Digital Supply Chain: What’s Your Reality

Digital Supply Chain: What’s Your Reality

What does the digital supply chain mean for your company? More integration, better visibility, a single version of the truth, a clearer view of the future—and maybe a few flying robots.

Maybe you thought your supply chain was digital already. You use barcode scanners, a transportation management system (TMS), and enterprise resource planning (ERP) software; surely you’re conducting business in zeroes and ones.

While it’s true that every supply chain these days uses some kind of digital technology, many companies want to take the digital enterprise to a whole new level. Their leaders talk about using advanced technologies to produce grand transformations, making their supply chains faster, smarter, more efficient, more integrated, and more agile.

The drive toward the digital supply chain clearly has captured imaginations at leading companies. Eighty percent of respondents to a 2017 survey of supply chain professionals, conducted by material handling trade association MHI in partnership with Deloitte, say the digital supply chain will become the dominant model within five years, while 16 percent say this new model already prevails.

The technologies that prompt the most disruptive changes are: robotics and automation, predictive analytics, the Internet of Things (IoT), driverless vehicles and drones, sensors and automatic identification, and inventory and network optimization tools, according to survey respondents.

"The adoption rate of these technologies over the past four years is absolutely incredible," says George Prest, chief executive officer at MHI in Charlotte, North Carolina. "Companies are using all these tools to get products built faster, better, and cheaper."

As one might expect with any hot, new technology trend, studies on the state of the digital supply chain abound. According to a study that New York-based business software company Infor, which owns cloud-based global supply chain management service GT Nexus, conducted with Capgemini, more than three-quarters of the 337 executives in 20 countries surveyed say digital transformation of the supply chain is important or very important. Seventy percent say they already have such transformations underway.

Also as one might expect with a hot, new technology trend, it’s hard to pin down a precise definition of "digital supply chain." But ask enough people, and you’ll come up with something like this: the digital supply chain draws data from many sources along the supply chain, integrates that data as much as possible, and uses it not only to improve supply chain processes, but maybe also to reshape those processes altogether.

For example (to cite two cases mentioned in the MHI report), a company might use advanced robotics to develop a fully automated omnichannel fulfillment center; or a hospital might use predictive analytics to make sure an emergency room is always stocked with the supplies required for the next scheduled procedure.

At Amber Road, a provider of global trade management solutions, when people talk about the benefits of a digital supply chain, they focus on four values: "cost savings, agility, risk reduction, and improved visibility," says Gary Barraco, director, global product marketing at the company, in East Rutherford, New Jersey. Agility is the most important value of all, according to Amber Road customers. "Unless you have agility, you can’t reduce costs or minimize risk," Barraco says. "And visibility comes along with that."

One overriding goal of the digital supply chain is to break down siloes among trading partners, according to Greg Kefer, vice president, corporate marketing at Infor. Everyone having access to the same data creates a single version of the truth.

Kefer compares this to the single truth that appears on the social networking platform LinkedIn. "When you change jobs, your entire network gets the news instantly," he says. In a fully digital supply chain, when someone issues a purchase order, or a shipment arrives at a port, everyone who needs that information gets the same details at the same time.

Supporting Smart Decisions

While visibility is crucial in the digital supply chain, simply knowing the facts does not, by itself, produce a revolution. Now that companies can capture and store vast volumes of data about their operations, they need ways to extract business intelligence from that mass and use it to support smart decisions.

"It has come to the point where the volume of data being generated in the supply chain has surpassed what humans can process," Kefer says. As companies pull more and more data from sensors, scanners, and other sources that make up the IoT, they need analytics technology to make sense of that raw material.

A new software solution from transportation and logistics firm C.H. Robinson and its managed services division, TMC, does exactly that: uses big data to make predictions and recommend action. Called Navisphere Vision, the solution starts by collecting data from all of a shipper’s transportation partners, as often as the partners can provide it. Navisphere Vision uses that data to build a real-time picture of all the shipper’s freight. Users view shipment status information on a map display, and they can filter it based on a variety of factors, such as line of business, product, or SKU.

Of course, shipment-tracking systems have been available for years. The newer twist is that Navisphere Vision predicts how freight will travel in the future. The insights come largely from computer models that C.H. Robinson has developed using data from millions of shipments the company has managed over the years.

"Based on the truck’s location and destination, we use historical shipment data to build algorithms that predict whether the truck will be on time or late," says Chad Lindbloom, chief information officer at C.H. Robinson in Eden Prairie, Minnesota.

C.H. Robinson is further developing its algorithms to incorporate factors such as weather and traffic conditions. "For example, if the track of a snowstorm is going to intersect with the track of a truck, we’ll input a prediction for a three-hour delay," Lindbloom says.

The system can also draw information from the log where C.H. Robinson’s contract carriers and dispatchers record problems that affect their deliveries. Natural language processing technology extracts relevant data from the text. "Then we highlight on a map potential impacts to real-time events," says Brett Cooksey, the company’s director of information technology.

For example, a C.H. Robinson contract carrier making a delivery to a warehouse might learn that staff in that facility has gone on strike. Any Navisphere Vision customer with shipments moving to or from that warehouse—whether or not C.H. Robinson manages that freight—would get warnings about potential strike-related delays.

Beyond advising shippers about possible problems, Navisphere Vision might someday recommend corrective actions. "Then, over time, we can build up enough of that information to start taking action on behalf of users," Cooksey says.

For example, instead of suggesting that a company reroute a shipment to avoid bad weather, the software could execute the change on its own. To reach that point, C.H. Robinson will first have to improve its artificial intelligence (AI) capabilities, Cooksey adds.

Currency and Coffee

AI also figures in the work of Bext360, a Denver-based firm that is bringing that technology, plus machine vision and blockchain, into the coffee fields of Africa and South America.

Bext360 is harnessing those technologies and others to pay coffee farmers faster and track individual batches of coffee throughout the supply chain. The data it collects along the way can provide detailed information about the product to roasters, wholesalers, retailers, and consumers.

The process starts with a machine that Bext360 installs at the washing station where local coffee farmers deliver their product. Farmers pour harvested coffee into the box, which uses machine vision and AI to evaluate the coffee cherries one by one and assign a quality score to each. "We can now give the farmer feedback and also pay based on current quality," says Daniel Jones, CEO at Bext360.

The system makes a digital payment to farmers on their phones, using the local currency or a cryptocurrency based on blockchain technology.

As processors extract green coffee beans from the cherries, and then roast and transport them, Bext360 uses machine vision and AI to track those processes. It adds that information to its data about each batch, stored in a tamper-proof, encrypted format.

The company also tracks the condition of the product in transit, using GPS, temperature sensors, radio frequency identification (RFID), and other technologies. "We can record that and correlate it back to the original collection of the cherries," Jones says.

All this tracking, which establishes the quality of specific batches of coffee, grown on specific farms, allows farmers who deliver higher-quality coffee to command more money than they earn today.

Bext360 expects to lease its systems to large coffee trading houses, and provide its data as a service. The data will generate better information for use in marketing, and will help companies seeking certification for fair trade, environmental responsibility, and other good practices.

Coffee retailers form a second prospective market. Companies such as Starbucks and Blue Bottle like to show customers where their coffee was grown, but the information they can offer today is limited. "You can’t see where the coffee was produced, or the day it was produced, or any kind of real provenance," Jones says.

Bext360 can provide that information. Someday, the data might also show customers how their purchases help the farmers who grew the coffee in their cups. "For example, if you buy a cappuccino at Blue Bottle, your receipt could say that 10 cents of your purchase went to building a school in Uganda where that coffee was from," Jones says.

In late 2017, Bext360 ran a pilot of its system in Uganda, with coffee shipped through Kampala to Denver for roasting and sale. The system also operates in Ethiopia.

Bext360 is looking for opportunities to apply its technology to other commodities as well, such as chocolate, nuts, and seafood.

"We’re doing a mini-pilot in Nova Scotia," Jones says. The aim is to track where fishermen harvest shellfish such as lobsters, shrimp, and scallops, to make sure no one takes more than the environment will bear. "They’re sustainable if they’re harvested correctly and there’s no cheating," he says.

Send in the Drones

Besides taking the measure of coffee beans and seafood, new technologies can help distribution centers maintain correct inventory data. Such accuracy is crucial when you’re trying to keep product flowing to customers, without the delays caused by stockouts. "If you don’t have inventory accuracy, you don’t have velocity," says Matt Yearling, CEO of PINC Solutions, in Union City, California.

A warehouse management system (WMS) tracks how many units of each product you have on hand, but those systems have always relied on humans to feed them information. "And it’s not timely information, either," Yearling says. Even in the best-run warehouse, the account of inventory in the WMS is no more than 90 percent accurate, he adds.

To address that problem, PINC has introduced a system that sends a small, unmanned aerial vehicle equipped with optical sensors into all the nooks and crannies of a warehouse to conduct automated cycle counting.

You could call this vehicle a drone, but it isn’t the kind that a human pilot flies with a handheld controller. It’s actually a flying robot, finding its own way past racking and around corners with help from onboard cameras and machine learning software.

"We feed the drone a map at the beginning, but it’s constantly looking and updating as it continues to exist in the environment," Yearling says.

Along with the cameras for navigation, the drone carries a high-resolution camera for capturing inventory data. Onboard software picks out significant objects in the camera’s field of vision, such as a label displaying a barcode or an alphanumeric identifier. "You train it to understand the preferred mechanism and that will provide the highest accuracy rate when the system reads it," Yearling says.

As it collects and interprets this data, the drone transmits the results across a wireless link to a cloud-based system, which then uses the information for inventory management.

Because the drone can count inventory as often as needed, it ensures that a company always has a current snapshot of the products in a warehouse. That’s not possible when you rely on humans walking the aisles with barcode scanners to conduct cycle counts. "Labor today is so stretched, companies don’t achieve what they mean to do," Yearling says

Handing the repetitive task of cycle counting to robots, companies can assign employees to higher-value activities, such as managing exceptions.

Because they can easily penetrate narrow aisles and reach product stored at any height, the drones also offer a safety advantage. "Removing people from a ‘dangerous’ environment is attractive," Yearling says. But the real return on investment comes from the ability to maintain inventory accuracy, and to do that faster, better, and cheaper.

While the thought of implementing drones, AI, and other leading-edge technologies sparks buzz, for many companies the journey to digital supply chain transformation starts with a more basic step: eliminating manual processes.

"Every thing, every supplier, every data point, has to be digital and shared on a common platform so we can collaborate," says Barraco. Otherwise, the data flow grinds to a halt each time someone uses fax or e-mail to share information.

Where to Start

Converting all your processes and communications with suppliers to digital format on a common platform can be a huge undertaking. "No one can roll out a digital transformation across the entire supply chain at one time," Barraco says. "It has to be done in phases." To choose where to start, identify your biggest supply chain pain points and address them first.

Value stream mapping can help a company locate the most effective starting point for a digital transformation. "Quantify your processes from a dollar perspective, to see where the most efficiency value is achieved," says Cooksey. "That’s where you start."

As companies swap manual processes for digital ones and adopt new technology, they also need to make sure they have the talent onboard to take advantage of those innovations.

"The technology is way ahead of our workforce capabilities," says Prest. The warehouse of the future will require workers who know how to install, program, and maintain automated systems. MHI is working with technical schools to develop programs that can prepare young people for those kinds of jobs.

Whatever starting point a company chooses, it’s important to get moving now on a digital transformation, with its promise of a single view of the truth for everyone involved in a company’s supply chain.

"Don’t sit around and wait for blockchain to mature," Kefer says. Before that and other new technologies enter the mainstream, companies must put themselves in a position to take advantage of their capabilities. "Your company is going nowhere until you centralize your data and get a holistic view of what’s going on," he says.

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