May 17, 2020

Genpact: Supply chain insights from the world of Formula E

Formula E
Genpact
Risk Management
Mike Landry
5 min
Mike Landry, supply chain service line leader at Genpact, draws comparisons between supply chain management and the high-speed world of Formula E racing
Imagine a competitive field where a complete business cycle plays out in just 45 minutes. Where energy is scarce and dwindling, weather is a constant th...

Imagine a competitive field where a complete business cycle plays out in just 45 minutes. Where energy is scarce and dwindling, weather is a constant threat, competitors can literally squeeze you out of contention by just a few centimetres, and strategy is everything. That’s a typical day at the office for Envision Virgin Racing, one of the teams in the world’s first and only all-electric international motorsport, the FIA Formula E Championship.

Now, picture all of these factors, and others, on a global business stage. Natural disasters and geopolitical events can cause notable disruptions to even the best business strategies. Supply chain advantages can quickly shift into disadvantages that operators must overcome to maintain their place in a competitive market.

The need to quickly identify and assess shifting circumstances and make data-driven decisions are challenges that both Envision Virgin Racing and global businesses contend with on a regular basis. Of course, not every organisation makes decisions at 170mph while barrelling down the streets of Hong Kong or Paris. But against intense global competition and stretching customer expectations, every business decision needs to consider the end-to-end implications. Improving your place in the race depends on more than smart transactional execution – it depends on finding insights that can shift the entire approach.

The cognitive supply chain

In recent decades, businesses have initiated supply chain improvements by focusing on transactional excellence. Companies have streamlined internal processes on a static cycle often tied to daily metrics. After shaving internal inefficiencies as finely as possible, they worked to reduce friction in the handoff to the next partner, and so on down the line. While these transactional optimisations deliver tangible results, they can only be repeated so many times until the effort required dwarfs the return. But now the prevalence of AI is creating opportunities to look beyond these improvements for competitive advantages.

Looking at the broader picture for potential strategic advantages is also key to Formula E racing. Using its AI-based Lap Estimate Optimizer (LEO), a scenario engine that analyses weather, track conditions, and driver positions, Genpact helps Envision Virgin Racing better predict the number of laps in a race. This not only helps the team decide how hard to push to protect a position or when to overtake a competitor, it allows it to improve its strategies race to race. The focus shifts from analysing the previous race for minute improvements to predicting approaches and outcomes across future races.

The evolution of these digital technologies is also enhancing prediction in supply chains. With an influx of data, cognitive supply chains are emerging, shifting the focus away from narrow transactions towards a bigger growth agenda. By capturing, storing, processing, and sharing relevant data across partners, demand is clearer, planning more accurate, inventory leaner, and disruptions more easily avoided. The same types of advanced algorithms used by Envision Virgin Racing can generate far more accurate forecasting models in supply chains, including balancing inventory levels against demand volatility and customer service agreements. Anticipation, rather than reaction, becomes the norm.

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Finding advantages hidden in plain sight

Businesses sit on a mountain of structured and unstructured data – and trying to manually identify meaningful data and insights is akin to finding a needle in the proverbial haystack. How companies use data and advanced analytics to generate meaningful insights can make a tremendous difference.

For instance, we realized that Formula E teams have access to GPS data showing drivers’ locations during each race, but teams were not optimizing this noisy dataset. By carefully cleaning and filtering the data, we found that it provides valuable insights into driver tendencies, such as patterns in acceleration and braking, and the impact of in-race hazards. And because the emphasis is on overall outcomes, these insights now feed into race strategy to maximize the drivers’ and team’s points in the championship.

These small breakthroughs can translate into much bigger wins for global supply chains. In the food and beverage industry, Genpact works with a European manufacturer to cut down on micro-stoppages in production – those of 30 minutes or less. Individually, the impact from each micro-stoppage is minor, and at a distance it would be easy to shrug them off as an unavoidable inefficiency. But, working to find the insights to stave off these interruptions pays off in aggregate, because they cost each manufacturing facility over $1.6mn in labour cost, materials, and lost revenue. Scaled across every factory in the business, the total savings potential for cutting out micro-stoppages is more than $150mn.

Sophisticated modeling and forecasting can prepare for uncertainty

Today’s supply chains face mounting pressure and uncertainty – ranging from a fast-changing tariff landscape to natural disasters, Brexit and the likelihood of protracted trade wars.

Just as Envision Virgin Racing relies on effective scenario planning and simulations to understand the impact of disruptions in a race, advanced supply chains are doing the same to determine how to best adjust their strategy and manage resources. So, when natural disasters, port closures, or trade restraints suddenly dent plans, companies that can combine technical skills with industry and process expertise to generate predictive insights will stay ahead of disruption.

Building a cognitive supply chain means first focusing on business outcomes rather than short-term, tactical improvements. That’s not to suggest short-term improvements aren’t critical, but, rather, need to be considered as part of a broader strategic framework when driving systemic improvements across global supply chains. Coordinating people, processes, and technology, with an eye toward applying data to create better outcomes against any set of constraints – regulatory, marketplace, environmental or competitive – can make a world of difference.

Whether your competition is an adrenaline-soaked race through narrow city streets or a pursuit for the right materials to respond to a sudden surge in demand, the result is the same. Cognitive processes give organisations the opportunity to disrupt markets and seize advantages that are tied to innovation and commitment to excellence rather than incumbency or size. And that’s an exciting start to any race.

Mike Landry is the supply chain service line leader at Genpact, a global professional services firm focused on delivering digital transformation.

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Jun 11, 2021

NTT DATA Services, Remodelling Supply Chains for Resilience

NTTDATA
supplychain
Supplychainriskmanagement
Procurement
6 min
Joey Dean, Managing Director of healthcare consulting at NTT DATA Services, shares remodelling strategies for more resilient supply chains

Joey Dean, the man with the coolest name ever and Managing Director in the healthcare consulting practice for NTT DATA and is focused on delivering workplace transformation and enabling the future workforce for healthcare providers. Dean also leads client innovation programs to enhance service delivery and business outcomes for clients.

The pandemic has shifted priorities and created opportunities to do things differently, and companies are now looking to build more resilient supply chains, none needed more urgently than those within the healthcare system. Dean shares with us how he feels they can get there.

A Multi-Vendor Sourcing Approach

“Healthcare systems cannot afford delays in the supply chain when there are lives at stake. Healthcare procurement teams are looking at multi-vendor sourcing strategies, stockpiling more inventory, and ways to use data and AI to have a predictive view into the future and drive greater efficiency.

“The priority should be to shore up procurement channels and re-evaluate inventory management norms, i.e. stockpiling for assurance. Health systems should take the opportunity to renegotiate with their current vendors and broaden the supplier channel. Through those efforts, work with suppliers that have greater geographic diversity and transparency around manufacturing data, process, and continuity plans,” says Dean.

But here ensues the never-ending battle of domestic vs global supply chains. As I see it, domestic sourcing limits the high-risk exposure related to offshore sourcing— Canada’s issue with importing the vaccine is a good example of that. So, of course, I had to ask, for lifesaving products, is building domestic capabilities an option that is being considered?

“Domestic supply chains are sparse or have a high dependence on overseas centres for parts and raw materials. There are measures being discussed from a legislative perspective to drive more domestic sourcing, and there will need to be a concerted effort by Western countries through a mix of investments and financial incentives,” Dean explains.

Wielding Big Tech for Better Outcomes

So, that’s a long way off. In the meantime, leveraging technology is another way to mitigate the risks that lie within global supply chains while decreasing costs and improving quality. Dean expands on the potential of blockchain and AI in the industry

“Blockchain is particularly interesting in creating more transparency and visibility across all supply chain activities. Organisations can create a decentralised record of all transactions to track assets from production to delivery or use by end-user. This increased supply chain transparency provides more visibility to both buyers and suppliers to resolve disputes and build more trusting relationships. Another benefit is that the validation of data is more efficient to prioritise time on the delivery of goods and services to reduce cost and improve quality. 

“Artificial Intelligence and Machine Learning (AI/ML) is another area where there’s incredible value in processing massive amounts of data to aggregate and normalise the data to produce proactive recommendations on actions to improve the speed and cost-efficiency of the supply chain.”

Evolving Procurement Models 

From asking more of suppliers to beefing up stocks, Dean believes procurement models should be remodelled to favour resilience, mitigate risk and ensure the needs of the customer are kept in view. 

“The bottom line is that healthcare systems are expecting more from their suppliers. While transactional approaches focused solely on price and transactions have been the norm, collaborative relationships, where the buyer and supplier establish mutual objectives and outcomes, drives a trusting and transparent relationship. Healthcare systems are also looking to multi-vendor strategies to mitigate risk, so it is imperative for suppliers to stand out and embrace evolving procurement models.

“Healthcare systems are looking at partners that can establish domestic centres for supplies to mitigate the risks of having ‘all of their eggs’ in overseas locations. Suppliers should look to perform a strategic evaluation review that includes a distribution network analysis and distribution footprint review to understand cost, service, flexibility, and risks. Included in that strategy should be a “voice of the customer” assessment to understand current pain points and needs of customers.”

“Healthcare supply chain leaders are re-evaluating the Just In Time (JIT) model with supplies delivered on a regular basis. The approach does not require an investment in infrastructure but leaves organisations open to risk of disruption. Having domestic centres and warehousing from suppliers gives healthcare systems the ability to have inventory on hand without having to invest in their own infrastructure. Also, in the spirit of transparency, having predictive views into inventory levels can help enable better decision making from both sides.”

But, again, I had to ask, what about the risks and associated costs that come with higher inventory levels, such as expired product if there isn’t fast enough turnover, tying up cash flow, warehousing and inventory management costs?

“In the current supply chain environment, it is advisable for buyers to carry an in-house inventory on a just-in-time basis, while suppliers take a just-in-case approach, preserving capacity for surges, retaining safety stock, and building rapid replenishment channels for restock. But the risk of expired product is very real. This could be curbed with better data intelligence and improved technology that could forecast surges and predictively automate future supply needs. In this way, ordering would be more data-driven and rationalised to align with anticipated surges. Further adoption of data and intelligence and will be crucial for modernised buying in the new normal.

The Challenges

These are tough tasks, so I asked Dean to speak to some of the challenges. Luckily, he’s a patient guy with a lot to say.

On managing stakeholders and ensuring alignment on priorities and objectives, Dean says, “In order for managing stakeholders to stay aligned on priorities, they’ll need more transparency and collaborative win-win business relationships in which both healthcare systems and medical device manufacturers are equally committed to each other’s success. On the healthcare side, they need to understand where parts and products are manufactured to perform more predictive data and analytics for forecasting and planning efforts. And the manufacturers should offer more data transparency which will result in better planning and forecasting to navigate the ebbs and flows and enable better decision-making by healthcare systems.

Due to the sensitive nature of the information being requested, the effort to increase visibility is typically met with a lot of reluctance and push back. Dean essentially puts the onus back on suppliers to get with the times. “Traditionally, the relationships between buyers and suppliers are transactional, based only on the transaction between the two parties: what is the supplier providing, at what cost, and for what length of time. The relationship begins and ends there. The tide is shifting, and buyers expect more from their suppliers, especially given what the pandemic exposed around the fragility of the supply chain. The suppliers that get ahead of this will not only reap the benefits of improved relationships, but they will be able to take action on insights derived from greater visibility to manage risks more effectively.”

He offers a final tip. “A first step in enabling a supply chain data exchange is to make sure partners and buyers are aware of the conditions throughout the supply chain based on real-time data to enable predictive views into delays and disruptions. With well understand data sets, both parties can respond more effectively and work together when disruptions occur.”

As for where supply chain is heading, Dean says, “Moving forward, we’ll continue to see a shift toward Robotic Process Automation (RPA), Artificial Intelligence (AI), and advanced analytics to optimise the supply chain. The pandemic, as it has done in many other industries, will accelerate the move to digital, with the benefits of improving efficiency, visibility, and error rate. AI can consume enormous amounts of data to drive real-time pattern detection and mitigate risk from global disruptive events.”

 

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