As part of Deloitte’s eighth annual Technology Trends report, we sat down with Paul Oppenheimer, CIO at RMIT University to get his take on how businesses can illuminate opportunities hidden within unstructured data. Here’s what he had to say. Illuminating the potential When we think of data and analytics, there is such potential. When we look around an office, lecture hall or university campus, the bustling ecosystem is filled with interactions, meetings, information gathering and a myriad of data points. Out of that comes the potential for robust information. Insights and analytics can be harnessed to paint a powerful picture of what is possible. From operational and executive dashboards to advanced analytics case studies, we need to think about what might drive analytics across the education sector and other associated industries. Unlike a bank where a core asset is the information it holds on accounts and services, we might need to shift the mind-set a bit in education to focus on why data is fundamental to unlocking growth and opportunity. Bringing to light the key issues With a strong focus on learning and the delivery of content in third level education, data sometimes tends to sit in the background, but it is time for it to start moving front and centre. As we move into a rapidly evolving digital world, digitising day-to-day elements and interactions means we can use the analysis to inform how we educate, interact and deliver content. It’s important to consider how we can create a robust ecosystem to support the university sector. Whether this is creating educational solutions with inbuilt analytics or having a diversity of channels, it would be fantastic to be able to synthesise data insights quickly and efficiently. Purpose: what’s in it for me? If we look externally at the range of channels being used to capture data, such as social media, data in these situations indicate a propensity to buy or be interested in a certain item or product. What if the same insights could be harnessed from data around subject choices, lecturer reviews, content feedback, course interests and more? There is sentiment of freedom across a university campus and the role of digital or collecting insights from data might constrain this notion. So it needs to be balanced carefully – taking into account the role of regulation, policies and technology – with the end user and outcome in mind. We need to always ask ourselves: what are we trying to achieve? In order to incorporate a move towards data being a part of university life, there would need to be education and incentives around how the use of analytics will improve and enhance a student’s experience overall. A careful buy-in from the university population would ensure that people understand why data is being captured and how it is being used or interpreted. The power of cognitive Once you have buy-in, there is an enormous amount of potential that comes from cognitive technologies. One area to explore is capturing emotions and sentiment in the lecture sessions and classrooms to answer such questions as “Are people engaged or disengaged?” “How are they processing the information?”, “Are students interacting positively with the lecture style and format?” The whole is greater than the sum of its parts – Aristotle While in some parts of an organisation or university setting IT can be viewed as merely a supplier, it’s critical that we elevate the role of IT as a key driver and collaborator on all things data. We need to collectively start asking the right questions to elicit the data we are trying to seek. When we look at the power of data across an organisation or institution, the whole picture is more meaningful than if we only look at the individual components in isolation. Some practical measures on what we can do right now are around leveraging analytics across the university sector and other industries includes three elements: #1 Use what you have: there is no need at times to launch into buying and implementing new software or devices. Often the existing tools, used correctly and right now, can offer insights. #2 Be proactive: rather than waiting for a complete strategy to be implemented, there is plenty of background research that can be done into what we can we harness right now from a data and analytics perspective. #3 Collaboration: across a university (and other industries) there are many departments and areas that can contribute to the data conversation. Collaborate to achieve the best possible outcome. In terms of where the sector is heading, we’re only at the tip of the digital data iceberg of what’s possible around illuminating dark analytics. What is next is a focus on asking questions and working together to explore innovative solutions and ideas. Paul Oppenheimer is a leader with a proven track record in developing strategy, managing operations and guiding teams to deliver valued outcomes for customers. He is skilled in the design of both tactical and strategic capability roadmaps and has a deep background in technology and digital developments that will disrupt current operating models in the market. Paul has a 17 year executive management background that includes senior stakeholder engagement, business strategy execution, team building, portfolio management, program delivery, change management and process improvement experience. Prior to RMIT, Paul worked at Accenture where he was responsible for the execution of a Business Transformation Program across operations, banking and non-banking streams. He has also held previous roles with the ANZ Bank – in Australia within the Personal and Technology Infrastructure divisions, as well as in Singapore where he managed a wide range of technology and operational responsibilities for the Asia, Pacific, Europe and America division of the bank. In between time, Paul has also started his own mobile technology company.