Most people agree it’s a matter of time before driverless cars become commonplace. These vehicles learn rapidly from experience, and become increasingly effective at navigating highways, streets and traffic.
Extending this development to industry, it doesn’t stretch credibility to envision a driverless supply chain using artificial intelligence to make optimal decisions to plan, source, procure, manufacture and deliver goods. Such a development would be extremely valuable, especially for energy companies struggling with low oil and gas prices.
With the exponential rise in sensors and mobile technologies, machines are interconnected in real time and can provide genuine insight for improved planning. The technology exists to crunch massive amounts of digital data, and cloud computing has removed many constraints on big-data capacity. Supply chain organizations stand to benefit from:
Highly automated execution. Automated decisions, in areas such as materials requisition and creation of purchase orders, can be informed by statistics of variability in historical supply, including lead times to improve service levels and inventory positions. Machine learning can be harnessed to improve transportation and logistics, including scheduling of material delivery, and also of repair and maintenance crews. When a requisition comes in, or inventory needs to be moved, systems with artificial intelligence can look at all of the parameters together and make better decisions without human intervention.
Integration from end to end. Self-learning algorithms lack a vested interest in preserving the status quo (i.e., departmental structures) and instead look to optimize overall results. With a driverless vehicle, for example, the engine, gear box, lights and steering are managed as a holistic entity based on the objective of safely and efficiently moving people and goods from point A to B. Similarly, a driverless supply chain would have the broader objective of integrating sequential activities—from planning, sourcing, procuring, transportation, fulfillment and service—with the overall goal of optimizing speed and quality while containing costs.
Although software vendors have begun to embed artificial intelligence in systems, the driverless supply chain appears to be at least five to 10 years away.
Can oil and gas companies afford, particularly in today’s volatile-oil-priced environment, putting up with low supply-chain inefficiency? Energy lags behind other industries, particularly consumer products and electronics, in supply chain advances. Decision support tools are helping companies in these industries realize significant improvements. Taking this route could help energy companies drive toward improved productivity today while preparing for tomorrow’s driverless supply chain.