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Four ways to step up your supply chain game

by Staff GBAF Publications Ltd
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Four ways to step up your supply chain game

By Kath Brameld, Industry Solution Advisor, Oracle NetSuite

Supply chain operations haven’t been smooth sailing for businesses recently – inflation, volatile customer demand, labour shortages, and extreme weather events all contributing to growing complexity. While governments are taking action in attempt to stabilise the economy, as we’ve seen with the EU’s new Economic Security Strategy, pressure still remains on organisations to increase flexibility and manage risk, all while holding down costs.

Businesses across the world have had to raise their standards in monitoring, analysing, and rebalancing opportunities and risks across the entire supply chain. As a result, the outlines of a stronger supply chain model — one that can withstand volatility as a permanent condition — have begun to emerge. As we step into the second half of 2023, we will likely see more business leaders adopting new frameworks, restructuring operations, and reinforcing digital tools. But in the ever-increasing competitive environment, what should leaders be prioritising to step up their supply chain game?

Creating sustainable supply chains with improved visibility

As the frequency of extreme weather events increases, more people will experience weather-related disruptions to the supply chains they depend on. Thus, we can expect sustainability issues to continue gaining emphasis in the public eye, putting pressure on policymakers and businesses to uphold sustainability practices.

As well as reducing harmful impact on the climate, the business case for sustainable supply chains is stronger than ever. Beyond goodwill, businesses have tended to cost-justify their steps toward sustainability as brand-burnishing exercises to appeal to customers’ sensibilities, to be more desirable to employers, and meet investors’ environmental, social, and governance (ESG) standards. These concerned stakeholders are growing in number and expanding to include business partners and lenders.

The drivers for businesses to be more sustainable are also changing. For instance, they now face government regulation of supply chain emissions and operational resilience. Recently, the Financial Conduct Authority (FCA) submitted a proposal that would require retailers to outline new sustainability labels in an attempt to counter greenwashing. At the beginning of 2023, the European Union also enacted the Corporate Sustainability Reporting Directive, which requires businesses in the EU to disclose climate change related risks and relevant supply chain information among other things. We are seeing this regulatory momentum take place all over the world, and it is only going to pick up pace.

As such, the reporting data needed for compliance will require greater visibility into supply chain sustainability — well beyond Tier 1 supply partners into Tier 2 and beyond. Achieving mandates for greater supply chain resilience in the face of extreme weather events will require advanced analytics to identify variable risk and achieve supply chain agility.

Increasing supply chain agility with a modular approach

Decades of driving toward leaner supply chains to cut costs ultimately ended up catching many businesses flat-footed as volatility surged during the pandemic.

Times have changed — so much so that the leading global reference model for supply chain operations (SCOR) recently underwent its most significant update in over 25 years, with a new emphasis on digitisation. The new model — the Supply Chain Operations Reference Digital Standard (SCOR DS) —covers processes, metrics, skills, and practices across industries, aiming to provide the foundation for digital investments through to 2030. It emphasises market drivers, end-to-end visibility, and buyer-seller collaboration in supply chain design and operations, replacing linear thinking and lopsided buyer-supplier relationships with a more agile, orchestrated approach to supply chain management.

Maintain a customer-centric approach

Supply chains play an increasingly important role in the customer experience (CX), as consumers have become more digitally connected to brands. According to Gartner, more than 60% of supply chain leaders are investing in CX metrics and customer data analytics to improve their supply chain’s ability to sense and respond to what their customers want, need and think. Investing in CX and collaborating across company departments not only help to grow the business, but they also support classic supply chain functions, such as forecasting and optimising inventory.

In the early 2020s, some of the biggest winners in the CX race were the vertically-integrated digitally native direct-to-consumer (D2C) brands. The D2C model engages customers using a hyper-focused, customer-first approach that often includes social media marketing and subscription selling. D2C brands collect a wealth of customer data. But with ecommerce and social growth slowing, many of these brands are now diversifying channels, for example opening stores, even as more conventional brands have looked to add a page from the D2C playbook in their own omnichannel strategies.

Maximise the utility of Artificial Intelligence (AI) and Machine Learning (ML)

Artificial Intelligence is expected to see the fastest growth in the next five years among all advanced technologies ranked in the MHI annual survey — in use by only 15% of respondents today but rising to 73% over the next five years. But are businesses investing in AI realising its full potential?

Supply chain managers face a kaleidoscope of potentially concurrent disruptions at various levels of the supply chain, from demand to supply and out to suppliers’ suppliers, across geographies, channels, and climates. Unassisted, no supply chain team can keep on top of all the potential inefficiencies and fault lines, let alone take decisive action fast enough.

AI, on the other hand, can learn from the team’s past decisions, correlate information across departments, and recommend actions for similar situations. It can then continually analyse resulting data to make recurring decisions that optimise performance and provide recommendations to enhance the supply chain — much of which gradually takes place more autonomously. For example, AI algorithms can be trained to react to unforeseen events in the warehouse to avoid sudden obstacles and accidents on their programmed routes. In another context, AI can identify unfolding weather disasters and how they impact routes, correlating that information with the location of suppliers, warehouses, and other assets to activate backup plans.

Supply chain stress is at its highest level in recent history, even more so than during the 2008 global financial crisis, according to KPMG’s Supply Chain Stability Index. In a situation where environmental and economic factors can’t be changed; it is up to businesses to control how their supply chains are able to react and adapt to unforeseen circumstances – this means rethinking strategies and approaches to supply chains.