AWS Cloud Enterprise Strategy Blog

SCM: Supply Chain Muscling or Modernization?

In my customer conversations, Supply Chain Management (SCM) has become almost as constant a theme as people and agility. The last two years of pandemic and other disruptive events, along with the necessity to achieve sustainability objectives, have shocked companies into realising that they don’t necessarily know as much about their supply chains as they thought they did. Two of my colleagues, Dimitrios Armenakis and Sebastian von Berg, share their observations of what the impetuses for change are and how you can start on your own journey to become both efficient and effective.  Phil

SCM: Supply Chain Muscling or Modernization?

Recent events have emphasized the importance of SCM in delivering business outcomes. A perfect storm of disruption, customer demand, and labor shortages have contributed to make insights into supply chains and the ability to respond rapidly strategic necessities for companies.

Many enterprises—especially ones with a global footprint—have seen their revenue and share price plummet due to supply chain disruptions. Their responses have often been reactive: throwing more people and money at procurement and planning or reverting to resource-intensive processes to identify and mitigate risks. Events such as the pandemic, Brexit, more frequent climate-triggered natural disasters, and the infamous Suez Canal blockage have impacted industries globally. The common denominator is SCM.

In parallel to this, the pandemic has also been a catalyst for new customer behavior. Business-to-business (B2B) customers and end consumers have demanded more, faster. They want companies to agilely react to their needs. Switching costs have often become less significant with competitors now easily compared to each other in one webpage.

Finally, recent socioeconomic changes have also disrupted the labor market, creating global competition for talent with location no longer being a barrier. The skills needed in the workplace are evolving quickly, requiring a deeper understanding of data and technology in many roles. It’s a change that has forced enterprises to focus on employee experience, including talent attraction, engagement, and motivation. In few places has this been as true as in SCM. A deep understanding of weaknesses in a company’s supply chain, risks downstream with suppliers or suppliers-of-suppliers, and the need to fully understand the supply chain for Scope 3 emissions all contribute to this demand [1].

With these compounding changes, applying brute force by throwing more money and people at the problem—or “muscling” your supply chain—simply cannot keep up with business and customer needs. Taking a more strategic approach to supply chain modernization can make product supply networks more resilient and cost-effective, and speed up operations to keep up with customer sentiment while inspiring talent through continual opportunities to innovate.

There’s good news in how to achieve this: technology has also evolved at a rapid pace, with cloud-based services now able to address many of these challenges. Technologies like Artificial Intelligence (AI) and Machine Learning (ML), analytics for big data sets, and IoT-enabled devices have opened the avenues for supply chains to be innovative and resilient. Businesses that are making good use of these technologies are becoming the new leaders in their markets. The availability of rich, real-time data within supply chains is allowing businesses to draw insights into their operations that were not possible in the past. It has enhanced and encouraged collaboration upstream with suppliers and downstream with trading partners. Previously siloed enterprises with their siloed data are opening up. These days, partners want to collaborate with you closely and make it a win-win situation in the end-to-end supply chain, enabled by the broad availability of data lakes and blockchain technologies.

Most organizations aren’t there yet. A recent study from McKinsey about the state of planning processes showed that approximately 80% of companies still follow traditional sales and operations planning (S&OP) processes, with limited real-time decision-making or automation [2]. These processes often depend on unreliable sources of data and outdated IT systems, with coordination limited across functions. We know the results of such simplistic approaches: product shortages, increased costs from stock, inventory write-offs, and inefficiencies up and down the value chain.

Industry leaders and innovators have begun to embrace next-generation solutions, with the rest of the field starting to follow. Modern solutions incorporate AI, ML, and data analytics to speed up decision-making, paving the way for autonomous planning. AI/ML with real-time data from internal and external sources allows end-to-end visibility of material flows and supply chain disruptions, in turn enabling the creation of agile supply chains by mitigating them. Using data to drive actionable insights along with decision support platforms and predictive and prescriptive recommendations is critical to be agile and mitigate supply chain risks. Automation enables cost-effective, high-quality work at scale. These technologies and more, including robotics connected devices, can now integrate with people to accomplish tasks together with greater efficiencies in the operations.

Supply chains need to reinvent themselves and stay ahead of the evolving business needs or they will become a stalling weight for their businesses. Supply chain executives need to ask themselves three questions and take relevant action. First, is my supply chain resilient and can it quickly overcome disruptions? Then, is my supply chain versatile enough to deliver different go to market, customer, and business needs? Finally, is my supply chain elastic enough to scale up and down based on demand and to deliver the “and” on cash, cost, and customer service? If the answers are not firmly positive or if you believe that there is still opportunity then there is need for change.

And then come the questions that we get frequently from supply chain executives who are eager to modernize their supply chains: “Where shall I start?” or “I have already made IT investments and long-term plans, should I really now add more complexity and cost?” Embarking on a digitalization journey should not be overwhelming. Think big, start small, and scale fast. Start with the end in mind, don’t constrain your thinking, and use recent learnings from what has shaken your operations to define what your supply chain should look like over the next five years to meet customer and business needs. Then start with a small but representative value chain to pilot and prove the change. Break the customer or business challenge into small problem statements, and try to solve one at a time. Bring together all your data sources, break down silos, and start using the vast array of tools the cloud gives access to such as ML to gain insights that have never been considered before. No need for more IT capital to be spent on having to start by standardizing platforms or systems; instead, connect the data and use advanced analytics to help show you the direction towards harvesting new business value. Once the value is revealed, scale fast. By reaching this point you have already explored the first steps of modernization including creating a data lake, introducing machine learning, and having granted your supply chain end-to-end visibility, all foundations to building an integrated and resilient supply chain. And you’ve paved the way towards an automated and then possibly fully autonomous supply chain.

Are you still wondering whether you should modernize or muscle your supply chain?


[1] Description of scope 3 emissions, Environmental Protection Agency, 2022

[2] Autonomous supply chain planning for consumer goods companies, McKinsey, March 2022

Phil Le-Brun

Phil Le-Brun

Phil Le-Brun is an Enterprise Strategist and Evangelist at Amazon Web Services (AWS). In this role, Phil works with enterprise executives to share experiences and strategies for how the cloud can help them increase speed and agility while devoting more of their resources to their customers. Prior to joining AWS, Phil held multiple senior technology leadership roles at McDonald’s Corporation. Phil has a BEng in Electronic and Electrical Engineering, a Masters in Business Administration, and an MSc in Systems Thinking in Practice.

Dimitrios Armenakis

Dimitrios Armenakis

Dimitrios Armenakis is a Principal Consultant Supply Chain, Transportation & Logistics at Amazon Web Services (AWS). In this role, Dimitrios works with C-level executives across different customers and industries to transform their Supply Chain Operations by applying disruptive technology, systems and services and to help them create a digitalization roadmap including Machine Learning, AI, Digital Twin, IoT and E2E Control Towers. Prior to joining AWS and for the last 20+ years, Dimitrios held multiple senior leadership roles heading Global and Regional Supply Chains in companies that are mastering digital Supply Chains like Amazon Transportation, Procter & Gamble and others. Dimitrios has a BEng and MSc in Mechanical Engineering and a MSc in Applied Economics and Finance.

Sebastian von Berg

Sebastian von Berg

Sebastian von Berg is a Principal Consultant in the Amazon Web Services (AWS) Supply Chain, Transportation & Logistics Global Specialty Practice. He works with clients across a range of industries looking to leverage technology to transform their supply chains. Prior to joining AWS, Sebastian spent 12+ years in the automotive industry, in management consulting, and as a startup founder. Sebastian holds a BSE in Mechanical Engineering, an ME in Industrial Engineering and Operations research, and an MBA in Management.