Knowing when to ditch old equipment is tricky but essential to avoid waste and downtime
“Data is a precious thing and will last longer than the systems themselves,” wrote Tim Berners-Lee back in 2006 in A Framework for Web Science. It’s an interesting quote because 19 years later it can be applied to what we are starting to see in industry.
As new research from Forrester Consulting has revealed that within five years, the value from equipment and service data will exceed the value of equipment itself.
The research, From Grease to Code: What Drives Digital Service Transformation, found that forty one percent of organisations say they don’t know if they are retiring equipment prematurely, and a lack of service data insight means they have no knowledge of how much capacity remains in their capital assets.
Interestingly this statistic was taken from a cross section of industries, including manufacturing, healthcare, utilities and telecommunications. Organisations of all shapes and sizes are reaching the same conclusion. Something drastic has to be done to ensure they are not pouring money down the drain by ripping out machines too early or risking productivity by keeping them in situ for too long.
“Firms struggle with understanding the lifetime of their equipment and how to improve it,” says Forrester Consulting in the report. “As a result, they face high maintenance costs and unplanned downtime that affects their revenue and customer experience.”
Most, according to the report, have high maintenance and operating equipment costs, as well as a lack of knowledge on how to reduce these costs. More than half of organisations surveyed say unplanned downtime is becoming a bigger issue, which of course directly impacts revenues and customer experience.
It’s a huge challenge for organisations, especially those with considerable fixed assets. While the average lifespan of equipment is under ten years for most companies, eighty percent of firms say they need better insight to extend the life of their equipment. Close to seventy percent of businesses say extending equipment life would result in financial gains.
Who owns the assets also owns the risk of over-capacity and under-utilisation, poor machine up-time, managing the supply chain required to keep the machines running, recruiting, training, and retaining staff to service the equipment – or paying someone else to do so. It’s a catalogue of tasks that needs managing but how?
Firstly, there’s an assumption that information about a capital asset resides in the company ERP system, but that’s a record of business transactions of the equipment “as sold”, which doesn’t describe what the equipment looks like today. Overcoming invisibility of assets should be a primary task and that means on-going health, repairs, patches and add-ons.
Accurate data about “equipment as-maintained” is critically important for any business as it not only enables companies to see how much longer they can ‘sweat’ their assets, but it also ensures they’re dispatching the right technicians, with the proper tools should anything go wrong. The last thing organisations want is to delay repairs by having multiple visits, or truck rolls, to get a machine up and running again. Otherwise it’s a bit like a doctor trying to help a patient without having any medical records. It’s still possible to fix the problem but it could take so much longer to do.
And of course, it’s important to take the issue of ‘skills fade’ into account. As a piece equipment ages, so too does the workforce – you need a system to knowledge share and collaborate around asset maintenance.
In short, businesses need a system of record for equipment as it is maintained to prevent downtime, lost revenue, negative customer experiences and expensive and unnecessary premature retirement of capital assets. With live equipment information, technicians can minimise outages and downtime. Response rates will increase and be more efficient. Calls to the service desk to log a “case” should become obsolete as service teams can be alerted to issues through live product visibility.
Only then can organisations truly know when their machines’ time is truly up.