Data, Analytics, and Automation for Resilient and Agile Supply Chains

⇨ Over the years, supply chains have increasingly focused on customer needs, forcing organizations to create efficient and speedy systems.

⇨ Organizations need integrated planning and analytics capabilities that rely on a centralized, enriched, and harmonized data foundation.

⇨ Data and analytics form the foundation for developing resilient and agile supply chains capabilities while automation provides the fundamental support.

Building Resilient and Agile Supply Chains Leveraging Data, Analytics, and Automation

The difficulties associated with supply chains risks have increased rapidly. These challenges come in various forms, such as significant changes in demand and supply, unexpected disruptions affecting sourcing, manufacturing, and distribution, an increase in the number of product offerings, and geopolitical volatility. The pandemic has only heightened these challenges as businesses strive to adapt their supply chains to meet the demands of the VUCA (Volatile, Uncertain, Complex, and Ambiguous) business environment.

Over the years, supply chains have increasingly focused on customer needs, creating efficient and speedy systems. Although these factors propelled organizations to develop agile supply chains, they also made them vulnerable to risks and disruptions, which in turn highlighted the need for supply chain resiliency. These challenges have expedited supply chain digital transformation initiatives in various industries and data, analytics, and automation play a crucial role in this digital transformation effort.

According to SAPinsider’s latest research report Building Resilient and Agile Supply Chains Leveraging Data, Analytics, and Automation, organizations need integrated planning and analytics capabilities that rely on a centralized, enriched, and harmonized data foundation. This need arises from the challenges organizations face with their current set of tools and technologies in terms of a lack of integration with other systems, which significantly contributes to data fragmentation. The key challenges that organizations face are:

• Poor integration capabilities with other systems
• Fragmented data sources and data quality issues impact the quality of insights
• Lack of internal skill sets to make the best use of tools available
• Data and analytics latency

The survey findings also suggest that organizations intend to adopt a phased approach to develop their supply chain data and analytics capabilities while addressing the primary challenges in their existing portfolio. Organizations are currently investing in technologies that will help in establishing a robust data foundation, integrated planning solutions, and analytics solutions. In the medium term, they focus on more advanced technologies such as edge analytics, AIoT, and Industry 4.0. With real-time visualization, planning, and execution being critical for developing resilient and agile supply chains, data and analytics form the foundation for developing resilient and agile supply chains capabilities while automation provides the fundamental support.

The research findings suggest that organizations should consider the following steps for building robust data and analytics capabilities in their supply chains:

• Understand how data insights can transform customer experience strategy.
• Data tools and technologies provide ample opportunities to build solutions that can address unique inventory management challenges.
• Build comprehensive process hubs that are tightly integrated with supply chain control towers.
• Make integration across planning and analytics systems a critical imperative.
• Upskilling can help organizations extract value from tools.
• Develop adoption roadmap for strategic change management.