Data and AI Driven Supply Chain in Manufacturing

Else Beate Gullestad
Else Beate Gullestad,

The last six months have once and for all proven how critical and sensitive supply chains are. During a joint Microsoft/Cognizant seminar, speakers from Orkla, Wallenius Wilhelmsen and the organizers shared their views on how to build a more resilient, intelligent supply chain fueled by data, analytics and AI.

As many companies find themselves in the turmoil caused by the Covid pandemic, the level of uncertainty, complexity, and volatility is at a record high. In turbulent times, the need for speed in business is increasing; the cost of late responsiveness and lack of smart decisions have become painfully obvious across industries.

If there ever was a need to accelerate digitization, it is now. According to Patrick van Loon, Manufacturing Industry Executive at Microsoft, companies that used the financial crisis in 2008 to truly reinvent themselves have significantly outperformed their peers in recent years.

However, supply chains are a complex, data-intensive process characterized by data silos, a mix of structured/unstructured data, and lack of standardization. To make speedier, better-informed decisions, companies need easy access to data, fast analytical workflows, and actionable insights for the end-user. To optimize supply chains, AI can play a key role.

To discuss your specific supply chain situation, sign up for a FREE 1-day workshop 

Data as a foundational enabler
How can new AI-based insights be realized then? Anoop Sharma is leading Cognizant’s AI and Analytics practice in the Nordics (learn more about cross-industry data and AI trends in the Nordics and how companies are adopting data and AI to solve problems in the post-Covid world). He says that data modernization is essential to succeed; it helps companies get a coherent view over their operations and lays the foundation for growth and optimization. It also constitutes the digital backbone that can leverage the potential of AI and machine learning.

Opportunities for AI are everywhere in the supply chain/logistics space, eg. to improve forecast, to cluster suppliers by performance, trending analysis, resilience scenarios, prediction of performance, quality monitoring and trends, contractual compliance, and last but not least the creation of recommendations when optimizing conflicting objectives. This requires an integrated platform where multiple sources come together and data is transformed into insights through AI paradigms.

To help data come to life, Cognizant has a structured Digital Engineering approach realized through PODs, cross-functional, cohesive high-performing teams. PODs leverage automation and accelerators to foster scalability across the enterprise, with a strong focus on the business outcome. It’s done through seamless transition across engagement phases in an effective manner, all measured by well-defined KPIs.

For manufacturing, in particular, Anoop Sharma sees many relevant use cases, such as modernizing remote work capabilities, forecasting accuracy, inventory/fleet management, improving cash position, and building supply chain resilience.

Digitalization at shipping giant
Wallenius Wilhelmsen is a 150-year old Norwegian shipping company. Environmental challenges combined with technology opportunities mean that every aspect of its operations will change in the coming years, according to Donal Duggan, responsible for Performance Management, Planning, and Analytics.

WWL is currently in the midst of a fundamental digital transformation, where connectivity, IoT, AI and big data will increase efficiency, help meet regulations and cut carbon emissions. The change is also driven from the customer side. As an example, 55 vessels are now streaming performance data to an onshore big data platform, where engine performance is tracked to improve efficiency and save fuel.

Based on his experience, Donal says that taking advantage of modern technologies and the opportunities they provide is about business strategy, planning and competence. It also requires mapping what’s available and valuable to the company; you should structure your ambitions to take the step from hype to a tangible plan. A modern data platform is essential to make it all happen – it will help you consolidate, manage and make data available across the enterprise to support digital transformation. 

Data as an asset at Orkla
Stig Sjursen is VP for Big Data & Analytics at Orkla. He says that the company immediately got its act together as Covid hit. Being a major supplier of food, cleaning and hygiene products, Orkla’s focus has been on securing stable, uninterrupted operations.

From a supply chain point of view, Orkla has been challenged by many local systems. More than 50 different ERP systems are now being consolidated into two systems. Acknowledging the value of data, preferable high-quality master data, as the most fundamental piece has been essential. It is now treated as an important asset across the value chain. Reliable data is also the foundation for AI and new insights.

Stig, together with a data management team and an analytics team, has put great emphasis on collecting and combining data across the complex supply chain. They have also “demystified machine learning and artificial intelligence” and are using embedded solutions from ERP vendors. Orkla also runs a few IoT pilots.

Learn more about the Microsoft/Cognizant partnership here and also check out our dedicated manufacturing web

Offering- Sign up for 1-DAY FREE WORKSHOP
Finally, Cognizant and Microsoft would like to offer a 1-day free workshop to discuss your situation.

The structure of the workshop is as follows:

  • Supply chain/logistics overview 
  • Opportunities 
  • Impediments 
  • Art of the possible, use cases examples 
  • High-level use cases identifications 
  • Solution items to remove impediments 
  • High-level roadmap 
  • Next steps/PoC 


The optimal workshop audience could be :

  • Business decision-makers
  • Supply chain analysts
  • Relevant IT personnel