO should do all of the following:
- Improve forecast accuracy
- Minimize supply disruptions
- Increase revenue
- Optimize inventory
Emerging Supply Chain Innovation Technology No. 3: Digital Twin + Digital Assistants
Digital Twin is a unique perspective that looks at both data from business applications and from a 360 perspective. In short, it simplifies interaction with physical assets. In greater detail, Digital Twin is a single pane of glass with a 360-degree view of assets like KPIs, incidents, maintenance, and financials.
Digital Twin is unique because it allows you to view the asset in the context of the business processes and relate it to other assets and hierarchies. It allows the user to interact with assets, physically or virtually, using an augmented reality interface and what-if simulations.
In addition to Digital Twin, conversational intelligence is also accomplished with digital assistants. Designed with all of the capability of a chatbot and more, digital assistant is a program that simulates conversation with human users while recommending and completing tasks beyond simple conversations.
Whereas chatbots are single-purpose and user-initiated, DA is bot initiated and multi-purpose. Oracle has found the digital assistant to be extremely useful, especially for complex routine tasks that are time-consuming. Utilizing this feature, Oracle has seen improved productivity, even for the occasional user, for which DA removes the learning curve.
What makes DA superior is its ability to work across many channels (SaaS UI, Web UI, iOS, Android, and more) and its vast network of skillsets. One example of this is automated skill coordination. Benefits of this skill include:
- Modularization of functions
- Enabling incremental development
- Simplification of code management
- Improvement of non-sequitur handling
- Simplification of versioning and LCM
- Enabling segmented authorization
Another example is the transportation status skill. Currently, Oracle works with the Digital Assistant team and shares information in order for them to provide sample items for supply chain customers. With the transportation status skill, the initial skills included Shipment Status Inquiry and Order Status Inquiry. Potential implementation partner extensions include modification of the dialog flow and leveraging REST services to build custom components.
The sales order status skill shows items ordered, the fulfillment status, and the expected ship date. It has the ability to answer questions about ordering/return policies with the capability to redirect to customer service (Oracle Cloud Service) for more detailed inquiries.
Manufacturing and maintenance skill is a skill that incorporates the functions of Manufacturing Line Status (today’s work orders due, work orders for an item, and past-due work orders) and Maintenance Work Requests (identify maintenance issue, use of phone location to identify the site, and set maintenance status update preferences).
The supply chain planning exception skill primarily has the ability to report run status of multiple plans. However, it gets plan exceptions including total value, revenue at risk by the customer, and products with demand at risk.
Emerging Technology No. 4: Blockchain
Currently, Oracle Blockchain Application Cloud is working mainly with its intelligent track and trace functionality, which monitors transactions and movement of assets or goods across organizations. Using a distributed ledger, blockchain records/monitors:
- Shipment notifications
- Bill of landing
- Manufacturing work orders
- Purchase orders
- Sales orders
- Service records
- Warranty information
- Assets
- Equipment and cargo conditions
- Predictive insights
Moving forward, Oracle hopes to roll out new functionality of blockchain such as:
- Lot Lineage and Provenance: Pedigree, serialization, and genealogy of product components
- Intelligent Cold Chain: Comprehensive track and trace system for food and pharmaceuticals safety
- Warranty and Usage Tracking: Product usage tracking for rental, warranty, service, and insurance for high-value assets
Another functionality Goyal discussed was the Oracle Integration Cloud Platform. Oracle Supply Chain Management (SCM) Cloud produces services-driven integrations and process automation. Process automation features include:
- Structured process modeling using standard BPM
- Unstructured (rule-based) using declarative interface
- Complex human workflow
- Decision modeling
- Complete process traceability and process milestones
- Robotic process automation
The end result of this produces SCM extensions, partner solutions, blended visual analytics, X-functional process, and mobile solutions.
Goyal also quickly touched on robotic process automation (RPA) for digital SCM transformation. This functionality orchestrates RPA robots using a prebuilt RPA adapter to incorporate robots into integration flows effortlessly. Robots execute repetitive tasks with easy “record and playback” modeling. Operational analytics leverage execution data to optimize end-to-end processes. Over 75 adapters are available to Oracle and all third-party support as a starting point for this process.
To learn more about how to enable supply chain innovation with emerging technology, check out the additional resources attached below.
Additional Resources
COLLABORATE 20 will take place April 19-23, 2020 at the Mandalay Bay Resort and Casino in Las Vegas, Nevada! Don’t miss this chance to share inspiration, insights, and solutions with your peers, vendors, and the Oracle team! Register before March 6, 2020, to take advantage of Early Bird pricing.