Harnessing AI to mitigate supply chain risk in black swan events

By Ambuj Kathuria, Global Head, Data & Analytics, Birlasoft

It was 11 March 2011 when the fourth most powerful earthquake in the world hit the northwestern coast of Japan. Back then, Japan was home to the manufacturing of 40% of memory chips globally. Apple sourced this chip to manufacture iPads, which was a rage those days. Much to Apple’s misfortunes, iPad 2 was launched the same day as the Tsunami occurred-11 March 2011. The demand for the new iPad was palpable. The Japanese shutdowns had a massive ripple effect on the production of iPad 2. The immediate fallouts were customer discontent and brand deputation. Apple’s share price sank by 12% the same day! It took some time for things to get back to normal.
COVID-19 and the growing focus on supply chain risk

Black swan events have caused immense damage in the last few years. In 2019, losses due to catastrophic events like these reached USD 150 billion, as per McKinsey. 89% of the companies have seen a supplier disruption event in the last five years, says Gartner. What’s shocking is that most of them lack the seriousness to deal with the disruption. 65% of the chief procurement officers have limited and no visibility into tier 2/3 level supplier, as per Deloitte’s CPO survey. There’s a lot of catching up to do. The ongoing pandemic has pushed sourcing and procurement (S&P) leaders to relook at supplier risk a lot gravely than they have ever done. There are six significant imperatives for the S&P leaders in these uncertain times:
1. Agility in activating alternative supplier planning.
2. Capturing risk arising from Tier 2/3 suppliers.
3. Negotiating best prices with suppliers.
4. Fixing gaps in existing supplier risk assessment approaches.
5. Improving visibility into potential supplier risk failures.
6. Ensuring business continuity in their operations.
The traditional ways of managing supplier risk

The majority of the organizations use a supplier risk assessment framework to measure the risk exposures. There are usually five broad categories that cover the variables used to calculate the risk index. And, these categories are financial, operational, environmental, social, and regulatory landscape. There are many leading and lagging indicators aligned to each of these categories. Organizations assign weightage to each of these indicators as they calculate their risk exposure. Many of these methods are manually managed or are dependent on external advisors. E.g., a quarterly review by an external auditor, asking external agencies for supplier data reports and analysis, manually looking around for risks a supplier is exposed to through annual reports, asking teams for supplier quality data, and many other ways. There are limitations around scaling-up and enterprise-wide collaboration while adopting these methods. These age-old ways of supplier risk assessments have significant flaws:

1. They focus mostly on the first line of supply network. Every 2 out of 3 procurement leader has no
2. Procuring the right set of primary supplier data is always a challenge.
3. The risk assessment models are not comprehensive enough.
4. Most of these assessments are reactive.
5. These assessments are periodic and not real-time. Forget predictive.
6. It doesn’t work in case the organization has suppliers running into hundreds and thousands.

The perils of ineffective supplier risk management

The after-effects of a weak supplier risk assessment go beyond commercial repercussions. Here are the top five risks that organizations get exposed to if they have an ineffective supplier risk management:
1. Poor customer experience
2. Data and information breaches
3. Disrupted operations and broken value chain
4. Commercial losses and overheads
5. Non-compliance to government regulations
6. Potential brand reputation blows

In today’s volatile and fast-moving world, organizations need to find better ways of dealing with this problem. Unfortunately, it takes a dent for organizations to understand the liability they are carrying. 53% of the organizations follow a reactive approach to managing supplier risk disruptions, says a Gartner research report. So, what should they do now?
The dawn of AI-led supplier risk management

Imagine a S&P world that’s free from below mundane and unproductive tasks:
1. Spending hours with auditors to figure out which supplier is going to fail next.
2. Manually looking through piles of annual reports to carry out financial health checks.
3. Asking for supplier data and then waiting for months to get the correct data.
4. Getting sleepless nights what could go next with your sole-sourced supplier (that’s not a task, by the way!)

AI can bring all of these scenarios to life. Let’s get into the ‘how’ of it. Organizations can build AI and machine learning-based models depending upon their risk assessment framework. The model can feed on real-time data from various sources (like social, news, media, etc.) 24×7 across as many categories as you wish. AI can run noise reduction, relevance-based normalization, other data science-based techniques to provide actionable insights. It then calculates a risk score/index for a supplier by picking up the most relevant and meaningful data from the vast pool of big data that gets fed into it. Depending upon the risk scores, it alerts the organization of potential supplier failures.
Ten reasons to embrace AI for supplier risk management

Only one third of procurement leaders use technologies like predictive analytics and collaboration networks, says Deloitte’s global CPO survey. The same survey states that supplier risk management is the least digitized of the processes in the S&P world. There is immense gap in the adoption of AI in the CPO function that organizations need to address. By embracing AI, organizations can create dashboards that show lagging and leading indicators for a supplier. Using smart AI-based solutions for supplier risk assessment, the S&P leaders will start to see improvement in their key metrics. We list down a few of them:
1. By building a real-time and predictive supplier assessment and monitoring model, organizations get the first line of sight into supplier failure and reduce the extent of supply chain disruption.
2. AI provides a data-driven and real-time approach to negotiate and communicate with suppliers.
3. AI-based solutions foster agility and improved decision making and course corrections by providing better visibility into supplier networks.
4. Organizations reduce operations downtime that happens due to the unavailability of critical raw material.
5. By minimizing delay in production downtime, organizations meet the customer order fulfillment rates and add to the growth and better CX.
6. Due to access to real-time information from multiple sources, including non-traditional sources like social, organizations are better prepared to deal with non-compliance issues and safeguard their reputation.
7. Organizations can reduce their dependency on emergency purchases on sole-sourced moderate to high-risk profile suppliers.
8. By knowing potential supplier disruptions, organizations can spread their supplier risk and minimize the impact. Whether it is about funding a sole-sourced supplier OR switching to a low-risk supplier, AI-based solutions
9. Doing away with manual tracking and monitoring reduces the processing cost per order.
10. With better monitoring and assessment, organizations will drive better price competition amongst suppliers.
So, what’s next?

The ongoing pandemic has opened up the pandora box for S&P leaders. We all realize that all organizations carry some amount of unavoidable supplier risk. Yet, in times like these, the risk amplifies manifold and disrupts the entire value chain.
Back to the Japanese tsunami, there were several learnings for organizations at the end of it. Some of them were: (i.) discarding JIT approach, (ii) diversifying production, and (iii) building alternative S&P strategies. Every black swan event has presented organizations with a lot of learning opportunities.
Unfortunately, COVID-19 is not the last black swan event the world will see. In these uncertain times, a robust supplier risk management system is more about survival than anything else. S&P leaders need to think long-term and underpin supply-chain risk-management with AI. That’s the only way to build supply chains of the future that are predictive, agile and ready to combat future black swan events.