The technologies powering high-performing logistics

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, 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 – 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 off-the-shelf cloud integration stems from Oracle’s partnership with Loadsmart, a leading online freight delivery broker. The partnership lets logistics managers match their loads with available third-party truckers at the best price from within the Oracle Transportation Management Cloud application—a task that usually required multiple calls and emails with a broker.

Incorporating a range of machine-learning capabilities into cloud-based back-office applications is crucial to enabling high-performing logistics. For example, integrating ERP systems with SCM systems automates administrative tasks as well as scores supplier risk and recommends alternatives. IoT cloud applications integrated with cloud supply chain applications incorporates 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. Without cloud technology, organizations won’t be able to do what their rivals are doing.”

But companies should be warned – there is no rest, and you’re never done. There will always be a new disruption to contend with, whether from within because of a new product launch, or from the outside from a known competitor – or a company that’s not even on your radar.

Survival means you’ve earned the right to do it again.


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