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Predictions: Three Supply Chain Technologies Set to Disrupt in 2017

Several technologies are poised to disrupt the supply change this year, as they do every year. Here are three you should take seriously to stay competitive.

1. Self-Driving Vehicles Take to the Streets

Ford, Nissan, Toyota and Tesla all project that autonomous vehicles will be sharing the road 2020. Business Insider estimates the total number at 10 million. Consumers may get excited by this prospect because it means unlimited texting while driving (without the dirty looks from the person whose lane they are invading) and possibly catching a quick gridlock nap.

For the estimated 1.2 million trucking companies in the U.S., self-driving vehicles could completely change everything. More than $1 trillion of manufactured and retail goods are transported via truck within America and to and from Mexico and Canada. Having these transported by machines, and not humans, is expected to offer several safety advantages.

After an exhausted Walmart truck driver hit a limo bus carrying comedian Tracy Morgan in 2014, critically injuring him and killing passenger James McNair, the company and its insurers were forced to pay a reported $90 million to Morgan and $10 million to McNair's estate.

That year, there were a total of 3,978 fatal accidents involving trucks and large buses, according to the Federal Motor Carrier Safety Administration. Self-driving trucks are expected to nearly eliminate this problem.

"It is projected that they can reduce traffic fatalities by up to 90% – while also providing enhanced data in real time on critical functions like deliveries and vehicle functionality," says Gary Brooks, CMO of Syncron Inc., which specializes in inventory management and price optimization software.

The world's first commercial shipment via autonomous truck already happened in Oct. 2016, when a Budweiser semi using Otto Motors' self-driving technology hauled a shipment more than 120 miles.

Putting some to all of the 3.5 million U.S. truck drivers is problematic, to put it mildly, but it makes business sense.

An OTTO-powered Budweiser truck made the first autonomous delivery last year. What will this year bring?
Photo: OTTO Motors

2. Expansion of Service parts inventory management and pricing optimization

About half of all failed product repairs are attributed to poor part availability.

"Having the right parts in the right place at the right time is critical to a company’s ability to maximize uptime of the product they sell – think planes, trains, heavy medical equipment, construction equipment, etc.," Brooks says. "Maximizing uptime of these revenue generating assets is what customers care about most, and if the equipment is down, the manufacturer is losing money and pushing customers away."

To combat this, Brooks says companies should implement inventory and pricing management software to bolster the aftersales supply chain.

Syncron Global Price Management solution optimized Hitachi Construction Machinery's pricing capabilities through science-based segmentation, pricing guidance, and advanced analytics. Hitachi is the third largest full-range construction equipment manufacturer in the world and the software solution improved the price revision lead time from five to three months, and reduced the pricing lead time by 30% for new parts. Hitachi estimated the gross profit increase from making the change at $20 million.

"The world’s most successful companies are investing in service parts planning technologies to improve their often sub-optimized service supply chains to ensure part availability levels are consistently higher than 95%," he says.

Hitachi Construction Machinery

Using advanced price management software, Hitachi's Construction Machinery division cut its price revision lead time from five to three months, allowing maximum uptime for equipment such as the ZX350LC excavator.
Photo: Hitachi Construction Machinery

3. Automation Moves into Ordering Process

Ordering data is obviously vital to any business's ability to understand its past, present, and future, from analyzing customer behavior to figuring out where to steer new investments. But what happens when that information isn't right due to human error?

"With manual processing costing between $30 - $60 per order (not to mention the cost of filing, document storage, error resolution and more), continuing to accept error-prone manual data entry is costing businesses millions of dollars a year in direct and indirect costs," says Brent Halverson, CEO of Conexiom.

In addition, manually keying in orders for processing takes customer service members away from helping your customers, and focused on what is essentially mind-numbingly boring busy work. With orders piling up, it's no wonder sometimes an error occurs.

"With hundreds of purchase orders arriving daily, each with thousands of line items to manually process, it is inevitable that keying errors occur and orders go missing," Halverson says. "But just one innocent data entry error or lost order can result in delays, the wrong part, quantity, color or even pricing for a customer. Not only are these mistakes frustrating for them, causing additional effort on their part to resolve, but it also costs you money too in extra shipping costs, wasted materials, credit notes, restocking costs, and even write-offs."

Right now, he says, only about 30% of Order-to-Cash and Procure-to-Pay processes are automated, but that AI is creeping in. Conexiom has automated this process and deployed for a decade, and sees 2017 as the year more companies shift from manual entry and Optical Character Recognition (OCR) and to algorithms and AI.

"The biggest advantage with adopting an AI approach is that the identification of which customers are ideally suited for automation is transferred from the manufacturer or distributor to the technology itself," Halverson says. "In addition, instead of having to embark on an implementation process and work through how a purchase order can be mapped to a sales order with the software vendor, the technology can take care of that process itself."

Contact Conexiom at [email protected] for more information.

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