Data and data analytics are vital to supply chain management and resilience, particularly in uncertain times. Yet many businesses are slow to introduce or to participate in data sharing and visibility arrangements, and risk missing out on greater accountability, efficiency, and resilience throughout the supply chain as a result. The reasons for this reluctance can be seen through a number of lenses, but legal certainty is central to addressing concerns.
Technology
Connected, digital technologies have opened up new possibilities in communication and supply chain transparency. Decentralised, cloud-based systems enhance information sharing. Communication and collaboration platforms may be shared by stakeholders to monitor, and react, to changes.
Real-time data sources can be used to monitor supplier performance and reduce volatility and uncertainty resulting from internal or external crises, including the pandemic and public health emergency businesses are operating through currently. It can also be used for dynamic rerouting, automatic stock relocation or automatic selection of warehouses based on the proximity of suppliers and customers, and estimation of demand by accessing data on sales, production and distribution scheduling. Data analytics tools, including the use of AI tools, can also be used to identify the key data and to map this in to the decision making process for all activities across the supply chain.
Contracts for the procurement of such new technologies and tools need to be carefully considered, in particular securing the appropriate assurances, transparency, governance and statements of liability. Additionally, if technology is to be used to process personal data, GDPR compliance requirements need to be considered when selecting a supplier and operator of such technology used for data processing in the supply chain.
Economic impacts
Many businesses have yet to digitise their supply chain processes, but rather rely on paper-based exchanges. This can lead to very limited visibility and coordination, and processes being heavily disrupted in times of crisis. This can lead to a failure to anticipate and meet demand and consequent loss of revenue.
Digitisation requires investment and change management, but if properly leveraged it supports visibility, collaboration and communication. Access to real-time data compared with historical data can help businesses to identify cost drivers, support demand-supply balancing, manage warehouse cost by way of stock optimisation, optimise processes, and in turn, identify opportunities to lower costs. This can result in an ecosystem which makes digitisation and data sharing pay by improving economic and financial performance.
Internal impacts
The collection and analysis of data creates valuable visibility and understanding within the supply chain but also greater confidence in the analysis and decision making process. It enables businesses to introduce governance mechanisms and business models to measure the demand signal across the supply chain.
Data collection and data analytics requires businesses to employ staff with appropriate skill sets to collect the correct data, to measure and understand its impact in the supply chain, to surface the impacts to the decision makers and decision making process and to develop algorithms and other measures to synchronise demand and supply. Demand for data collection and data analytics means individuals with these skills are at a premium.
Collaboration
Data can be used to oil the wheels of the supply chain but to achieve these benefits collaboration and the sharing of data is required amongst participants across the supply chain or at least between critical parts of the chain. Collaboration and data sharing require trust. This can be challenging, particularly where the parties in the supply chain are competitors.