Market research shows that up to 50% of unscheduled manufacturing downtime is due to lack of spare parts, yet sometimes as little as 10% of MRO (Maintenance, Repair and Operations) stock may move in any 1 year.

Building Advanced Analytics intelligence into your systems has the potential to deliver:

  1. Significant reduction in unplanned downtime related to parts
  2. Measurable reduction in inventory costs and stock levels
  3. Eradication of stock-outs and obsolescence
  4. A data-driven inventory system where the competing views from Finance, Operations and Maintenance can agree on evidence-based reorder points.

Any way you look at it, the potential savings are significant.


So, how can organisations take some light touch, manageable steps, to reduce MRO inventory levels and costs while maintaining their maintenance SLAs and downtime KPIs?

Put another way, how to use Advanced Analytics to drive usable insights and visual outputs to help move from ‘trench warfare’ to meaningful collaboration between Finance, Maintenance and Asset Management.

Typically, sectors that can benefit the most from such programmes include Utilities, Logistics and Heavy Manufacturing and they actually all had very similar challenges.

  • How can we identify current obsolete stock? How can we monitor when stock is going to become obsolete? How can we identify what we can remove from our warehouse and balance sheet?
  • How can we improve our data quality to include things such as asset criticality?
  • How can we get a clear picture of our current MRO stock levels, segmented by stock types, SKUs or location to help us to understand optimum strategies for each?
  • How can we look at unusual behaviours to ensure we are alerted to stock out risks or inefficient buying behaviour that is costing us money?


Getting MRO Inventory Management Right

Traditionally MRO Inventory Management has been based on gut feel, experience and complex spreadsheets. Centralised Asset Management Systems such as IBM Maximo, store the relevant data (often in very poor quality), but cannot analyse or present it in a way that the business can use to deliver the maintenance required and the optimum stock levels.

Advanced Analytics:

  • offers an insight-driven approach that delivers outputs through easy to consume visual dashboards,
  • delivers an ongoing process rather than a one-time snapshot of your inventory data,
  • provides for immediate results to identify and remove obsolete stock and
  • enables an on-going capability to maintain your optimal levels of different MRO inventory and improve data quality where required for better and more accurate insights.

Front and centre to the success or failure of a solution is gaining buy-in and trust from all the stakeholders involved. For Finance this means showing that inventory optimisation is not the same as inventory reduction. For operations, this means showing clear evidence that inventory reduction will not increase risk of a stock out.


So, how can Advanced Analytics bring the right mix of inventory to deliver both cost effectiveness and the highest performance for maintenance?

  1. Help in defining what is critical – In a certain Utility, classifying stock items based on recency and frequency allowed them to immediately identify non-moving stock and then use the SKU value to get to work creating a criticality index. This was then added to the analysis. In doing so, they considered the risks and costs associated from a stock out of each non-moving spare part. The impact of downtime on the business and the workaround options were investigated, which delivered an accurate criticality for each item.
  2. Current inventory segmentation – You can plan and establish inventory control per category and set different strategies, based on lead time, criticality, movement frequency, insurance items, cost, etc. The ability to drill down and segment your stock helps ensure that appropriate policies are applied consistently. Not all spare parts will be managed in the same way. Segmentation will also help focus clear ownership and discussions with the relevant stakeholders.
  3. Reduce current and future obsolete stock – Visualising the stock usage history, you can quickly see which parts are non-moving, remove the non-critical parts and, on an on-going basis, monitor which parts are becoming obsolete. This can also take into consideration changes of equipment and machinery.
  4. Demand forecasting for slow, seasonal and lumpy demand items – As much as 90% of MRO inventory can be defined as slow moving, so it’s important that forecasts for demand also take lead time and irregular usage patterns into account.
  5. True collaboration to achieve business results – All Advanced Analytics initiatives come to nought unless the business owner uses the outputs. A critical point raised several times at my talk was that people had seen the technology as “Black Box” where the maintenance operators ignored the outputs because they couldn’t understand the logic behind them. Insights displayed in an “easy to use” format are critical in getting buy-in from the different stakeholders, each with their own respective KPIs.

MRO Inventory Management is the first step in their journey to full Predictive Maintenance. Given the limited data required to deliver MRO spare parts optimisation and the significant ROI that can be achieved, this is a space that looks set for explosive growth.



Properly done, Smart Inventory Analytics delivers real competitive advantage using both predictive and prescriptive analytics, combined with multi-dimensional inventory forecasting algorithms, and easy to understand reporting dashboards. The result is that MRO Managers have successfully reduced costs, increased service levels, minimised unplanned downtime, and achieved greater efficiencies across their operations.