C-suite leaders face a common challenge of trying to predict what new business models will take hold out of the convergence of developing trends, evolving technologies and shifting market structures. Specific to the food system, this complexity involves how to best approach changing regulatory requirements, new consumer expectations and the need to enhance supply chain resilience. Value networks are positioned to meet these transparency challenges as an integrated business model across source-to-consume participants.
Transparency issues threatening the food value chain reside largely in a physical-digital disconnect associated with its products and services, restricting insights as goods are exchanged across stakeholders. Much of the disconnect is a result of the food system’s inherent production success within the physical domain. After the first two industrial revolutions birthed mechanization and standardized manufacturing, the global food value chain became highly efficient at sourcing, processing and delivering affordable products at scale.
As the food industry continued to invest in large production systems, it was typically more cost-effective to add internal labor than to digitize. This was, in part, due to technological immaturity. The realm of vision-based artificial intelligence (AI) and robotics could not yet handle many of the required processing tasks at high speed, especially with complex biological products such as meats.
The tendency to add headcount rather than digitize extended beyond processing to areas such as planning, demand forecasting and procurement. Consequently, much of the industry still functions on internal spreadsheets scattered across hundreds of employees. As companies expanded their footprint globally, digital transformation efforts with enterprise resource planning (ERP), supply chain management (SCM) and other applications occurred in isolated pockets, resulting in a disparity of systems and master data both within and across business units.
Apart from complications with internal systems, external sourcing issues present problematic transparency challenges within the food supply chain. Depending on the ingredient, product or by-product, the procurement network for major brands may range from thousands to hundreds of thousands of independent producers spanning the globe. Many of these smallholder farmers are in rural settings and remain highly analog. However, even if producers are recording data, the (oftentimes multiple) aggregation points are not equipped to associate data with blended batches of product.
Digital hindrances across the supply chain may not only result in costly inefficiencies but can also contribute to friction between the food industry and evolving societal standards. As the waves of digitization that marked the third industrial revolution led to a world of hyper-connectivity, the arrival of social media ushered in new expectations toward transparency and information accessibility. This has impacted the food industry with modern consumer trends and regulatory requirements in monitoring and reporting issues with food safety, quality and sustainability. Failures in these areas can result in costly product recalls and substantial brand damage with multiplied ramifications from negative social media.
Overcoming these challenges may require a new business model that will create the needed visibility and verification across an ecosystem of disparate systems, business units and supply chain partnerships. Without such a model, opacity can continue to hamper a food provider’s ability to manage complexities, thus amplifying risk and reducing value capture in four primary areas: brand protection, supply chain inefficiencies, consumer loyalty and regulatory compliance.
Reducing complexity caused by a lack of transparency involves the establishment of value networks. Within the context of the aforementioned challenges, a value network is a collaborative relationship across multiple participants that embraces digital conduits to capture specific value-based incentives. These networks are designed to utilize multi-party data for alleviating risk and creating new areas of value without disclosing information that may be harmful to participants or encourage predatory behavior.
Value networks consist of the three primary components: stakeholder involvement, ecosystem governance and augmented intelligence.
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Source: fooddive.com