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4 Key Themes Emerge As Top Of Mind For Australian Data & Analytics Leaders

We interviewed a number of Australian Data Analytics Leaders from leading industry and research organisations to understand what is top of mind for them when it comes to ‘creating value from data’ and to capture what changes they are seeing in this fast-moving space.

Time to move beyond theoretical ROI

The data driven promise hasn’t delivered for many organisations.  Patience and budget for theoretical ROI has gone.  Impact and real ROI from Data Analytics is essential to the success and survival of data teams and, in some cases, the whole organisation.

  • Clearly define the objectives up front
  • Secure executive level involvement and sponsorship
  • Don’t underestimate the importance of people, culture and transformation in delivering ROI

“The key to creating enterprise value from your data requires greater involvement of analytic leaders in the strategic planning process at the executive level, identifying where analytics can be leveraged to accelerate and enhance organisational strategies.” Peter Inge, General Manager – Data & Analytics, SAI Global

“There is a growing realisation from C-level executives of the value that data analytics can provide to their business. This realisation has arisen because they are increasingly seeing real world applications and tangible benefits to other businesses.” Dr Sanjay Mazumdar, CEO, D2D CRC

“We are shifting from the mindset of ‘what can we do with this data’ to ‘what data do we need to solve this problem’ — and subsequently driving strategic investment into the creation of purpose-led data assets.”
Blair Hudson, Data Analytics Leader

Don’t forget the Transformation in Digital Transformation

Digital transformation, of course, requires human change management.

Whilst shifting to a data-driven culture is recognised as a long term exercise, success of individual data initiatives absolutely hinges on effective change management.  Accounting for this up front is an enabler of success.

  • Identify where challenges to adoption and impact will lie
  • Gain sponsorship and proactively plan for successful adoption
  • Consider structural change if this will unlock realisation of ROI

“Whilst many businesses are standing up insights teams with data analysts and data scientists, organisational barriers remain.  These include building trust in the insights and improving communication, influence and business leadership skills within technical teams.  Establishment of a ‘Business Scientist’ function or dedicated role, one with high soft skills, is an advocate and interface to the business to overcome “buy in” barriers and help translate data science capability to business benefit.
Kari Mastropasqua, Executive General Manager, Data & Analytics – Equifax

“There is a rise of the Chief Data Officer in organisations. This is an important role to explore opportunities where data can be used to enhance the business and champion the cause throughout the company.” Richard Morwood, Head of Innovation, InfoTrack

“Supported decision making, using machine learning and data to augment intelligence rather than automate or replace.  Interpretable machine learning assists acceptance and adoption as users interact with an algorithm in order to gain trust that it’s working as expected.” Ian Hansel Director, Verge Labs

It’s time for Agility – in mindset, technology and execution

Recognising the themes about focused realisation of ROI and keen attention to change management, it is unsurprising to see the Data Analytics Leaders similarly laser-focused on technology that holds up to changing production demands and recognition that the flow of data across your platforms must be carefully managed.  

  • Your solution needs to be low-cost, low-friction, fast-ROI
  • Your technology choice must enable agility, flexibility and scalability
  • DataOps is essential to successful production use of Data Analytics

“A move to a DataOps mindset – Agile, Lean, DevOps style development and deployment of analytic outputs, demonstrating Insights and creating value in far shorter cycles is imperative.” Peter Inge, General Manager – Data & Analytics, SAI Global

“With serverless, even complex architectures can be made robust and faults isolated by taking inspiration from nature and building redundancy into the system: multiple workflows can be set up in the architecture to achieve the same outcome but triggered by different upstream events.” Dr Denis Bauer, Head of Cloud Computing Bioinformatics, CSIRO

“There’s a new breed of tools taking full advantage of the cloud bringing costs down by huge amounts!” Richard Morwood, Head of Innovation, InfoTrack

“Rapid changes in technology means data is exploding.  At the same time, the cost of computing is diving, easing deployment of complex machine learning models.” Kari Mastropasqua, Executive General Manager, Data & Analytics – Equifax

“People are thinking more about what’s required to productionise a machine learning model into something that can be depended upon. Some of the biggest changes are happening in the DataOps space.  More companies are using machine learning to get value from their data and it’s no longer just the large tech companies that are taking machine learning seriously.” Ian Hansel, Director, Verge Labs

You need to be planning for Data Sharing, Ethical AI and Data for Social Good

Ethics in Data Analytics was a backwater topic.  It is now in mainstream media and showing no signs of abating.  Our surveyed Data Analytics leaders observe there is value to be had and that sharing, ethical intent and good governance deliver business value, not just avoidance of reputational risk.

  • There are opportunities in sharing data and knowledge
  • Determine how to share data safely and with the right attribution
  • Ethical AI and using data for ‘social good’ are important to many, including your employees.  Public attention has increased.

“Staying competitive in an environment of ever-increasing speed of technological advancement requires an attitude shift away from proprietary in-house software development towards open access and knowledge sharing.” Dr Denis Bauer, Head of Cloud Computing Bioinformatics, CSIRO

“Data sharing is an important challenge – how to share data and realise value while not breaching privacy.” Dr Sanjay Mazumdar, CEO, D2D CRC

“The next change to come will be with data sharing. This is currently a hard process, for a number of reasons.  However, the potential opportunities that can result will bring focus to overcoming the challenges.” Richard Morwood, Head of Innovation, InfoTrack

“Passionate data scientists are looking for avenues to use their skills for positive social impact, as evidenced by all of the ‘for good’ competitions (such as GovHack), volunteer groups (such as Data for Democracy), thought leaders and individual contributors bringing awareness to the likes of data ethics, consumer privacy, explainable AI, the open data movement, reproducible research and global collaboration (including open source).” Blair Hudson, Data Analytics Leader