Written by Shareen Dhillon and Katie Lewis.
Rapid advances in technology have transformed the way that businesses approach data, increasing the touchpoints via which businesses can create linkages between suppliers, manufacturers, logistics providers and retailers within a supply chain. In this changing landscape, there is a greater need for businesses to understand how to leverage internal and external data to improve internal operations and drive efficiency across their supply chains.
KWM recently hosted a breakfast panel on the data-driven supply chain in Sydney which provided an insight into the role that data can play in enhancing businesses' supply chains. Panellists included Adam Berry (Associate Professor, Data Innovation, University of Technology Sydney) and Peter Woodward (Associate Director Customer Service & Logistics – Colgate-Palmolive), along with KWM partners Adrian Perkins (Mergers & Acquisitions, Industrial & Consumer Sector Leader) and Andrew Gray (Employee Relations & Safety) and senior associate Katie Lewis (Commercial IP & Technology).
Here are six key learnings for businesses interested in adopting data-driven supply chains:
Ensure that your contractual relationships protect your data
There isn't one approach to data in commercial agreements – but data should be carefully considered on a case by case basis. Data should be seen as one of the key commercial drivers of a deal and be factored into pricing and other relevant discussions on privacy and confidentiality. Consider what access you need to data and what access you are required to give to other parties, including subcontractors or agents, for any arrangement to work effectively. As the trend towards longer term procurement and supply arrangements emerges, companies are able to make greater investments in collaborating and sharing data. Businesses should look to "future-proof" agreements by building sufficient flexibility into contractual arrangements to keep up with the rapid pace of changes in technology over the life of an agreement, which might affect the collection or use of data. Be mindful that there may also be constraints on sharing data acquired or created in one contractual relationship with a third party in a separate relationship.
Data should be used as a tool to solve tangible problems
Most businesses make significant investments in collecting and obtaining data without considering the specific problems that it can be adapted to solve. This approach is often costly, complex and ultimately does not further the goal of improving data driven innovation. Instead, businesses should ask, "What problem am I trying to solve?", followed by, "What data will give us insights into solving this problem?". For example, if efficiency is a key concern, then to reduce lead times and get products out more quickly to customers, businesses should focus on data that creates linkages across the supply chain and increases their visibility over what others in the supply chain are doing. Another opportunity may be to turn labour-intensive, manual processes such as manufacturer-retailer collaboration into a data driven, digital relationship with more streamlined, real-time insights. Identifying a concrete problem within a supply chain and making tailored changes that are driven by data-fueled insights is likely to create the greatest impact for businesses in the short to medium term.
People are the key to promoting data-driven innovation within the business
It is essential to ensure that any data-driven approach has buy-in from staff at all levels across an organisation, from procurement and logistics team members to senior management. To ensure that change is managed effectively, consider who will use this data, which parts of the business will adopt any emerging insights and how the insights will be integrated into the business. Alongside this, employers and employees alike must embrace new ways of working, including the rise of automation, which can open up new roles and opportunities for employees to upskill. The easiest way to sell new technologies and artificial intelligence internally is by pitching solutions as having a supplemental function (in helping people do their jobs more skillfully or efficiently) rather than a job replacement function. Flexible job descriptions and enterprise agreements will facilitate the changes in working practices that go alongside this.
Start small – begin with internal data
The utopian ideal of a fully integrated supply chain characterised by collaboration between all key players will be difficult to achieve in practice. The quality, quantity and type of data varies significantly across organisations, and there is a significant amount of assumed knowledge within each business that is required to effectively analyse and interpret each set of data in a meaningful way. Therefore, for businesses beginning their data journey, the best place to start is internally, with something that can deliver tangible value in 6 months. Many sources of data within organisations are currently untapped. However, there is immense value in internal data, given that businesses themselves have the best understanding of the assumptions, constraints and influences that go alongside that data. This is an effective way to quickly demonstrate the value in data analytics and innovation, which can then assist businesses in offering a concrete collaboration proposition to external parties across their supply chain.
For global organisations in particular, there are also opportunities for internal synergies in relation to the use and management of data that represent significant untapped value. For example, different software systems in use across different regions can prevent meaningful global analysis of those data sets. Synthesising and sharing this data may bring about more centralised sourcing or procurement deals and partnerships across global supply chains.
Build internal capability and improve technology to adapt to change
A common roadblock when considering data collection, processing and use within an organisation's supply chain is that there is far more data available that what can currently be processed by most businesses. The reality for most organisations is that identifying, capturing and collecting data is far easier than processing the data and creating a meaningful output. Two components are critical to enhancing the processing phase – first, building people capability through effective recruitment and upskilling of staff, and second, adopting new software solutions that are able to generate enhanced insights from the data. A common assumption alongside the move to data-drive supply chains is that there will be a corresponding increase in automation of the workforce. However, the reality is much less bleak for employees – rather than a large-scale replacement of manual jobs with machines at the expense of human capital, roles are shifting towards a focus on supervisory and technology related tasks.
Delve into data that helps deliver what customers want and need
The digital age has opened up opportunities for businesses to transform their supply chains and embrace B2C relationships alongside more traditional B2B relationships, catering directly to customer wants and needs in new and insightful ways. Using predictive analytics, businesses can anticipate consumer demand, improve their forecasting and work with their suppliers to reduce lead times and drive efficiency, which operates to the advantage of all parties across the supply chain. Tapping into new data sources can assist businesses in identifying and delivering value for their customers, supporting the broad spectrum of consumer tastes and preferences.
Some of the key insights from our panelists are highlighted in the videos below:
