Transforming Supply Chain Analytics with AI and Machine Learning
Unleash the Potential of Supply Chain Efficiency with the Fusion of Supply Chain Analytics,
AI, and Machine Learning for Informed Decision-Making and Streamlined Operations.
Delivering Excellence & Innovation Across Supply Chain Analytics
Trusted Data’s customised Machine Learning and AI solutions have actively contributed to enhancing supply chain performance across diverse industry sectors. These tailored solutions have enabled organisations to streamline processes and elevate overall efficiency, resulting in optimised operations and enhanced outcomes.
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Forecast Accuracy
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Waste Reduction
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Net Sales Growth
Inventory Turnover Rate
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Logistics Spend Reduction
Our Approach to Delivering AI & Machine Learning Supply Chain Analytics
Predictive Demand & Replenishment
Being at the forefront of most supply chain leaders’ agendas, the ability to leverage demand and replenishment for driving cost optimisation and fulfillment capability is crucial. Trusted Data has been assisting organisations to innovate in this domain.
- ML-Predictive Demand
- Customer Replenishment Optimisation
- Production Planning Analytics
Warehouse Operations & Inventory Analytics
We employ advanced decision science protocols to ensure that warehouse efficiency, demand fulfilment and holding-cost optimisation are delivered in tandem, helping clients to improve OTIF, eliminate excess inventory and unlock cash flow.
- Warehouse Capacity Planning
- Inventory Optimisation
- Order Fulfilment Optimisation
Transport & Logistics Analytics
We employ advanced and bespoke modelling and analytical solutions to derive high performing transport operations spanning scheduling optimisation, network and asset utilisation.
- Routing & Scheduling Optimisation
- Logistics Network Design
- Asset and Infrastructure Optimisation
Supplier Risk and Management Analytics
We leverage advanced analytics to empower Procurement & Supply Chain leaders, enabling them to assess supplier value, mitigate risks, enhance cost management practices and make informed strategic decisions.
- Supplier Tiering and Segmentation
- Supplier Risk Analytics
- Spend Analytics and Optimisation
“The Supply Chain domain has been flooded with a wave of noise related to AI in recent years. Trusted Data’s team are at hand to help transition Supply Chain organisations from low-performing tech assets to best-in-class custom, objective AI and Analytical Solutions that drive top and bottom line growth”
Successful Supply Chain Analytics Projects
Presented below are several instances of our accomplished Supply Chain projects, achieved through the implementation of Machine Learning and AI solutions for our valued clients.
Our customised data and analytics training solutions for supply chain
As analytics and technology continue to evolve rapidly within the supply chain landscape, organisations face challenges in adapting their internal resources to keep pace with these changes.
Trusted Data is dedicated to supporting emerging supply chain functions in enhancing their teams’ expertise and understanding of implementing AI solutions and analytics in supply chain operations. Our training services are tailored to address the specific focus areas and analytics experience levels of our clients, ensuring customised content delivery.
Contact us today to learn more about empowering your workforce to make data-driven decisions, thereby improving efficiency and resilience throughout your supply chain.
"A survey by a global consulting firm across +300 supply chain executives found that when tasked with identifying key hiring challenges, 58% of respondents identified talent shortage in data analytics as major hurdle".
Introduction to Supply Chain Analytics
Advanced Supply Chain Analytics Techniques
Strategic Supply Chain Decision-Making with Analytics
Introduction to supply chain analytics: Embark on an enlightening journey into the world of supply chain analytics with our foundational course, designed to ignite your passion for this dynamic field. Immerse yourself in fundamental concepts, grasp essential terminology, and uncover the game-changing potential of data in reshaping the landscape of supply chain management.
- Introduction to supply chain management
- Basics of analytics and applications in supply chain
- Key performance indicators in supply chain analytics
- Data collection, cleaning, and preparation
- Introduction to analytics tools such as Tableau for supply chain data analysis
Duration: 4 weeks (self-paced).
Target Audience: Beginners in supply chain management, analysts looking to transition into supply chain roles.
Advanced Supply Chain Analytics Techniques: Explore advanced strategies in supply chain analytics, designed to deepen your understanding of key techniques. Delve into sophisticated topics such as forecasting, optimisation and risk management, equipping the audience with skills to navigate complex challenges and drive superior supply chain outcomes.
- Advanced forecasting methods
- Time series analysis, demand forecasting
- Supply chain optimisation techniques
- Inventory management analytics
- Supplier performance analytics
- Risk assessment and mitigation in supply chain
Duration: 6 weeks (self-paced).
Recommended prerequisites: Basic understanding of supply chain analytics or completion of Level 1 course
Target Audience: Supply chain professionals, data analysts seeking to specialise in supply chain.
Strategic Supply Chain Decision-Making: Embark on a transformative journey to equip you with the decision-making prowess to craft data-driven strategies that elevate operational efficiency and foster innovation. Dive deep into analytics techniques, trends & technologies in supply chain management, collaborate on real-world projects and receive mentorship from industry leaders.
- Strategic supply chain design
- Network optimisation techniques
- Supplier relationship management with analytics
- Sustainable supply chain practices using insights
- Case studies on successful supply chain transformations
Duration: 8 – 12 weeks (self-paced).
Recommended prerequisites: Proficiency in supply chain analytics or completion of Level 2 course
Target Audience: Supply chain managers, senior analysts, executives involved in strategic decision-making
