Article
4 min read
Srimathi Srinivasan

Supply chain innovation encompasses operational innovation, which involves companies demonstrating an innate ability to adapt their operations and deliver despite regional or global barriers. Such adaptability earns the favour and trust of their customers.

  

That approach begins and ends with information. Supply chain data enables leaders to have foresight and act decisively – but only if those insights are accurate and complete.

  

According to the Data Warehousing Institute, information that is incomplete or inaccurate can lose companies an estimated $600 billion annually. Moreover, a separate study reveals that bad data has yielded delays for 56% of supply chain managers, and of those disruptions, half led to budget overages and 43% prevented companies from meeting customer demand expectations.

  

Supply chain optimisation relies on total visibility. Information on product volumes, partner transport and other variables enables logistics and warehousing leaders to shift from a reactive to proactive stance. This aggressive approach not only enhances operational efficiency, but it also bolsters companies’ resilience, enabling them to swiftly rebound from any unforeseen circumstances.

 

The barriers to optimised supply chain data

 

Data makes things happen. For supply chain professionals, information can spell the difference between a well-oiled workflow and one susceptible to a grinding halt at a moment’s notice due to any variable.   

  

82% of procurement and sourcing industry leaders distrust their data, with many spending almost an hour daily updating supplier-provided insights. What are the most significant impediments to supply chain data?

 

Integration and interoperability

 

Numerous supply chain systems still lean heavily on their legacy foundations. In these more antiquated setups, data storage and sharing are typically more siloed, which can make it difficult for next-generation and legacy solutions to work in tandem. Couple that struggle with many companies’ siloed approach to data storage and sharing, and a host of supply chain resilience challenges present themselves.   

 

 Information lacking the common thread becomes more difficult to integrate into workflows, leaving supply chains vulnerable to delays and disruptions. 

 

Security and privacy

 

Next-generation supply chain technology relies on a unique balance of on-premises hardware and cloud services. This mixture of platforms makes data security and privacy even more paramount, especially as cyber-attackers prey on vulnerable solutions.

 

One area these hackers can exploit is third-party relationships in which supply chains share data with outside vendors. Vendor collaboration is inherent with risk related to data security, and an understanding between both sides regarding security and compliance is key to ensuring data is safely and effectively leveraged.

 

Analytics and insights

 

A critical arm of supply chain resilience is to be proactive via data-driven insights. Still, the accompanying data sets can be convoluted, sizable and difficult to navigate.

 

Particularly, it can be difficult to develop systems and models to help establish clarity within those data sets. Machine learning and predictive analytics are valuable resources, but they’re best utilised in conjunction with experts who can help better understand what that information means.

 

Supply chain resilience hinges on having not only the information and tools to make sweeping decisions but also on-site expertise to read and react to data. Crafting strategies to help address and overcome these challenges empowers supply chains to sustain and scale their operations to ensure uninterrupted functionality.

 

Build a transparent, viable supply chain data process

 

A fictiv report reveals that improved visibility is a priority for 55% of supply chain and manufacturing decision-makers. Data provides the clarity those chains need to see the full picture and maximise their long-term effectiveness.

 

Use the following tactics to create a sustainable supply chain data process:

 

1. Build a needs-based strategy

 

The operations, objectives and outcomes of any supply chain are different. To truly build a strategy set up for success, it’s critical to look at your chain’s specific data needs and make them sustainable and reliable from a data perspective.

 

This starts with identifying the gaps that are present in your supply chain and where data can help improve visibility. From those variables, your organisation can start to develop a rock-solid supply chain data strategy.

 

2. Keep reporting a priority

 

Reporting must remain central to your supply chain, and it can be achieved via several different dashboard variations. Use these visualisations to understand the impact data is having on your operations.

 

These illustrative tools can take many forms, from heat maps to traditional graphs. One such variation is a knowledge graph, which depicts the relationship between data points and makes that union easier to analyse and understand. Though it’s not intended as an end-user visualisation, knowledge graphs can help the data team to lay down the data foundation effectively and analyse the health of the data layout.

 

3. Foster an iterative, communicative and collaborative environment

 

Encourage the whole of your supply chain to keep in contact with one another and work together to see the real benefits of data. Data-driven cultures thrive when lines of communication are open and collaboration is a central value. Empower members of your team to connect with every level of stakeholder to understand the health of the chain and the data it’s deploying.

 

Use those conversations and insights to improve processes and optimise operations. Prioritise select KPIs and use those numbers to evaluate the health of your supply chain and its data. These can be the benchmarks to gauge the viability of your workforce and its data strategy.

 

Investing in visible, reliable and resilient data is an investment in your supply chain’s viability. Data resilience is a central tenet of a supply chain control tower, a platform dedicated to monitoring and managing the information that powers your supply chain. Learn more about it by downloading our whitepaper, How Supply Chain Control Towers Unlock New Levels of Resilience, now.

 

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