Analytics is transforming businesses and the world, but organisations are often “immobilised” and unsure how - or where - to jump into the game, according to SAS vice-president, global technology and industry practices, Bob Messier.
Messier delivered his message during the recent two-city CIO Breakfast event ‘Innovate with Analytics: The Art of Deeper insights,’ in partnership with SAS.
Messier was joined by international keynote speaker, Gerhard Pilcher, president and CEO of Elder Research, as well as a host of panelists - executives from Telstra, Origin Energy, Black Dog Institute and Westpac - who all demonstrated during an interactive panel discussion how they’re leading their industry with the adoption of analytics.
Speaking to packed crowds in Sydney and Melbourne, Messier acknowledged there is confusion in the market and many businesses are unsure of the right steps to take in adopting an analytics strategy.
“They are struggling to really understand what it is and we need to simplify it for a lot of our customers,” he said, breaking it down into three components: computer vision (images and video); machine learning and deep learning; and natural language processing (text data).
Digging deeper, Messier delved into the transformative power of advanced analytics and the road to innovation - and how to build for the future of artificial intelligence (AI) and machine learning.
“It’s about capturing as much information as possible, and now we have the compute power to analyse as much data as possible. We’re in the midst of an analytics platform movement.”
He explained how the analytics platform movement is not a single vendor movement, but an ecosystem movement that stitches together different tools and techniques from open source to software off-the-shelf.
“It presents different and new challenges for the people in IT to support this movement. But this movement will bring forth an analytics economy, where customers will be able to incrementally improve what they’re doing in their existing analytics environments, as well as the opportunity to leverage their existing data and the new types of data that are coming into the fold.”
He flagged a myriad of forces shaping the analytics economy from data scientists embracing open source to a changing data landscape with regulatory issues like GDPR and privacy, and to the onslaught of new data formats including image, video, text, and unstructured data.
“Not only is it coming at us, but it’s coming at us at a velocity we never imagined - in milliseconds - and so how do we consume that information, and how do we score that information?
“Today, we’re looking at how to score data as it’s coming into the organisation. Score it for its relevance and then determine its storage. So stream it, score it and store it,” he said, explaining not all data is relevant and the relevance can change over time.
Overall, the possibilities are endless. Messier said analytics not only delivers increased automation and speeds up processes, but also enables the identification of new models, the discovery of hidden relationships, and can unlock a new level of intelligence.
He said many organisations are building on the momentum and capitalising on AI and machine learning, and producing real tangible business value.
But is AI perfect? Messier believes there are “limitations” given the technology can see things and recognise things, but not always understand things. “The machine is getting smarter, but it certainly isn’t at the point of understanding comprehension or what I call abstraction.”
Despite the challenges, Messier urged businesses to get started on the analytics journey - one that will ultimately lead to rapid innovation, business automation and transformed operations.
“Dip your toe into the water and take a crack at it. There’s no doubt that it’s all achievable. But don’t get caught up in all of the hype. Do your business assessment first before you go off and buy a technology. Figure out what problem you want to solve.”
Set appropriate expectations
Like Messier, Pilcher urged businesses to conduct a reality check and set appropriate expectations. In his keynote address, Pilcher discussed how AI is shaping the world, and how it can incrementally help businesses.
“This is all about expectations. We get so excited about data science and analytics and AI and machine learning that we think our businesses are going to be transformed overnight. I’ve never found that to be the case. It doesn’t happen.”
That being said, Pilcher said there’s a huge opportunity for businesses to take advantage of advanced analytics in order to improve business efficiency and unlock solutions to hidden business problems.
Getting granular, he said the first step in adopting an analytics project is to define the opportunity or business problem and gather the data. The next step is to utilise machine learning, which provides a mathematical model or some classification to make a prediction. The final step is to push the delivery and change management process into the organisation so it has a positive and lasting impact.
“Be flexible and be willing to allow questions that come out of machine learning to direct your thinking and how the project might proceed.”
Certainly, as AI creates new questions - and uncovers new problems - it’s important companies identify both the pain points and the opportunities - and don’t forget the change management piece.
“Getting people to rethink how they operate on a daily basis is hard. The change part of the equation is difficult and we don’t think enough about the person whose job is going to be impacted, and how we can deliver that analytic result in a way that they’re glad to consume it.”
At the moment, he said there’s way too much “focus and hype” on AI and machine learning - and not enough practical business analysis and data soul searching.
“We want to go buy a new tool before we’ve even defined a problem to solve with that tool. So maybe we buy a hammer, but what we actually needed was a screwdriver.”
As a result, he said it’s important to get the problem definition worked out, gather the data, and then begin to cleanse the data.
“There are new questions that have to be asked, so we have to allow ourselves to be redirected by those new questions sometimes. This is a test and learn type of environment - an experimental type of environment.
“We have to get comfortable with the fact this is not like a normal project with a beginning and an end. This is a new way of thinking about how we bring data into our business decision making process.”
Making a difference and driving change
Already, many companies from banks to utilities to government departments are driving transformational change and making a difference thanks to the power of analytics.
Experts agree the use cases - and problem solving possibilities - of data analytics are endless. From improving business operations, to increasing revenues, and helping with marketing campaigns and the customer experience, analytics gives businesses and government a timely edge.
Companies like Westpac are already seeing the benefits of adopting advanced analytics, according to Westpac general manager of business performance and analytics, Leif Evensen.
During the panel discussion, Evensen said the bank is taking advantage of the latest technologies and the emerging data sources becoming more prevalent.
“My vision for analytics at Westpac is it very much can be a true source of competitive advantage for the organisation and we focus on three things: actual information, insight and advice.”
Evensen said the information aspect takes into account ‘what happened,’ insight involves asking ‘so what?,’ and advice is about determining ‘what should you do about it?’ “Pretty much everything that we do at Westpac with analytics aligns up with those three areas of aspiration.”
Additionally, he’s particularly interested in the human capital dimension. “There’s a lot of talk about data and technology and tools, but the true source of differentiation remains the human capital in advanced analytics and that’s where we continue to push a lot of our efforts at Westpac.”
Meanwhile, for Origin Energy, group head of customer analytics, Sandra Hogan, said the company is using data analytics in a bid to boost customer experience and “understand the customer,” in order to make the relationship far richer and more enhanced.
“While data analytics is not new to Origin, it’s certainly heightened at the moment with the disruption going on around customer experience. The challenge in this industry - and other industries - is around trying to get that customer engagement right.
“It’s about trying to get the right balance and making sure we’re becoming relevant to a customer, and making that experience a positive one. There’s a lot of negativity in the industry, so it’s about trying to get that improvement in visibility and using the analytics to help the customer experience.”
Like Hogan, Telstra general manager of analytics, Russell Hunter, said the telco is using analytics in a bid to understand the customer and their pain points. “The primary application of analytics is understanding the customer, understanding the pain points and understanding what they need.” It’s about solving business problems that are front of mind for customers.
Hunter said some big challenges - particularly felt by middle management - involve understanding the analytics, knowing the right questions to ask, engaging back with the analytics team, and then being able to assess and adequately tap into the right skills sets required across the organisation.
“If we can actually solve the problems that most middle managers have, and actually focus on those, as opposed to some of the sexy AI stuff that we all want to do, you start to generate trust, you start to get an understanding around what it is that analytics can do and you start to generate a pull for our services.”
Meanwhile, over at the Black Dog Institute, its experience with advanced analytics involves ground-breaking work on suicide prevention.
As part of the strategy, the institute is using data analytics to create a ‘suicide audit’ of communities based on the latest data sets, according to its director and chief scientist, Helen Christensen, who is also a professor of mental health at UNSW.
“Suicide is the number one killer of young people in Australia, aged 15 to 44 years. Around seven or eight people take their lives every day. The issue is that nobody has ever really brought data analytics to this really human problem.
“One of the things we’ve been trying to do is actually capture the data and be able to deliver information on the ground to people who are working in communities to try and give them some insights into what may be good strategies.
“For example, we know that means restriction is a very effective strategy. That means making sure people don’t have firearms, or protecting people from bridge jumps, or keeping people away from cliffs because that’s really at the ultimate end of their journey in terms of their risk.”
It’s a very effective strategy, she said, explaining “time itself” is an effective way to reduce suicide attempts.
“You can do a suicide audit of your community and have that information given back to you to provide you with the real clues on what we can actually do on the ground to change this.
“Over the last three years of the journey, we’ve pulled together some very impressive data sets. We’ve now got really good information on all of those aspects. And with the help of SAS, we’ve been able to use that information to turn that into reports that directly go back to each community to show them what they can actually do on the ground.”