IT departments wasting thousands on redundant tech
Nearly half of IT departments from Australia and New Zealand are wasting over $10,000 per year on redundant technology, according to Rackspace research.
A survey of IT decision-makers in the two markets shows that 25% of IT teams are wasting $10,000 to $49,999 per year on redundant IT. A further 13% are wasting $50,000 to $99,999 and 10% are wasting over $100,000.
The survey shows that 43% of IT decision-makers polled had experienced executive pressure to implement a technology even though they believed it was too risky for the business.
Nearly three-quarters (73%) of survey respondents admitted to making a poor purchasing decision, either because the software and hardware didn’t deliver what was promised or became irrelevant within the intended lifespan of the technology.
“In a crowded market where new technologies are released at such a rapid rate, the modern-day choice has become less black and white than it was a decade ago,” said Angus Dorney, director and general manager at Rackspace ANZ.
“It can be difficult to forecast if a purchase is going to deliver on its promise to provide your business with sufficient ROI. In some cases, this research shows that a lot of technology is purchased and never used.”
Besides the technology, more than half of businesses, including 77% of medium-sized organisations, have hired an IT employee that turned out to be a bad fit.
Outsourcing is one solution for companies adopting a technology that’s beyond their in-house expertise, but 57% of respondents have had a negative outsourcing experience from an IT service provider. Top complaints include badly managed services, repeated downtime and security concerns.
Is the Australian tech skills gap a myth?
As Australia navigates this shift towards a skills-based economy, addressing the learning gap...
How 'pre-mortem' analysis can support successful IT deployments
As IT projects become more complex, the adoption of pre-mortem analysis should be a standard...
The key to navigating the data privacy dilemma
Feeding personal and sensitive consumer data into AI models presents a privacy challenge.