November 2024
The recent ‘Towards a 90% No-Touch Spares Supply Chain’ workshop in Johannesburg sparked vibrant discussions on the role of AI in the spares supply chain. While some see AI as a game-changer, concerns remain over its impact on jobs. We believe it’s time to reimagine the roles of inventory professionals, using AI as a tool to enhance job functions. By automating repetitive tasks, AI frees up people to focus on what they excel at—creative problem-solving.

Unlike humans, AI doesn’t run on coffee.

AI is fuelled by data – lots of data.

For example, if you aim to predict parts’ criticality on a High-Low scale, you need:

  • a clear blueprint, and
  • enough historical data to validate those predictions.

Many asset owners have shelves full of slow- and non-moving spare parts, meaning demand data is about as plentiful as unicorn sightings.

Is this a roadblock? Actually, no.

Probabilistic models, such as Croston forecasting and compound Poisson distributions, remain highly effective for managing slow movers. These models are sometimes mistaken for AI, but in reality, they have been in use for decades and continue to outperform AI when data is limited.

Key applications: Where AI truly adds value

Exploring the potential of AI means focusing on areas where data is readily available and where existing models fall short. AI’s superpower lies in enhancing decision-making processes where data is sufficient. Gordian and Lanza collaborate with universities and other industry partners to identify these high-potential domains.

Here are two examples of how we see AI can be applied effectively:

    1.  Streamlining exception management –
      The spares supply chain is full of data anomalies that can disrupt operations. Identifying these anomalies is step one; automating their resolution is where AI shines. By using AI, planners can focus on the “exceptions that matter”, freeing them from repetitive administrative work. This shift allows employees to engage in higher-value activities, like creative problem-solving.
    2.  Optimising workflows for slow-moving items – For extremely slow-moving items, traditional models become less effective, leaving manual workflows as the default. At Gordian, we’re experimenting with AI techniques to pre-populate workflows after analysing a representative set of parts. This automation reduces mundane manual processes even more.

 

Reimagining the role of inventory professionals

AI will bring change to the world of spare parts

Without trying to be politically correct, we believe these changes will be positive.

Here is why:

1. Amplifying intelligence – AI supports job performance by handling routine tasks, allowing employees to concentrate on strategic, value-adding work. This shift leads to better job satisfaction and increased productivity.

2. Widening access to opportunities  With AI simplifying complex tasks, roles in inventory management are becoming accessible to those with diverse educational backgrounds. It’s not just about efficiency—it’s about creating inclusive job opportunities.

At Gordian, we draw parallels with the impact of extended reality (XR) in maintenance. Previously, only highly specialised engineers could conduct repairs. Now, general logistics staff, with the right support, can handle complex maintenance tasks. This approach doesn’t lower standards; it empowers a broader workforce.

 

Our vision: Democratising spares management in Africa

Gordian is committed to making spares inventory management more accessible across the African continent. By leveraging AI and innovative tools, we aim to transform this sector into one that’s efficient, inclusive, and future-ready.

We welcome collaboration to help us achieve this vision. Join the conversation, scan the QR code to share your feedback.

Download and share this whitepaper here.