Bridging the Data Gap: How Inaccessible Information is Impacting Australia's Supply Chains

Written by Gordon Maddock, Regional Vice President, Broad Markets at Appian APAC

Australian supply chains are facing significant disruptions due to widespread data accessibility issues. According to new research from Appian, 66% of supply chain employees report struggling with incomplete or inaccessible data, impacting their ability to operate efficiently and meet demands.

The study, which surveyed 300 supply chain workers across the shipping, distribution, and transportation sectors, highlights persistent data-related obstacles despite ongoing digital advancements in the industry. The lack of unified data significantly affects inbound visibility, creating challenges in predicting what, when, and how much inventory will arrive at distribution centres or factories.

The research found that for approximately 41% of supply chain professionals, maintaining operational efficiency is compromised by poor data accessibility. Similarly, 31% of the workforce expressed difficulties completing essential inventory management tasks. This uncertainty around the availability of parts and materials hinders future operational capabilities, impacting production planning and decisions on adjusting output levels.

Australian supply chains rely on digital processes and accurate data to function. Yet, research shows that they are asking their workers to operate with incomplete or inadequate information to manage complex, and often disconnected operations across critical areas such as logistics management, shipment tracking, and schedule coordination. Fragmented, inconsistent or unavailable data creates a lack of real-time visibility. This impacts key functions within the supply chain including inbound visibility, which can have knock-on effects on efficient staffing and warehouse operations.

The Need for Enhanced Data Access and Visibility in the Supply Chain

For stronger business outcomes, supply chain organisations need greater data access and visibility. Many organisations still rely on manual processes and spreadsheet tracking, limiting enterprise-wide visibility across their operations and high priority assets including equipment, machinery, vehicles and infrastructure.

Automating track-and-trace operations in supply chains can also provide new levels of insight for smarter business decisions, as it allows businesses to collect and analyse real-time data at every step of the supply chain. By implementing digital solutions like IoT sensors, RFID tags, and advanced analytics platforms, companies can gain granular visibility into the movement of goods, inventory levels, and potential bottlenecks.

This enhanced transparency enables quicker responses to disruptions, optimises resource allocation, and reduces operational inefficiencies. Moreover, integrating machine learning and AI into these digital systems can more accurately forecast demand, assess supplier reliability, and predict potential risks before they materialise, driving more informed, proactive decision-making. In Australia, where supply chains are vast and often challenged by distance and remote delivery locations, digitisation can be the key to maintaining resilience and ensuring long-term sustainability. The ability to track goods across remote regions in real-time offers businesses a critical competitive advantage, streamlining processes and fostering stronger partnerships throughout the supply chain.

 The Risk of Inaccessible Data

While major digital transformation projects are ongoing in the Australian supply chain sector with 78% of respondents noting their organisations had adopted new digital initiatives within the last five years, data usability has not kept pace.

Currently, 43% of workers identify data accessibility as their biggest challenge. A significant portion also highlighted data overload-—having abundant data but lacking effective tools to analyse and utilise it—as a major issue.

When information is inaccessible or unable to be analysed accurately, it complicates decision-making processes and heightens the risk of operational errors and ongoing inefficiencies across supply chain operations.

To address these challenges, organisations should consider the strategic implementation of a modern process automation platform enhanced by a data fabric. A data fabric is an architectural layer and toolkit that seamlessly integrates data across disparate systems, whether on-premises or in the cloud. By creating a centralised, unified view, it substantially enhances operational efficiency.

Data Challenges Impact Customer and Employee Experiences

Appian research also highlighted the impact of poor data accessibility on the overall customer and employee experience. It found that approximately 39% of workers encountered obstacles in meeting customer service expectations directly due to complications arising from inadequate data access.

Compounding the issue, 33% of those surveyed reported that such data-related challenges adversely affect the employee experience. This dissatisfaction is particularly problematic for Australian supply chain organisations facing skilled worker shortages, where maintaining a satisfied and efficient workforce is crucial to prevent increased turnover, knowledge loss and to ensure workforce stability.

Lacking unified and visible data needed to forecast productivity fluctuations renders proactive staffing decisions impossible. This leads to inefficient labour management, with employers struggling to optimise both, casual and full-time labour. Consequently, this impacts the overall experience of staff and the service output for their customers.

AI: Low Adoption, High Potential

Despite the growing adoption of digital transformation strategies, the integration of Artificial Intelligence (AI) in supply chain operations remains low, with only 3.67% of workers regularly using AI-powered systems.

This slow uptake highlights significant opportunities to enhance supply chain efficiency and responsiveness through advanced technologies. AI has the potential to transform supply chain management by automating repetitive tasks, improving demand forecasting, optimising inventory management, and enhancing decision-making across the entire supply chain.

Low AI adoption rates can be attributed to several factors, including the complexity of integrating AI into legacy systems, a lack of digital skills within the workforce, and concerns over the upfront implementation costs. However, as the benefits of AI become more apparent, especially in areas like predictive analytics and real-time optimisation, the case for adoption grows stronger. AI can sift through massive amounts of data to identify patterns and trends, enabling businesses to anticipate disruptions, streamline logistics, and improve overall operational agility.

Embracing AI, alongside sophisticated data management tools, can revolutionise the way organisations approach supply chain operations. By connecting and streamlining access to data across various touchpoints, companies can transform logistical challenges into growth opportunities. AI can enable end-to-end visibility and predict issues before they escalate, fostering a more responsive and resilient supply chain ecosystem.

For more information, please visit: https://appian.com/industries/broad-markets/supply-chain-orchestration