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22 AUGUST 2017



AUGUST 2017 23

Imagine your company has a promotion underway for a newly launched product, and based on the sales forecast, youve kept a certain amount of inventory on hand. Then, your artificial intelligence (AI) system alerts you that the product

is gaining traction on social media customers are giving it a five-star rating leading to an unexpected increase in demand. The system can then offer recommendations on how to ramp up production and inventory.

Or consider: Your AI system informs you of an 18-car pileup on a major freeway and that if you ship from a certain distribution center, your delivery trucks are going to be hours late. Using suggestions from the system, you might decide to take a different route or ship the goods from another location.

Still in its infancy, AI has the potential to impact multiple parts of the supply chain including order management, customer service, logistics and inventory management as well as in procurement and spend analysis.

It enables supply management organizations to make decisions faster, using the fullest set of data possible and in real time, says Jeanette Barlow, vice president of strategy and offering management, IBM Watson Customer Engagement Supply Chain Solutions at IBM in Cambridge, Massachusetts. AI acts as an advisor, she says.

Without it, supply management practitioners would have to check across many systems, sending emails, making phone calls and holding meetings, she says: If you were lucky, this would take you only a few days. But it likely will take longer, especially if youre looking outside the organization.


Although still in development, AI has

the potential to impact organizations in

many ways and supply management

practitioners need to be prepared.

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WHAT AI IS AND ISNTTheres a lot of hype about what artificial intelligence is and isnt. Some think it pertains to computers or robots replacing humans and taking over human decision-making, says Robert Handfield, Ph.D., Bank of America Distinguished university professor of supply chain management and executive director of the Poole College of Management Supply Chain Resource Cooperative (SCRC) at North Carolina State University in Raleigh, North Carolina. Thats definitely what its not, he says.

According to Accenture, AI is a constellation of technologies that, when integrated together, can create a highly adaptable, nimble business capability. It is technology-rich, says Nicola Morini Bianzino, global lead of artificial intelligence at Accenture in San Francisco. Its a combination of multiple technologies: computer vision, natural language processing, machine learning, deep learning, knowledge representation, expert systems, biometrics and video analytics, he says.

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AI, which has been around for about 20 years, augments rather than replaces supply management processes, Handfield says. It can analyze data much faster than humans can by analyzing Microsoft Excel spreadsheets or order-management systems, enabling quicker decision-making, he says. And the decisions are based on facts and data as opposed to a gut feeling or an inadequate data capture, he says. For that reason, there will always be a human in the loop in any AI application, he says.

However, machines IBMs Watson Supply Chain, for example dont do this inherently, Handfield says. The machines have to be trained in how people in an organization make decisions. They have to be trained to know what data to look at, and what an expert would do in that particular context and situation, he adds. Thus, supply management professionals must learn how to interact with the AI systems to support them in decision-making, he says: The systems need to know what questions to ask of the data and what data must be analyzed in various situations, such as whether a supply chain disruption could occur or whether a spend analysis should be conducted.

IMPACTING SUPPLY MANAGEMENTHaving the right data is a concern for most procurement organizations. They worry about whether their data is of the quality needed to begin helping automate tasks, giving insights or enabling learning, Barlow says. One thing hasnt changed: Garbage in is garbage out.

AI can help with that greatly, she says, because it learns from outcomes that werent chosen and from past situations and experiences. Also, because it functions on real-time data, AI enables (1) increased demand and spend visibility and (2) velocity, offering recommendations so supply managers can make decisions quickly, develop contingency plans or plan ahead.

Immediacy is critical, Barlow says. Organizations no longer tolerate multiyear service engagements before they can start to see the payoff, she says. That era in technology is gone. With AI, organizations within hours start to feed data into their systems, get insights and grow from there, she says.

For example, Morini says, AI can aid in decisions on how to move inventory faster and more cost effectively. It also can aid in fixing a problem before it occurs or before it affects the supply chain, he says.

In addition to data management, AI also impacts:

Labor. Its not surprising that artificial intelligence will displace some job roles. While AI is likely to fundamentally change traditional business operations and ways of working, it will lead to new job categories related to creating, training and maintaining AI systems, Morini says. Machines offer strengths and capabilities, like scale, speed and the ability to cut through complexity, that are different from but crucially complementary to human skills, he says.

Morini says that Accenture believes the full power of AI should be unleashed through a people first approach: AI represents an entirely new factor of production that enables people to make more efficient use of their time and do what humans do best: create, imagine and innovate new things.

Accenture research indicates that AI can increase labor productivity significantly by up to 40 percent. This improvement will not be driven by longer hours but by innovative technologies that enable people to make more efficient use of their time, Morini says.

Production capabilities. Besides being a driver of productivity, AI has potential to be a new factor in production. The key is to see AI as a capital-labor hybrid, Morini says. AI can replicate labor activities at much greater scale and speed, even performing some tasks beyond the capabilities of humans. Similarly, AI can take the form of physical capital, such as robots and intelligent machines. This new form of labor will be able to self-improve over time at nearly zero-marginal costs. These characteristics make AI a powerful, versatile and cost-effective tool to drive new channels of growth.

RECOGNIZING THE POTENTIALA Pew Research study projects AI to be be integrated into nearly every aspect of our lives by 2025.

Its already being adopted by consumers. For example, 3 million people chat with Amazon Echos conversation-based assistant Alexa, asking it to do things like give the weather forecast, set a timer, request a pickup from a car service, or place an order for laundry detergent, Morini explains.

As of now, its in the early days of adoption among supply management organizations. This year will be a pivotal year, Morini says.

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We see 2017 as the coming of age for artificial intelligences maturity, he says. Moving beyond a back-end tool for the enterprise, AI will continue to take on more sophisticated roles within technology interfaces. It will consistently be used to add frictionless intelligence to employees interactions with technology, creating opportunities for simple exchanges that drive increased adoption and better user experiences.

TAKING ACTIONDespite AIs infancy, supply management practitioners must start thinking of the roles machine learning and cognitive learning could play in their organizations, Barlow says. They should ask where their organizations could use (1) automation, (2) better decision-making, (3) increased learning capabilities and (4) smart platforms, she says.

A key piece is not AI for the sake of AI, but AI in context of what those use cases are and how supply management practitioners need to work, she says. Those looking at AI to service particular supply management practices are going to have advantages. Its not about technology. Its about how that technology can help drive efficiencies and have a more resilient supply chain.

Morini says that to optimize their manufacturing and supply chains, organizations should begin to implement AI not only in back-office processes, but in operational processes. Executives need to think about setting the right KPIs, tracking results and creating a culture for AI within their organizations, he says.

A key consideration is people. As smart machines take on a bigger role in optimizing supply chain processes, the role of the manager needs to evolve from managing the supply chain process to managing the smart machine that is updating the supply chain process, he says. Leaders need to use AI responsibly by creating the right framework to enable AI to flourish while reskilling employees to do different jobs.

Another consideration is data governance, Handfield says. You need to establish a method to ensure the data you have is accurate, valid and timely, he says. You must be able to pull on data to make these kinds of machine-informed decisions. But if you dont have good data or information, then nobody trusts it. Its not going to be useful.

The First Annual Procurement Data Governanc