Clearing the Path to Resilient Supply Chains for CPG Companies

⇨ Embracing digital-first investments is crucial for mid-sized consumer products companies to enhance supply chain visibility and mitigate risks associated with disruptions.

⇨ Agility and resilience in supply chains, emphasized by 35% of surveyed professionals, can be achieved through investments in newer technologies like AI, data analytics, and creating a robust collaborative environment.

⇨ CPG companies should initiate small-scale AI pilot projects, ensure data integration, invest in employee training, and continuously optimize their AI models to build a more adaptable and efficient supply chain.

Disruptions in the supply chain can significantly impact the success of a mid-sized consumer products (CPG) company, making it imperative for these organizations to embrace digital-first investments to gain better visibility and understand the risks associated with supply chains.

In a recent SAPinsider report on supply chain challenges, 35% of surveyed supply chain professionals emphasized agility as essential to a robust and proactive supply chain, aiming for faster responses to volatility. According to Ron Gilson, Executive Advisor and Principal, NTT DATA Business Solutions-US, supply chains face some level of disruption on a daily basis. Thus, “resilient supply chains, those that are agile, responsive, prepared, and well-informed, are critical to the success of CPG organizations, regardless of size or geography,” he says.

While every organization has different strategies to increase its supply chain resilience, Gilson lists nine potential approaches, many of which involve an investment in newer technologies:

1. Diversification of supply base built on geographies and number of suppliers
2. On-shoring/re-shoring manufacturing and supply base
3. Maintaining buffer capacity in the form of underutilized production facilities or inventory more than safety stock requirements
4. Improving collaboration and data sharing across the end-to-end supply chain to improve visibility, lead time, and responsiveness
5. Consolidation of systems, processes and data into a single integrated landscape, which provides the critical foundation for improved analytics, integrated and predictive planning, automation, and AI
6. Strategic inventory management and real-time inventory tracking to provide transparency of suppliers’ and customers’ inventory positions
7. Improve forecasting accuracy and increase planning horizon augmented by AI to reduce the time to generate a forecast and extend the planning horizon
8. Empower employees with real-time data, analytics, and recommendations for swift, informed decisions
9. Implementing highly scalable solutions to handle complex value chains efficiently

The challenges

However, Gilson points out that CPG companies often put off many of these approaches for later as they juggle multiple competing priorities, such as product innovation, market share growth, profitability, product quality, data security, employee engagement, customer experience, cost management, and sustainability. Additionally, they face cultural resistance to change and technical debt, which can hinder their digital transformation efforts.

For organizations just starting out on their digital journey, Gilson says, “Implementing and leveraging new technologies like AI, RPA, and Analytics on top of obsolete technology stacks is difficult at best, often leading to missed expectations, inflated costs, and a “fragile” solution. Securing these obsolete systems becomes more difficult and costly every year, thereby exacerbating risk.”

In contrast, starting with a modern ERP like SAP S/4HANA and supply chain planning solutions like SAP IBP creates the foundation for leveraging advanced capabilities like AI to build supply chain resilience.

Using AI to harness supply chains

Johann Heydenrych, SVP Advisory and COO, NTT DATA Business Solutions-US, lists the following steps for mid-sized CPG companies to leverage AI for a more resilient and agile supply chain:

Pilot projects: Start with small-scale AI pilot projects to test and refine the approach before scaling up to understand the supply chain’s specific needs and challenges.

Data integration: Ensure seamless integration of AI with existing systems to enable real-time data access and analytics by consolidating data from various sources and ensuring data quality.

Employee training: Invest in training employees to use AI tools effectively. This includes technical training and change management to address resistance to new technologies.

Continuous monitoring and optimization: Regularly monitor and update AI models and algorithms based on new data and insights to ensure they continue to deliver value.

Collaboration and compliance: Foster collaboration across functions and organizations and ensure compliance with regulatory requirements for a holistic approach to supply chain management.

“By following these steps, mid-sized companies can harness the power of AI to build a more resilient and agile supply chain and pave the way for a more efficient and sustainable future,” Gilson concludes.