Expertise

sparesAI to increase asset availability while reducing inventory cost

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Increase critical asset availability while reducing inventory cost by up to 40%

sparesAI optimises maintenance, repair, and operations (MRO) inventory levels to minimise the cost of your inventory, and maximise the availability of your assets.

Wood’s inventory and materials management expert knowledge is packaged into models and deployed on your data to continuously optimise your asset over time.

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Increased accuracy in predictions

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Reduced inventory costs and associated working capital

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Increased asset availability through avoidance of stockouts

See how sparesAI can help you reduce inventory costs

Watch the video to understand how sparesAI works

Peter Carydias, Operations Manager, talks about trends in the industry, why Wood invested in sparesAI, how algorithms can help us predict the future, how we deploy sparesAI and the results we deliver.

Optimising inventory levels at scale

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sparesAI – domain expertise plus artificial intelligence

sparesAI can rapidly augment inventory data for an advanced and granular analysis based on a scalable, data-driven approach.

Make decisions today with your current data, while consistently optimising your inventory using live reliability information.

Wood has been optimising our clients’ inventories for 20+ years

sparesAI optimises inventory levels at scale. We’ve overhauled classic inventory models and optimised them based on years of R&D and real-life data.

The new models apply a semi-automated approach using data-driven models combined with human experience and proven maintenance management principles.

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Rapidly evaluates
larger datasets

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Brings operations, maintenance, and integrity insight to your inventory at scale, vetted by our engineers

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Forecasts accurate
spare holding levels

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Provides real-time updates of
inventory holding suggestions

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Uses advanced algorithms to infer reliable solutions, even with incomplete data

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Deploys inventory models to client cloud for dynamic inventory analysis

Case study:
$7B Water Corp

Lever

Optimise inventory and improve working capital

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Outcomes

40% reduction in inventory value, while increasing critical spare materials to enable high asset availability (~8% of inventory lines)

Differentiator

We leveraged Wood’s data-driven models on reliability, lead time and cost to quickly improve inventory strategy

sparesAI outlook

Data-driven models are only scratching the surface of what is possible.

Backed by Wood and innovation funding, our team is always pushing to find better, faster, and more robust solutions. With the ability to build specialised teams from over 40,000 experts in 60 countries, our solutions have no boundaries.

Speak to a specialist

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Be in the know
Peter Carydias
Global Digital Solutions Manager
Get in touch
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