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Supply Chain Lessons from 2020

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The complexities of modern supply chains prevented many businesses from agilely adapting and responding to the disruption witnessed last year. As the uncertainty and volatility continues, organizations also struggle to deliver on customers’ fluctuating expectations. This affects all stages of the supply chain from production to distribution. At the same time, the profession is experiencing a major talent shortage.

These challenges existed long before the pandemic. But addressing supply chains is necessary if they are going to truly deliver, both in the short term and for long after the pandemic. Some of these are quick wins. But forward-looking businesses are also thinking about long-term strategies to better prepare for the future, whatever it may hold.

During the first wave of the pandemic, many organizations realized they lacked visibility into their supply chains. Everyone needed to locate their stock. Did it leave the factory? Which trucks was it on? Was it in the middle of the ocean? Yet all they could see was when customers ordered it and when it arrived.

With waves of closures and reopenings, many businesses also learned they weren’t all that agile. Some of this stemmed from their systems. For example, an inability to relocate a shipping container to another port. Others originated from suppliers; most goods are still produced in third-party plants.

Maintaining supply planning, visibility, and transparency across partners and geographies is difficult. With disparate systems managing different representations of data, each subsystem integrator user has separate ways of managing and arranging it. Fortunately, today’s technologies can help supply chains realize a single source of truth.

Organizations are increasingly implementing end-to-end supply chain visibility solutions that hook into existing systems. At the same time, automation is helping businesses in the near term. As well as meeting workload challenges, automation reduced the stress on employees, boosted productivity, and tackled the significant talent shortage.

But it’s not just about automating tasks. By adding artificial intelligence (AI) and machine learning (ML), automation can improve itself and learn from its decisions to make better ones in the future. Automation is a great productivity tool and an important part of speed and scale, and with AI and ML, decision-making and productivity continually improve.

Many substantial investments have been currently made in supply chains. Some transformation initiatives involve end-to-end solutions that span blocks, geographies, and partners to synchronize disparate data and systems. They can simulate disruptions in supply or changes in demand to understand the impact on the business, and they’re agile enough to react accordingly. But if you’re not yet ready for that scale of undertaking, augmenting and automating some of your people and processes today will still make for a more agile supply chain.

Source: Genpact

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