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Children’s Cancer Institute’s Elaine Neeson eyes analytics

Children’s Cancer Institute’s Elaine Neeson eyes analytics

Machine learning, marketing automation, predictive analytics, disaster recovery, and data integration layer top CIO’s list

Newly crowned Children’s Cancer Institute CIO, Elaine Neeson, is setting her sights on delivering an analytics strategy across the organisation.

“Probably the most exciting thing for me is seeing how data can make a difference in research and hopefully accelerating research discoveries,” she told CIO Australia.

There is a focus on using predictive analytics to better understand the behaviours of the institute's supporters or using machine learning to accelerate research discoveries and innovations.

As CIO, Neeson is responsible for the overall direction and strategy of the institute’s technology needs that incorporates both operational and research directions. She recently left the head of technology role, which she held since November 2015, and stepped into the CIO role, a move that better “reflects the external environment,” she acknowledged.

Elaine Neeson
Elaine Neeson

Since first joining the Australian medical research institute in 2007, she has also worked as the strategic operations manager, project manager, as well as risk and compliance/project manager.

Signalling big things ahead, Neeson said her team is working on more than 20 projects this year but her main focus areas include machine learning implementation, marketing automation, predictive analytics, disaster recovery, and data integration layer.

Neeson's says her main priority is to drive a high performance and innovative culture where technology partners with the business to deliver relevant outcomes. This also ensuring that researchers and operational staff have access to the technologies needed to deliver on their goals, while giving them the mobility and flexibility to access resources from anywhere at any time.

Asked her big lessons learned from prior posts, she said it involves the need to partner with the business.

“To be able to accelerate adoption and innovation you have to bring the business with you on the journey,” she said.

“Technology decisions can’t be made in isolation or in silos they need to be aligned to the business needs and goals across the organisation. Empowering the team to make decisions and test ideas and theories without fear of failure, making sure everyone’s ideas are heard and acknowledged equally.”

Neeson said her biggest business and tech challenges - particularly working for a not-for-profit - is funding and access to resources. The push towards adopting emerging technologies is particularly difficult.

“I find there are many misconceptions about the NFP sector and that people don’t realise how innovative the technology landscape is. Within medical research the pace of innovation and new technologies continues to accelerate and the ability to keep up with those changes and provide the technologies and services so that our researchers can harness these innovations is a constant battle," she says.

“Every cent we spend needs to add value and drive outcomes, so we are constantly looking forward to ensure any decision we make now will not negatively impact in the future. We work with our corporate partners and collaborators to gain access to resources and technologies that we may otherwise not have been able to fund. Wee have a fantastic network of engaged partners that have given us access to everything from pro-bono software to specialised skills and knowledge.”

And while her challenges are many, she believes she’s in the right place at the right time, saying it “means a lot” running the IT department of the institute.

“I am passionate about our cause and know that everything I do contributes to our mission of ultimately curing childhood cancer, there is no better feeling than knowing what you do can make a difference to children’s lives.”

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Tags disaster recoverypredictive analyticsmarketing automationdata integrationdata analyticsChildren's Cancer Institute Australia (CCIA)machine learningElaine Neeson

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