Adapting to the demands of ‘batch of one’ production

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Kushal Nahata, CEO at FarEye, explores the rising demand of one-off products and the impact a partnership between artificial intelligence and logistics could have on the sector.

Thanks to the continuous improvement of technology, manufacturers are increasingly opting for ‘batch of one’ production. Advancements in fields such as 3D printing have enabled the production of one-off items, such as engine parts and prosthetics, that often need to be produced bespoke according to individual requirements. The technology reduces upfront costs and physical labor – both factors that would traditionally increase order volumes in an ordinary factory.

Biopharmaceuticals are enabling medicine to be tailored toward the genetic or molecular profiles of individual patients, enabling a better quality of healthcare. Yet such niche drugs obviously require a smaller batch of production, and will therefore change the way in which pharmaceutical companies must operate.

Putting production methods to one side, the internet has dramatically improved the business case for offering unusual products, allowing businesses to reach niche audiences while remaining profitable.

Research from eMarketer estimates projected sales from e-commerce to grow to US$4.058tn in 2020, making up 14.6% of total retail spending. A new expectation among consumers to be able to access anything and everything online has led to a rise in demand for personalized, one-off products, with recent findings from Deloitte pointing to an average of 36% of consumers now expressing an interest in personalized products or services.

Despite the benefits that industries such as manufacturing, medicine and healthcare undoubtedly feel, there’s an uncomfortable knock-on effect to logistics providers that now have to adapt to facilitate these new demands. It’s becoming less and less cost-effective to support the processing of ‘one-off’ products and services, with a complex and unwieldy process.

Solutions to meet the rising demand

To enable the efficient delivery of one-off products, automation can digitize and streamline steps in the operations workflow that were previously completed manually, such as delivery scheduling and path-routing. Automation is enabled through the use of algorithms incorporating machine learning functionality for continuous improvement and optimization.

Automated digital documentation in each step mitigates the detrimental impact of human error and empowers firms to provide better customer experience. Real-time omnichannel auto-updates to the customer enrich the overall customer journey and help deliver against brand promises.

Another solution to meet the demand of batch of one productions lies in the ‘Uberization’ of the industry. Through the use of Uberized tracking and real-time feedback, customers receive tracking links alongside an estimated time of delivery with a real-time view of the courier’s progress. Once delivery is complete, the customer receives a link to share instant feedback. Tasks are auto-assigned to employees who meet proximity and availability criteria, again helping to meet demands for the delivery of niche products.

Artificial intelligence is another technology that will play a critical role in the optimization of delivery routes, taking into account factors including idle time, maintenance and fuel costs to help serve customers quickly. Anticipatory AI will take customer experience to the next level, delivering goods to customers often before they’ve even needed the product. The technology will enable algorithms to analyze and draw predictions from vast amounts of data such as browsing behavior, purchase history and demographic norms to predict what customers will purchase, which will be able to personally meet the demands of each unique consumer.

IoT will also enable one-off items to be delivered quickly and efficiently. The technology, which has seen rapid growth thanks to the availability of cheap and reliable sensors, increasing penetration of the internet and incremental growth in data storage and processing capabilities, will accommodate end-to-end visibility for fleet managers.

Real-time notifications to managers enable immediate response to reduce downtime and eliminate bottlenecks. One-off items like pharmaceuticals may require a temperature-controlled environment during transit to avoid damage, and cloud based sensors can continuously monitor conditions to help eliminate the likelihood of damaged goods.

If manufacturing is to become more personalized then the logistics industry must play the same game, becoming less rigid and operating at maximum efficiency. Ultimately, there is no one-size-fits-all approach, but combining AI-enhanced digital software solutions in logistics could be the silver bullet.

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