The role of data in making supply chains more resilient

Out-Law Analysis | 24 Sep 2020 | 1:01 pm | 6 min. read

Businesses should invest in technologies that allow them to connect with suppliers and make use of real-time data that can enable the whole supply chain to operate more efficiently on the basis of better informed decisions.

The collection, sharing and analysis of the data created across the supply chain can be of tremendous value as it creates greater visibility and agility within the supply chain. However, the use and sharing of data can trigger obligations under data protection law, be subject to potential restriction under competition law, and face further legal and contractual constraints, including where the data qualifies as intellectual property (IP).

Digitising supply chains and meeting the compliance challenges that entails will, though, improve the quality of data at business' disposal and ultimately help make supply chains more resilient.


This article is part of a series on the subject of supply chain resilience.


The insights data can offer

Increased visibility and agility within the supply chain has never been as important as now. Businesses have faced and continue to face the challenges that Covid-19 and economic recovery from the pandemic have presented, and Covid-19 is not and will not be the only crisis which the supply chain has met and will meet. 

Data can reveal all aspects of the running of the supply chain and also support the management of the process. It can be used to model solutions and implement them. Data, particularly live data, provides valuable insights into the status of the supply chain, as well as better connectivity between those in the chain, such as in relation to service, flow, inventory, cost and efficiency. It allows visibility of sources of uncertainty, volatility and variability and enables the diagnosis of issues and creation of buffers where they are required. It enables businesses to introduce techniques to take out the peaks and troughs so that the demand signal can be more stable and there are fewer surprises, synchronising demand and supply. Data collection can be used to measure the heart beat of the supply chain.

Wyn Davies Cerys

Cerys Wyn Davies

Partner

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

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.

Appt Stephan

Dr. Stephan Appt, LL.M.

Rechtsanwalt, Partner, Head of German TMT

Tackling compliance and other legal concerns in an appropriate manner and introducing appropriate governance can bring the benefits of the sharing of better quality data, with better insights and greater resilience for the supply chain and business

Trust and privacy are core issues in this context and are traditionally obstacles to data sharing in a supply chain. However, smart solutions are being implemented, such as blockchain-based data trust sharing mechanisms for supply chain use cases. In some cases setting up data trusts that operate on the basis of specifically defined rules between the stakeholders of such a trust can be a good instrument to manage each party's data-sharing strategies, in particular to share only what is required and maintain control of their information.

Suppliers in the supply chain have traditionally been reluctant to share business data as they have concerns about sharing business confidential information and trade secrets, or because of a fear that doing so would risk breaching competition law. These concerns can be addressed by legal regulation.

Legal regulation

Concerns in relation to the sharing of confidential business information and data can be addressed by assessing carefully what data can usefully be shared. Digital secure locks or even distributed ledger technology can be helpful. Appropriately drafted confidentiality agreements can also be used to ensure the information is shared within a limited group and for specified limited purposes.

The competition law constraints on discussions between competitors need to be understood and properly addressed. However, fears can be allayed by advice on the scope of discussions and sharing which is permitted between competitors.

There are additional legal challenges to collecting and sharing data, particularly if personal data is included, which can act as a deterrent. However, tackling these compliance and other legal concerns in an appropriate manner and introducing appropriate governance can bring the benefits of the sharing of better quality data, with better insights and greater resilience for the supply chain and business.

Where personal data is among the data potentially to be shared it needs to be considered whether the sharing of such data is actually required or whether equivalent value and greater flexibility can be secured from anonymised or aggregated data.

If personal data is required compliance requirements need to be addressed. This will necessarily involve ensuring a record of all processing activities; meeting obligations on lawful processing; complying with the principle of purpose limitation – not processing personal data in a way incompatible with the purpose for which the data have been originally collected; ensuring transparency for data subjects; and implementing appropriate and proportionate security measures to safeguard data against accidental losses, unauthorised access or cyber-attacks. Additional measures may be required depending on the nature of the business, and different approaches may apply across individual countries including EU member states. However, compliance will lead to the processing of better quality data.

Even where the data that is to be collected and shared is not personal data there are a number of issues which will need to be addressed. These include issues around the ownership and rights of use of the data. In addition, businesses should seek assurances as to data accessibility, quality, and use for the intended purpose. Liability issues may also arise depending on the use that is to be made of the data. In each case the terms of collaboration and data sharing between the businesses in the supply chain should be clearly addressed and agreed.

Another issue to be addressed will be the employment terms of the data analysts and algorithm/AI developers. In particular, strong confidentiality obligations will be required in relation to the data and data insights which they handle, both in relation to their employer and the others across the supply chain.

Covid-19 has brought unprecedented disruption in the supply chain but the lessons learned from the collection, analysis and sharing of data will not only help businesses deal with immediate issues of supply and demand, but also to build a more resilient supply chain for the future.