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BigML Roadshow Down Under!

by on March 20, 2015

This week, I had the honor to present at AIIA’s cross-industry luncheon here in Melbourne thanks to the support of BigML’s local partner GCS Agile. The Australian Information Industry Association (AIIA) is the peak representative body and advocacy group for the ICT (Information and Communications Technology) industry in Australia. For over 35 years it has been their mission to advocate, promote, represent and grow the ICT industry in Australia as a not-for-profit organization, with over 400 member organizations covering a large spectrum between hardware, software, and services companies.

AIIA Event Melbourne

This year, the AIIA is running three cross-industry events under the umbrella theme of ‘Building the Digital Economy’. Featuring the utility, airport, transport, logistics, retail and finance sectors with separate sessions exploring intelligent operations, connectedness and digitization of the customer experience. These themes align with the Victorian government themes of achieving sustainability, productivity and citizen engagement through technology as discussed in their 2014 ICT Strategy and Digital Strategy.

‘Intelligent Operations’ is a mouthful term, but it is really meant to describe how intelligent technologies, including machine learning and predictive analytics can be used by businesses to drive operational efficiencies, employee productivity and improved customer service. Guest speakers at our luncheon included Paul Bunker, Manager, Business Systems & ICT, Melbourne Airport; Sue O’Connor, Deputy Chair, Goulburn Valley Water Corporation as well as myself (Atakan Cetinsoy, V.P. – Predictive Applications, BigML). After Rebecca Campbell-Burns of AIIA set the stage for the afternoon, Mr. Bunker took the podium making a strong case on how the Melbourne International Airport’s track record of operational excellence has added to the continued economic vibrancy of the state of Victoria stressing that they run a 24/7 operation, where cargo planes take to the air precious commodities to Asian destinations every night after the passenger airliner traffic subsides. Managing physical assets efficiently in this fast-paced context, while targeting a world-class traveler experience from the point of arrival until departure requires an analytical blanket that can adapt to sudden changes that may be caused by inclement weather or tightened security, which makes for a very interesting predictive analytics challenges.

Sue O’Connor’s presentation focused on the need for Goulburn Valley Water’s efforts to maintain a very affordable price point for drinking water, the most basic of human needs, at a time of environmental challenges, all the while making the necessary infrastructure investments to ensure the ability to meet growing demand now and in the future despite tight capital and operational expenditure budgets.  Sue went on to stress they intend to invest in Internet-enabled sensor networks to the extent that there is a clear business case and attractive ROI.

As I alluded to in my presentation, utility and aviation industries have a huge economic upside ($95 billion USD in savings as per a recent GE study) in efficiency terms from being able to better manage their existing infrastructure with the help of real-time sensor measurements.  As long as there is a way to analyze and interpret this tsunami of data in order to detect key signals business value can be drawn in multiple ways. For instance, it may be wise to prioritize big data initiatives targeting cost savings first due to clear return on investment.  Predictive maintenance schemes can avoid unnecessary dispatches of field maintenance personnel saving utilities significant amounts in costs.  However, sensor data can also be interpreted in ways that help launch completely new context sensitive value added services that can create new revenue streams all together. Luckily, machine learning is here to help with all these use cases. BigML’s “API first” approach to massively scaling carefully curated and well proven machine learning algorithms has been designed to streamline the process from raw data ingestion to real predictive insights. If interested on the topic, you can view my presentation deck on Slideshare.

Up next for us is a trip to Sydney, where we will be presenting at two different events on Wednesday (March 25, 2015). Feel free to come by and join us at either forum by following the links below.

We will do BigML demos followed by interactive discussions on the promise of machine learning in Australia.  It should be fun!

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