Amazon Supply Chain and Logistics

AWS Supply Chain Command Center for resiliency, visibility, and work orchestration

Supply chain disruption costs in the United States topped $228 million in 2021. These costs go beyond dollars with damage to brands, operational costs, delayed cash flows, customer complaints, loss of customers, and loss of productivity. A 2022 survey by The Economist found that 46% of large corporations (with more than $1B revenue) are launching digital platforms to improve supply chain resiliency with 60% prioritizing resiliency over efficiency.

Attracting and keeping knowledgeable talent in the supply chain and logistics market is a continuous challenge. The amount of manual, routine work in employees’ daily lives is no longer acceptable. The undifferentiated heavy lifting takes its toll on morale, and this causes increased turnover. As a result, 64% of supply chain professionals reported a talent shortage in their organizations. Talent shortage is further exacerbated by the frequent need for manual and low value-added tasks. For example, Excel sheet consolidations or ad hoc accesses to multiple ERP instances to get a more holistic view of the situation. This limits the efforts supply chain professionals dedicate to the most value-adding tasks, which, in turn, limits competitiveness of the business overall and its ability to build digital supply chains for the future.

In this blog you will learn about building solutions with AWS for supply chain transformation. AWS encourages you to choose the best approach for your organizational strategy and place in your journey. For customers seeking a ready to deploy applications as a starting point, AWS Supply Chain provides the prebuilt cloud application. AWS Supply Chain can connect to existing enterprise resource planning (ERP) and supply chain management systems without re-platforming, up-front licensing fees, or long-term contracts to mitigate risk and lowers cost with increased supply chain visibility and ML-powered actionable insights. Customers seeking a more customized approach for end-to-end visibility or tailored uses cases should consider the Supply Chain Command Center (SC3) and this blog provides the taxonomy of SC3 for resiliency, visibility, and work orchestration.

SC3 from AWS Professional Services is a prescriptive and automated work orchestration and visibility platform for organizational digital transformations. AWS customers present us with a wide range of challenges, tactical objectives, and strategic aspirations. These are called by many names including reinvention, digitalization, transformation, innovation, optimization, and modernization, and organizations approach them from different angles. But the commonly pursued objectives are similar: supply chain visibility, insights, resiliency, risk mitigation, and automation.

This is where SC3 comes into play. SC3 achieves digital transformation by going beyond traditional visibility tools and dashboards (often called the supply chain control tower). SC3 provides prescriptive recommendations that are orchestrated through systematic automation, task assignment to operators, or a hybrid of human ingenuity plus computer automation that blends these approaches to achieve the best of both worlds.

SC3 aims to maximize business performance by prioritizing the best actions to take when service levels are in jeopardy. It identifies risk with dollar cost impact to drive employee action. When an unexpected event occurs, filtering the daily distractions by assigning value to downstream results minimizes impact and helps decision makers focus on what truly matters. This requires a system of systems going across functional supply chain areas for the full end-to-end process.

AWS customers who benefit from the SC3 span industries including CPG, Telco, energy, automotive, manufacturing, and healthcare.

This post shows how to identify SC3 use cases in your organization and support your supply chain digital transformation. The greatest value of SC3 is realized when you implement its full stack of capabilities. However, the approach is flexible. We encourage you to start with a subset of features for a minimum loveable product (MLP) then scale out at a later stage.

SC3 is more than a typical supply chain control tower

Jeff Bezos, Executive Chairman of Amazon, claims that the further a defect moves downstream, the more expensive it is to fix. The purpose of SC3 is to detect a problem as early as possible, maintain visibility, and make sure that decision makers pursue the resolution urgently. We use this thinking as an overarching tenet for our SC3 design.

SC3 is the system of systems that combines data across the supply chain processes for end-to-end visibility and control. AWS employs reusable modules to accelerate implementations and reduce time to value. The five modules of SC3 are Assessment, Integration, Visibility, Work Orchestration, and Recommendations. The first three modules compose the traditional supply chain control tower. The SC3 emerges with the additional modules of Work Orchestration and Recommendations Engine.

The illustration shows five SC3 modules of Assessment, Integration Hub, Visibility, Work Orchestration, and Recommendation Engine.

The Recommendations module uses Artificial Intelligence and Machine Learning (AIML) to project risk then generate actions based on past behaviors and company rules.

  1. Assessment module – Provides the initial inventory of internal and external stakeholders with the key process steps’ inputs and outputs. Knowing where you’re going starts with a careful look at where you have been. During the assessment, the baseline is established by working backward to identify your company’s supply chain pain points, challenges, key processes, and desired outcomes. Scope and priority are determined for the minimum viable product (MVP) and the full-scale implementation.
  2. Integration module – Ingests data from all relevant sources including internal systems, vendors, carriers, suppliers, and third-party data. The foundational asset, Integration Hub, includes configuration of connectors, logging, alerting and monitoring, scheduling, data validation, and user security. Particularly in logistics, data flows are manually configured with custom development over and over, one by one. Data suppliers and integrators can test transactions while accessing the data catalog to reduce the back and forth that is common when tying together data from multiple systems. A centralized data lake for supply chain that manages all this rapidly changing information.
  3. Visibility module – Relies on the integration of data as the solid foundation. A tightly-knit sense and response system is established between suppliers, manufacturers, distributors, customers, and the end consumer. In the industry, this module constitutes a supply chain control tower, which is defined as a connected, personalized set of dashboards displaying real time metrics and important events across the supply chain. A digital twin represents the customer’s network. This displays the status of key locations, freight lanes, and their participant relationships.
  4. Work Orchestration module – Provides direct labor savings, cost avoidance, and quality improvements from the SC3. In lieu of waiting for operators to take the recommend steps, they can be automated using systematic workflows. Amazon Connect Agent Workspace provides the work orchestration process management and task assignment. Human engagement occurs only when necessary or per company guidelines. The prescriptive tasks guide SC3 operators through dynamic adjustments, replanning, and optimizations dictated by unfolding events. Automation reduces labor costs, avoids manual errors, and speeds up response times to improve delivery. The scope of this module can expand based on customer priority into areas such as product traceability, sustainability assessments, computer vision, and intelligent document management.
  5. Recommendations Engine module – Brings the command center to life using AIML and Internet of Things (IoT). It makes highly reliable prescriptions based on previous outcomes and prior behaviors. These forward-looking projections use relevant conditions to avoid disruptions, and breakdowns. Digital twin models are shown as projections based on the current conditions then for the top recommendations. This approach supports what-if analysis to identify the best targeted outcomes. You can set the recommendations to automatically execute or require approval based on company rules such as total cost, value, or impact. When recommendations are completed, the digital twin model is updated for everyone.

Thus, SC3 is not a single-based solution but rather a data-driven set of modules whose key features are configured on a per customer basis depending on their needs as found in the assessment. Each component is loosely coupled for maximum flexibility and interaction with other company systems. The next section covers the architecture in more detail.

SC3 reference architecture for visibility, orchestration, and automation

The underlying modern application architecture relies on AWS cloud-native functions, loosely coupled microservices, AIML managed databases, and integrated monitoring. Our AWS Solutions Guidance provides SC3 reference architecture.

The diagram shows 10-step SC3 architecture that processes initial inputs into user-ready insights for decision making.

  • Steps 1–3 employ AWS services for data integrations. Together, these are deployed using a prebuilt data integration hub. Standard connectors are included to help eliminate any data management errors and to continually improve data quality. Integrations data management is a critical requirement to avoid “garbage in, garbage out.”
  • Step 4 is data ingestion where the source data is transformed into a standard format and catalogued for easier data analytics.
  • In step 5, the data lake is hydrated using standard models to maintain data quality as new data continues to flow in over time.
  • Step 6 is where the AIML processing occurs for the Recommendations engine.
  • Step 7 provides advanced search of the data lake.
  • Step 8 shows insights and reports for the Visibility platform.
  • Step 9 provides for additional Microservices.
  • Finally, in Step 10, tasks are managed and users interact with SC3 through the application layer.

For coordination of enterprise operations, a complementary element to SC3 is Amazon Connect, which provides work orchestration. Associated actions flow through to Amazon Connect, which is a call center application. However, Amazon Connect contains functionality to support workflows for supply chain processes. Amazon Connect Agent Workspace is one feature where tasks are tracked by group through to completion. The Work Orchestration module employing Amazon Connect Flows implements automation for common scenarios. Amazon Connect Flows also allow for inline AWS Lambda custom code to manage specific automation steps.

SC3 benefits and features by business area

Every industry is different, but they all have supply chains with risks, manual processes, and customer concerns. SC3 provides resiliency by targeting risks, reduces labor costs through automation, and improves customer satisfaction by keeping delivery promises. The flexibility of SC3 allows for deep specialization based on unique industry trends or requirements, such as managing the preventative maintenance processes in mining operations. The existing functionality of SC3 covers the most important business areas.

Customer service

The illustration shows typical SC3 benefits for customer service.

Here is how SC3 provides a major, global automotive manufacturer with greater customer service for after-market parts: the customer’s aftermarket services business unit was looking for ways to improve customer experience. They wanted to see a measurable improvement in Net Promoter Score (NPS) from their automotive dealer network.

Our approach was for the dealer technicians to gain visibility into parts up to date availability in the supply chain to accurately commit to service windows with their customers. SC3 provided parts visibility from suppliers, ETA from manufacturing, and stock availability at various depots. Features delivered included API integrations, EDI processing, shipment tracking, ETA Prediction, and a dealer and technician portal. Our automotive industry leader saw dealer NPS improvement of over 20%.

Warehouse and manufacturing operations

The illustration shows typical SC3 benefits for warehouse and manufacturing operations.

Here is how SC3 assists a global manufacturer in healthcare and life sciences: all of the more than of the 50 manufacturing plants managed by the customer produced KPI reports for daily, weekly, monthly, and quarterly leadership meetings with no consistency.

Our approach was to build an SC3 to standardize KPI reporting across the plants. Deliverables included ERP integrations, data lake, lake house, and standardized process performance metrics. For the data analytics process, the company realized a 70% effort per labor hours savings, largely in the data extraction and initiation manual steps.

Supplier and vendor management

The illustration shows typical SC3 benefits for supplier and vendor management.

Here is how 3M’s supplier and vendor management benefited from SC3 capabilities according to Caitlin Finn, a Senior Software Developer in Corporate Research at 3M: “Our stakeholders were using unimaginably large spreadsheets to attempt to analyze the flow of products and materials through our supply chain… This process was cumbersome and difficult to have confidence in the data. My team and I found a solution for easy plug and play visual analysis that uses many AWS technologies.”

Transportation and Logistics

The illustration shows typical SC3 benefits for transportation and logistics.

Here is how Siemens provided benefits in the transportation industry according to Friedrich Gloeckner, the Data Services Architecture Team Leader with Siemens Mobility: “Our AWS data lake enables not only data scientists and software developers but also about 250 non-technical employees to create custom applications and reports that help maximize the value of the data.”

A leader in transport solutions for more than 160 years, Siemens Mobility – a separately managed company of Siemens AG – is constantly developing its portfolio in its core areas of rolling stock, rail automation and electrification, turnkey systems, intelligent traffic systems, and related services.

Deliverables for the Siemens project included a data lake for supply chain, real time end-to-end visibility of rail network, computer vision rail track inspector, predictive maintenance, and spare parts for repairs demand forecasting. The benefits for Siemens included lower maintenance costs and energy consumption by up to 15%, decrease in unplanned downtime by up to 50%, reduction in unnecessary transfers to maintenance by more than 30%, and an open ecosystem to enable third party applications from leading rail specialists.

Operational strategy

The illustration shows typical SC3 benefits for operational strategy.

Operational strategy relies on each company’s goals. For example, Invista used AWS technology for a transformational shift in how they report manufacturing from predictive maintenance to more accurate demand forecasting. “We take the quality of our airbag fibers extremely seriously”, says Elizabeth Gonzalez, analytics leader at Koch Industries. “That’s why we’re excited that, in addition to the careful manual inspection we’ve always had, we’re now able to analyze automated visual inspection data and use artificial intelligence to identify opportunities to produce even higher-yield fibers. It wouldn’t be remotely possible to do this if all our data was still siloed at each plant site.”


In this post, we introduced AWS Supply Chain Command Center offering called SC3, which provides holistic end-to-end visibility of the supply chain becoming greener and more intelligent. SC3 is supported by a ready integration and AIML platform. It comes with predictive and prescriptive tools to implement a smarter, cognitive, autonomous orchestration of the complex, multitiered fragmented processes in supply chains.

We provided the different components of an SC3, some of which might be already existing in a customer’s landscape of solutions, and others need building and integration as required by the business use case. Our SC3 vision follows modular design to support a multi-phase agile implementation approach and connect process, technology, and people.

Typical SC3 implementation results in benefits such as 20% improved Net Promoter Scores from better visibility, 70% less time spent on data management, 30% reduction in unplanned downtime, 10% lower energy consumption, and 15% savings from preventative maintenance costs – to name a few. We recommend that you start by defining your business use cases, and this is what AWS Supply Chain Global Practice helps with. Reach out to your account team for an introductory workshop with the AWS Professional Services team to assess SC3 implementation and benefits with your supply chain.

Maurice Stratton

Maurice Stratton

Maurice Stratton is an AWS Professional Services Advisor for Supply Chain Transformation based in the United States. Over the past 23 years, Maurice has had the pleasure of improving supply chain and logistics operations through technology with specialties in freight forwarding, fulfillment, and transportation. Prior to joining AWS, Maurice was VP of IT for a global logistics services provider.

Alex Artamonov

Alex Artamonov

Alex Artamonov is a Principal in the AWS Supply Chain, Transportation, and Logistics. He started his Amazon journey in 2017 as a Senior Program Manager in Amazon Transportation Services and he joined AWS in 2020. Alex works with AWS customers to baseline supply chain challenges and jointly innovate and co-create cloud-based and data-driven solutions for the immediate business impact. Alex holds a PhD in Operations Research, and he has 17+ years of cross-industry consulting experience with a long successful track record of efficiency improvement and cost reduction using data, advanced analytics, and technology. Alex works at Amazon EU HQ in Luxembourg.

Mais Rihani

Mais Rihani

Mais Rihani is Head of Supply Chain and Logistics solutions. Mais is a Former CTO. She joined AWS after a twenty-year career with a global transportation, logistics ecommerce, and freight forwarding company. She led the company’s digital transformation for mission critical, global enterprise applications and their supporting infrastructure.

Nikhil Lalla

Nikhil Lalla

Nikhil Lalla is an AWS Professional Services Advisor for Supply Chain Transformation, advising enterprise clients on their digital transformation strategies. He started his Amazon journey in 2020 as a Senior Program Manager in Amazon Transportation Services, where he helped plan, build, and scale the Middle Mile transportation capability of Amazon across North America, successfully led projects to optimize middle mile, linehaul and intermodal transportation strategy. Prior to his time at Amazon, he spent eight years in the supply chain solutions industry, implementing enterprise solutions to optimize clients’ supply chains in North and Central America, South America, and Europe. He is currently based in Atlanta, Georgia, USA.

William Dutton

William Dutton

William Dutton is a Senior Advisory Consultant at Amazon Web Services (AWS), specializing in Supply Chain, Transportation, and Logistics. He joined AWS from an AWS partner in 2021, and he works with AWS customers to help solve their supply chain challenges, jointly innovate, and cocreate cloud-based and data-driven solutions for immediate business impact. Will holds a Ph.D. in Operations and Supply Chain Management and has a track record of designing and implementing data solutions infused with AI/ML across the supply chain to enable enterprises to become more performant. Will is based in London, UK.