Friday, October 11, 2019

Technologies Are Key to High-Performing Logistics.

By Anna Tan
Head of Apps, Oracle Philippines

  In the modern digital economy, logistics is where the rubber meets the road. But scarce trucks and drivers, late deliveries, spoiled shipments, and rising shipment costs can put a supplier’s relationships with customers to the test, as well as cut into its bottom line. Fortunately, suppliers are starting to apply a range of new technologies—the Internet of Things (IoT), machine learning, driverless vehicles, and blockchain among them—to address those and other problem areas.

  For example, IoT systems already are enabling produce suppliers to monitor temperature and conditions of individual pallets of fruit and route those with a shorter remaining shelf life to the nearest grocery stores. And while self-driving trucks barrelling down the highway is still a futuristic scenario, autonomous vehicles unloading shipments at a warehouse isn’t so far-fetched, as they work in a controlled area, therefore a safer proving ground.

  These functional improvements are important, but a company won’t benefit from the true potential of new technologies if they’re not fully integrated with its supply chain, finance, sales, marketing, and other back-office and front-office applications, with the data outputs from one system becoming data inputs for other systems.

  That data flow and integration enable machine learning capabilities to pick up on patterns and opportunities that otherwise would be missed. All of this becomes much more difficult in an environment of disparate systems with varied data models.

  Companies that incorporate new technologies with that bigger potential in mind will have a substantial advantage, experts say.

Connecting Millions of Dots

  For example, a company that manufactures electronic devices sold in retail stores will use IoT and blockchain to trace component parts shipped to its factories, monitoring delivery times and other parameters to ensure that contract requirements are met. Payments will be made automatically at an agreed-upon time; no more manual back-and-forth to reconcile records.

  The company’s suppliers will use those same technologies to monitor the movement of their shipments, including those handled by third-party trucking companies. If the terms agreed to in any of these contracts aren’t met, the transparency of blockchain digital ledgers will make that abundantly clear to all parties.

  If a manufacturer needs to cut costs, machine learning capabilities in its back-office ERP systems will allow it to identify which suppliers offer discounts for faster payment, cross-referenced with historical shipment records and third-party information about suppliers’ finances that might help it negotiate an even better discount.

  And if defects are found in the finished product, components can be traced back through the blockchain to identify the supplier, specific shipment, and other factors to pinpoint the root cause.

Innovations in Sync

  The key is to not wind up with a tangled web of great technology that doesn’t easily work together—and that also makes incorporating new capabilities hard to do.

  One example of cloud integration is of Philippines' eCommerce pace-setter, QuadX, who implemented Oracle ERP Cloud to bring its myriad of financial transactions across the different users of its platforms onto a common, single enterprise solution. Previously, decisions on operations and management were made from manual integration to their internal operating systems, which was a struggle as QuadX’s business grew. Rolling out a unified ERP platform will deliver transparency and enable the company to scale its business significantly.

  Similarly, Oracle has been incorporating a range of machine-learning capabilities into its cloud-based back-office applications. Oracle ERP Cloud, which is fully integrated with Oracle Supply Chain Management (SCM) Cloud, automates administrative tasks as well as scores supplier risk and recommends alternatives. Oracle IoT cloud applications integrated with the vendor’s cloud supply chain applications incorporate machine learning to enable companies to monitor production on the factory floor, track assets, monitor fleets and workers, and use digital twins to remotely diagnose equipment problems.

  Companies that must build and maintain integrations of multiple systems and one-off cloud services—each with various data models—will have trouble meeting their businesses’ demands for real-time insight.

Risk of Obsolescence

  Businesses that hang on to their legacy, non-cloud systems risk rapid obsolescence, according to a recent MIT Technology Review Insights report.

“Due to the capabilities that cloud enables, traditional strategies for boosting the performance of existing systems, making incremental updates, or bolting on limited new functionality are becoming insufficient to keep pace with competitors that are using the cloud to transform their operations and create new business models,” the report says. “Without cloud technology, organizations won’t be able to do what their rivals are doing.”

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