In Today’s Supply Chain, Anticipating Risk is Only Half the Battle

As supply chains have become more complex and more global, just knowing your tier one and tier two suppliers no longer cuts it. To effectively manage risk, you need to know your suppliers’ suppliers — and even the suppliers supplying them. And more important, you must move from anticipating risk to proactively predicting it.

Not long ago, effectively managing a supply chain simply meant tracking and monitoring the suppliers you engaged with directly. But as supply chains have become longer, more complex and more global, just knowing your tier one and tier two suppliers no longer cuts it. To effectively manage risk, you need to know your suppliers’ suppliers — and even the suppliers supplying them. And more important, you must move from anticipating risk to proactively predicting it to create advantage.

The future of supply chain management is predictive. And it requires three things:

    1. The ability to predict the future with accuracy, leveraging input from real-time market dynamics and historical market trends from a network of partners and peers.
    2. The competency to assess a myriad of potential actions and identify those with the highest propensity for success — based on analyzing the actions and results of other enterprises or individuals that were exposed to similar conditions in the past.
    3. The flexibility to quickly act on these predictions by adapting business processes to execute the right action in advance of market changes.

Traditional technologies can’t enable this, but a new breed of solutions can. Combining the speed and agility of the cloud, the connectivity of business networks and the speed and power of in-memory analytics, such solutions enable companies to not only sense the present, but see the future and proactively shape it to their advantage. To anticipate risks and trends in the market and develop plans and adapt processes to execute on them before anyone else.

Leveraging the hundreds of billions of dollars of financial transactions and transactional data along with relationship history that resides in business networks, for instance, buyers and sellers can make more informed decisions by detecting changes in buying patterns or pricing trends and provide confidence and qualifying information on a potential — yet unfamiliar — trading partner. And, when combined with community-generated ratings and content, they can glean not only real-time insights, but also recommended strategies for moving their businesses forward.

Many companies are also beginning to recognize that they can gain new insights and enable new processes that fuel innovation and advantage by being connected to a community of their customers, partners and peers. TakeMSC Industrial Supply Co., a leading distributor of Metalworking and Maintenance, Repair and Operations (“MRO”) solutions, services and supplies to North American manufacturers

An early adopter of business networks, the company has access to more than 15 years of detailed transaction and relationship data. And it is making the most of it.

“We always did a fairly decent job of mining our own data for supply chain improvements, forecasting, and understanding what to purchase,” says Erik Gershwind. “Now we’re using it to help our customers, and even our suppliers run their businesses better.”

For instance, when MSC learned that employees at one of its customers’ locations had to walk a mile to get to a centralized storeroom where supply replacements were housed, it suggested they install vending machines to put inventory closer to where the work was being done. “In doing so, they are saving time and translating that into real dollar savings,” Gershwind said.

As companies like MSC demonstrate, the predictive revolution is underway. And it promises to transform every function within the enterprise and across the value chain:

    • Material Planning and Logistics teams can combine in-the-moment purchasing data with historic trends to predict stock outs before they happen and plan direct replenishment.
    • Procurement can be alerted to potential future risks in the sub-tier supply chain by triangulating a myriad of real-time supplier performance inputs (e.g., change in payment status, loss of a key customer, change in leadership, liens, patent violation lawsuits, commodity price or supply fluctuations) crossed-referenced historical results when such patterns exist. These alerts can be supplemented with recommended responses or alternative suppliers based on community-generated ratings and buying patterns of other like-buyers on the business network.
    • Real-time insights into invoice approval status married with historical payment patterns can empower companies to dynamically manage payables and access early payment discounts. This same intelligence will empower banks to remove risks from receivables financing, allowing them to offer more competitive rates and new services to business network members.

The benefits of predictive risk management are both clear and quantifiable. So too are the risks of ignoring it. Companies that don’t accurately anticipate customer demands run the risk of designing products that fall short of their needs and fail in the market. Those that fail to sense potential market, commodity, or supplier risks in their tier-one and sub-tier supply chain face not only higher costs but missed sales opportunities. Businesses without a clear view into their spend will miss opportunities to control their costs and more effectively manage their capital.

Companies that embrace the concept of predictive risk management can avoid these pitfalls and vault ahead of the competition.

It’s a major shift. And there will be laggards and leaders in making it. The laggards will remain content to process and react to information in real time. Leaders will understand the need to move faster and sense and predict things to drive smarter, better decisions and transform their supply chains.

Sundar Kamakshisundaram is a Senior Director of Ariba, an SAP company, and a global provider of solutions for spend management and supply risk management.

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