2018 Winner – Genevieve Elliott
Attending a program at Harvard has long been a dream of mine – and through the Frank Lowy Fellowship this became a reality.
Over the last four years at Vicinity, we have been on a data journey. Our goal has always been to be a point of difference for Vicinity – providing value through generating cost efficiencies, supporting revenue generation or providing our customers with enriched insights to support their business objectives.
The application and value of big data sets, particularly in traditional businesses, is still an emerging field. Whilst there is much discussion about the possibilities of big data, in reality, there are relatively few examples available to analyse in the Australian market. This is why, when asked to consider what I would do if I were to be the successful winner of the fellowship, I elected to attend the week-long ‘Competing on Business Analytics and Big Data’ program run by the Harvard Business School.
The program at Harvard promised an opportunity to see real life, practical applications of big data in small and large enterprises as well as to meet the protagonists – the data gurus – for each of the businesses we studied. What was not to love about that!
The course started at midday on a Sunday and from the moment we started the pace of content delivery and discussion was intense. The course was structured across three primary themes:
Deep dive into technical fields
For those of us that hadn’t done statistics since their undergraduate degree, a 6 hour deep dive into advanced statistical concepts with a deep focus on regression analysis was a bit of a shock. We learnt how to use R and R studio, were reminded that correlation does not equal causality and focussed on how much data is enough for predictive models (beware of overfitting a model!).
Big concept theoretical models
Network effects (single or double) were a new concept for me but are very relevant to how a shopping centre functions. Many of the new businesses that are disrupting traditional companies (Uber, AirBnB, Google) are reaping the benefits of a network effect model and understanding their growth drivers is so important in the development of new models within retail property.
Application of the technical and theoretical through case studies
Theory and practice collided through the case studies we were asked to analyse. Our case studies ranged in subject from Bundesliga football teams to the movie industry. All of the case studies involved the application of analytics but the industries and subjects were different. In at least fifty percent of the case studies, the leader of change from the actual organisation attended the session so we were able to ask questions and also challenge some of the decisions they had make. The case study sessions were dynamic and student participation was strongly encouraged (if you didn’t volunteer you were ‘cold called’!). I was a proud Australian throughout the AfterPay case – which was also of interest given the impact it is having on in-store and online sales in Australia.
We had approximately 70 students in the program from 31 countries – from Russia to Taiwan, Uganda to Belize. Participants also came from multiple industries with a broad range of capability with the use and application of advanced analytics and big data. There were CEOs, CFOs, CIOs, COOs, Chief Commercial Offices, Data team leads, solutions architects, heads of logistics – all united by a keen interest to learn more about the value of data.
This week of learning was the best piece of post grad learning that I have ever done – targeted in its focus with consistent high-quality delivery. I learnt new concepts, was given the opportunity to benchmark Vicinity’s current capability in this space and have developed a network of peers with a shared experience that will stay with me for a lifetime. I am immensely grateful to the Frank Lowy Fellowship and to the SCCA for this opportunity and I am determined to continue to apply my learnings for the benefit of physical shopping spaces to limit the impact of digital disruption on our businesses.