Supply chain risk management teams know the world is full of challenges and complexity. Trying to prepare for every potential risk to supply chain operations is impossible; nevertheless, some preparation must be made in order to prevent or mitigate significant disruptions to operations. As more and more companies transform into digital enterprises and implement digital supply chains, cybersecurity has risen near the top of the risk management priority list. This was evident in a series of interviews with risk management experts conducted by Robert Bowman, Managing Editor of SupplyChainBrain. During these interviews, the experts laid “out the biggest challenges that companies face today in protecting their supply chains from all kinds of disruptions, the solutions that are currently available to them, and the ways in which they intend to address the issue of risk in the future.”[1] A video of those interviews can be found here. The experts note, however, risk managers need to look both broadly and deeply when it comes to potential risks. The experts also stress the importance of leveraging data and analytics in their risk management efforts.

Reactive Supply Chain Risk Management is No Longer Viable

As the global supply chains extend they also become more complex. Managing a supply chain with tier 2, 3, and 4 suppliers is no longer remarkable. What that means for supply chain professionals is that they need greater visibility and understanding into the entire value chain. They need to understand the perturbative effects of upstream disruptions to downstream operations. A global survey focusing on cost, risk, and the evolving role of procurement in today’s supply chains conducted by riskmethods concluded reactive supply chain risk is no longer viable.[2] Key survey findings include the following:

• “70 percent of survey respondents chose ‘be more strategic and act preventatively’ when asked to select the driving reason behind prioritizing supply chain risk management in their organizations. This goes to show the larger strategic role that procurement leaders are being tasked with, and suggests that reactive risk management is becoming less viable.”
• “49 percent of respondents said that they have no structured assessment when asked if they possessed a mechanism for measuring supplier impact.”
• “Only 27 percent said they have structured, quantitative assessment of financial impact related to supply chains when asked if they possessed a mechanism for measuring supplier impact and 44 percent have a qualitative assessment of criticality of suppliers, such as substitutability. This is a huge blind spot for procurement teams and businesses in avoiding and mitigating major disruptions.”
• “58 percent of respondents said that solving the conflict of their objectives of minimizing risk vs. generating savings is either unclear or just not solved, meaning procurement is operating in a state of fluctuating goals, usually in favor of cost savings where risk could be higher.”

One way of generalizing those findings is too many companies are “penny-wise and pound-foolish.” Risk management programs are essential in today’s complicated world and they require a significant investment in time, resources, and manpower.

Leveraging Big Data and Analytics

Risk management essentials discussed by the experts Bowman interviewed included things like end-to-end supply chain visibility, collaboration, communication, real-time data, and analytical insights. The complexity of today’s business landscape demands technological solutions that provide a clear picture of supply operations, insights into potential areas of risk, and recommended actions both ahead of and during disruptive events. Analysts from DHL Resilience360 draw lessons from Star Wars movies when discussing risk management.[3] They understand “the Jedi have the force on their side” — and that not every company will have that advantage. Nevertheless, they note, “Even a long time ago in a galaxy far, far away, success depended on many of the same practices that apply on Earth today.” Those practices include:

• Access the right data. “In the 1977 original ‘Star Wars,’ the rebel force must attempt to destroy the largest and most powerful weapon ever built. Outnumbered and outgunned the task seems impossible, but for one decisive advantage. Our heroes have a detailed map of their target allowing them to identify, and ultimately exploit, it’s only weakness.” Today, accessing the right data is made easier by software bots that can automatically access required information.
• Use local knowledge. “Two films later in ‘Return of the Jedi’ another daring plan seems doomed to failure, with our heroes ambushed and pinned down on an alien world. It isn’t targeted firepower that saves them here, but an alliance with the indigenous population, who apply their forest skills to overcome and destroy the Empire’s troops.” Suppliers are often located in areas with unique risks like flooding, tornadoes, hurricanes, social unrest, governmental regulations, and so forth. Knowing local conditions is critical to ensuring contingency plans address the scenarios most likely to emerge.
• Have your contingency plans in place. “Plan A doesn’t always work out in a ‘Star Wars’ movie. In fact, it often places the heroes in more jeopardy than they were at the start. From Luke Skywalker to Poe Dameron, the principal characters of the series each take a similar journey, from youthful impulsiveness to mature premeditation. Over time, our heroes learn by hard experience that they must assess the risks, weigh the options and adjust their plans, even if that means retreating to fight another day. This is a journey companies on Earth experience every day, and those that navigate it wisely will survive and thrive.” Adopting contingency plans without exercising them is foolish. The military is fond of saying no plan survives contact with the enemy. By exercising plans, companies can provide their employees with valuable experience as well as detect any glaring discrepancies in their plans.

Technologies, like cognitive computing platforms, can be valuable in all of the above areas. Nari Viswanathan (@nariv), Vice President of Product Management for River Logic, asserts, “Businesses that have applied big data analytics to their supply chain functions have seen a reduction in costs, improved risk management, shorter cycle times, more accurate forecasting, and an overall improvement when it comes to making informed decisions.”[4] Viswanathan points out prescriptive analytics is one of the benefits provided by cognitive technologies. Cynthia Harvey explains, “Prescriptive analytics tell organizations what they should do in order to achieve a desired result. These tools require very advanced machine learning capabilities, and few solutions on the market today offer true prescriptive capabilities.”[5] Viswanathan adds, “Not only does advanced analytics benefit the entire company, but it also betters the career of supply chain staff. Employees become more empowered as they make decisions that are of global impact to the company. They become more efficient as they rely on a digital assistant of sorts to help them make more informed decisions. Supply chain managers play a more strategic role as they collaborate across the organization. While many companies are making great strides in implementing prescriptive analytics in their supply chain operations, there is still a long way to go. The market is ripe for the next round of supply chain technologies, and businesses will only continue to improve efficiency, increase savings, and improve the lives of their supply chain staff as they take a more strategic approach to their data.”

Summary

Business risks today range from reputational risks resulting from social media complaints to cyber risks from hackers to supplier risks due to financial crises to disruptions created by natural disasters. To monitor and understand these risks, companies need technologies equal to the task. Cognitive computing platforms are good place to start.

Footnotes
[1] Robert Bowman, “Waking Up to the Need for Risk Management,” SupplyChainBrain, 30 April 2018.
[2] riskmethods, “Reactive Supply Chain Risk Management is no Longer Viable, says New riskmethods Survey,” Cision PRWeb, 17 April 2018.
[3] DHL Resilience360, “May Resilience Be With You, Because Risk Sure Is,” Spend Matters, 3 may 2018.
[4] Nari Viswanathan, “Using Prescriptive Analytics to Decrease Supply Chain Disruptions,” Supply Chain Management Review, 7 May 2018.
[5] Cynthia Harvey, “Big Data Analytics,” Datamation, 27 July 2017.