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Measuring success

Roger Marks, MD of Aeromark explains why total cost to serve and asset uptime are key metrics for profitability

Metrics like total cost to serve (TCS); asset uptime; total cost of ownership (TCO) mean time between failures (MTBF) first time fix rates (FTF) beyond economic repair (BER) have become the key for managing assets and ensuring service effectiveness and profitability.

Asset management is the foundation for managing these metrics and a core requirement of effective service management. If you do not have full visibility of the assets across yours or your customers’ business, you risk operational inefficiencies, increased costs, and a decline in overall performance. You might even risk the safety of your employees, contractors, and customers.

At the heart of managing these is effective Enterprise Asset Management (EAM).

BENEFITS OF ENTERPRISE ASSET MANAGEMENT

EAM software helps service organisations monitor, manage, and report on the condition of all assets across your own business as well as your customers.

With an EAM, every asset is given a unique tag to scan for every visit, fault, and PPM service. This creates a full history and builds data on TCS and TCO. Enabling you to understand and analyse and cost each visit, the parts used, the margin per job and per contract.

Live management of your assets builds a service history from day one. Every task, from installation to planned preventative maintenance, reactive repair, or replacement, has end-to-end visibility within the system, driving both performance and behaviours. Asset uptime, or the duration a particular asset remains operational and productive, is critical to your customers – after all, a faulty coffee machine earns nothing for a restaurant or pub and every non-productive asset is, firstly a high priority fix, and secondly, a real annoyance.

Asset data is especially useful for larger enterprises who spend significant amounts of money kitting out multiple sites. Providing your customers with information of asset performance, failures and fixes can give them significant commercial information in dealing with their suppliers for the selection of assets amounting often to many hundreds of thousands of pounds.

How then do we gain visibility of this crucial information and create a self-cleaning database and turn these analytics from data into knowledge.

The key is to create an EAM and then manage planned, reactive, and preventative maintenance from that foundation.

ASSET TAGGING AND CUSTOMER PORTALS

Asset tagging, usually with QR codes, is quite an easy function when the EAM is fully integrated with a mobile application. Scanning a tag and completing a workflow-based asset or site audit become the basis of a clean EAM. Every action writes back to that history, and, with a Customer Portal, every incident can be traced back to the scanned tag for triage and accuracy of fault data so the appropriately qualified engineer with the right spare parts in their van stock is despatched.

The mobile applications also add further value to the asset database because every single action, either by the engineer or as part of a back-office triage process can be attributed to the asset. That ensures the database is always up-to-date and becomes, in effect, self-cleaning.

PLANNED MAINTENANCE SCHEDULES

Many assets require regular planned maintenance for compliance and performance. Targeted correctly, these service plans significantly reduce the risk of unplanned failures and reactive breakdown costs and ensure not only asset uptime for your customers but also that assets are operating in an optimal and safe fashion.

Increasingly however, some non-compliance related planned maintenance schedules are becoming superseded by predictive maintenance as assets become more connected with IoT technology.

REACTIVE MAINTENANCE

For reactive maintenance, the TCS again need to be ascertained and billed appropriately. To do this effectively a scheduling function needs to be aligned with the asset database, so the best and closest resources are allocated within SLA’s.

Ideally that resource will have the appropriate parts within van stock; and the asset database should inform the stock process which parts are commonly required so the stock holding maximises the opportunities for first time fix.

If however, parts need to be ordered, the ability to look up the parts for the asset and then have access to an integrated supply chain which shows all the orders, despatches receipts and on the scheduled revisit installs and charges as needed, ensures excellent service and just-in-time (JITS) stock management. Finally, an automated process for apportioning the right schedule of rates (SOR) and parts mark-up should automatically create the bill.

PREDICTIVE MAINTENANCE

Predictive maintenance is the next stage of asset management. By providing an integrated IoT platform the sensors monitoring the asset can identify when it is operating outside of normal working parameters. Take for example a freezer unit, not only can the internal food temperatures be monitored for HACCP regulations but, if the unit is running either hot or cold this can be adjusted for energy saving or act as an early notification of failure.

Ultimately, the platform could ensure the engineer arrives to fix an asset that is about to fail…saving both the asset and its contents.

About Sarah OBeirne

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