Op-ed by Ruediger Hagedorn, Data-Driven Value Chain Director, The Consumer Goods Forum.
In today’s ‘age of AI’, how companies use data is a driving force for competitiveness. Companies that harness insights from their supply chain data can make more informed decisions that lead to growth and profit. Those that don’t, risk being outpaced.
According to the latest State of Consumer Products report, 76% of FMCG industry leaders agree that innovation is becoming more complex and increasingly requires analytics and AI. Yet fewer than a third believe their current approach gives them the essential competitive edge.
Recognising data’s increasing value and responding to growing consumer and regulatory demands, companies are taking the following approaches to stay ahead:
1. Invest in quality, integrated data
Historically, many consumer goods companies have struggled with fragmented data locked in silos across departments, regions, and different manufacturing processes.
The first step is to improve data quality and integrate sources, ensuring data interoperability. This allows decisions to be made based on reliable, holistic insights. By using real-time analysis from across value chains, businesses can adjust production based on live demand signals, optimise delivery routes to lower emissions and respond to disruptions with agility and more.
2. Enable advanced predictive analytics
Integrated, high-quality data is the foundation on which companies can build effective predictive analytics, using AI as the user interface for Machine Learning, which can identify opportunities to improve end-to-end supply chain agility. Ultimately, this gets companies closer to the ideal scenario: having the right product in the right place at the right time, produced more efficiently.
For instance, predictive analytics offer more precise demand forecasting and inventory management. By using AI, Unilever Tinsukia reported that it drove a 35% increase in forecast accuracy for customer purchase orders and a 92% reduction in the frozen period for goods.
Predictive analytics can also help avoid quality defects in the supply chains, reducing waste at both the manufacturing and market level. Unilever Dapada saw a 50% decrease in manufacturing defects when the company developed a digital twin that simulated a product formulation change, allowing them to anticipate and address potential defects before they occurred.
Building consumer trust with transparent data
While smarter data use can significantly optimise the internal supply chain, its benefits extend far beyond operational efficiency. The same principles of quality and interoperability can be leveraged to build stronger connections with consumers. Now more than ever, companies are adopting digitisation on product packaging to trace product data more efficiently across the value chain.
A good example of this is the transition from traditional barcodes to QR codes that align with GS1 standards. By implementing this, companies can share a product’s journey with their customers, providing information on where it was made, how it was sourced, and what ingredients it contains.
Looking ahead, the pace of change is only accelerating. Supply chain data is already moving from operational tracking to supporting decision-making across business functions.
While individual companies are making impressive progress, the real breakthroughs are happening through collaboration.
The Consumer Goods Forum’s Data-Driven Value Chain initiative promotes pre-competitive knowledge sharing and innovation. This is achieved by enabling companies to build foundational data infrastructure, accelerate the adoption of new technologies, and provide guiding principles for the responsible use of data, technology, and AI. Ultimately, this creates tangible opportunities for efficiency and productivity improvements between manufacturers and retailers across the value chain.
The Initiative is also working closely with other CGF Coalitions such as the Climate Transition to simplify ESG Data Exchange and enhance their recent release: the Common Data Framework. These projects aim to facilitate the secure flow of sustainability data. By promoting interoperability on emissions and deforestation data and how this data is collected, we enable companies to cut down on manual reporting, improve transparency, and meet evolving regulatory demands without sharing sensitive data.
For an optimised end-to-end value chain, consumer goods companies need to embrace a data-first mindset.It is essential for leading performance on margins, efficiency and sustainability, as well as building consumer trust. They can start today by making the most of opportunities from pre-competitive collaboration and acting on these building blocks to compete better.
Learn more about The Consumer Goods Forum’s Data-Driven Value Chain initiative here.
