Utilising Big Data to Drive Business Growth

In his 1597 text Meditationes Sacrae and Human Philosophy, Sir Francis Bacon noted that knowledge is power. And despite all that has changed in the four subsequent centuries, his statement rings as true today as ever.

But there is one rather major difference between knowledge in Bacon’s world and knowledge in ours – thanks to the internet, almost everyone has access to the same information. The playing field has been levelled.

We find ourselves at the beginning of the big data age. In today’s business world, all the answers are hidden somewhere within the zeroes and ones… it’s just a matter of finding them. But how does an organisation go about obtaining the seemingly limitless knowledge locked away big data, and the power that comes with it?

To find out, we spoke to four leaders in the big data field: Denham Pinder, VP and Head of Markets at Cognizant, Kevin Kong, Data Analyst at OpenAgent, Yi Fang Chua, Senior Cyber Security Manager at EY and Simone Roberts, Director of Data Science & Analytics at Optus. So, what do these professionals see as the current keys to big data success, and how do they view big data playing out into the future?

How does big data impact business transformation?

With almost all businesses having transferred from analogue to digital systems in recent decades, everything is now measured and recorded. This effectively makes every business data-driven, whether they like it or not. So how will this change how a business runs?

“Currently most businesses are loaded with customer data, but only a small proportion is being used well” notes Kong from OpenAgent. “With the wider availability of AI tools and increased capabilities for computers to deal with large complex data sets, businesses can begin to learn a lot more about how customers behave, and really start to target individual customers.”

“At its simplest, data analysis tells you what is working in your business and what is not, allowing you to focus on areas that drive value. It can uncover opportunities for growth hidden in the complexity of everyday business” explains Roberts of Optus. She also expands on the use of artificial intelligence in big data. “AI will help businesses by finding the fastest way to meet customer needs, but businesses will still need to know their customers and what makes them loyal advocates.”

In essence, the future role of humans in big data is to focus on the big picture while AI and automation take care of the legwork.

According to Roberts, this shift will eventually bring about some fundamental changes to the shape of businesses and their relationships with customers. “The uptake of AI and big data will mean that, over time, businesses need to change the roles they need to serve their customers, and take into account new considerations such as ethical use of data.”

Building a framework for data-driven decision-making

Big data can be confusing – we humans simply aren’t designed to deal with huge amounts of information. But as it becomes ever more important to the future success of all organisations, even the most tech-phobic of C-suites and stakeholders will need to take it seriously. And when it comes to replacing hesitation with effectiveness, a solid framework is key.

One such framework is offered up by the Healthy Data Science Organisation, who boiled a complex task down six central principles:

• Understand the business and decision-making processes: How can data help your organisation become more efficient, better manage costs and grow? What are your big data goals?

• Establish performance metrics: What are you measuring, how are your measuring it, and what is considered success? “Have a very clearly defined business outcome, and ensure the value you will add with big data analytics is measurable,” instructs Roberts.

• Architect the end-to-end solution: How will the use of big data be implemented throughout the business? How will data be stored, accessed and manipulated? How will the data’s integrity be ensured?

• Build your toolbox of data science tricks: Starting with a small subset of data, learn the most efficient and productive ways to work with the data and the system.

• Unify your organisation’s data science vision: Those at the frontline of your data push need to be in sync with the business leaders and stakeholders from day one of the journey.

• Keep humans in the loop: Between smart tools, automation and artificial intelligence it’s possible to hand almost all data responsibility over to machines. But the human element of any data push is the most important, and must be a feature of all processes.

Big data = big risk?

While big data is the future, it’s important not to run headlong into it. By making endless data accessible to those within your own organisation, you may inadvertently make it accessible to outsiders too. Big data can therefore represent a big security risk for any organisation that doesn’t take security seriously.

EY’s Yi Fang Chua offers the following tips to ensure that you enjoy all the perks of big data, without the drawbacks:

• Understand the threats: “Key questions that organisation leaders should ask and have answers to include: What and where are your critical assets (e.g. infrastructure, data)? What is your ecosystem? Are they vulnerable to attacks? How are you securing?”
• Utilise proven security measures: “Many incidents and breaches can be prevented with practices which many may call ‘outdated’ in light of shiny new tech: application whitelisting, role based access control, two factor authentication, etc.”
• Create a culture of curiosity: “Cybersecurity and risk metrics have traditionally been focused on fast resolution and compliance. This can be misleading, as people may be overly focused on closing a ticket by adopting checklist approach, as opposed to seeking a holistic understanding of threats. Organisation leaders should encourage a risk aware, innovative and pre-emptive defence mentality to enable agile response (vs. reaction) to new and evolving tactics from the adversaries.”

How leading companies utilise big data

But how does all this theory translate into reality? We asked our experts how their own organisations, Australian leaders in the field, were currently utilising big data.

As an Australia-wide company that allows people to search for and compare real estate agents, OpenAgent is the perfect case study for big data done right, and their data strategy has played out in a myriad of ways. Kong cites an example: “One of the ways we harness big data is to better understand how customer interaction with our site indicates their likelihood to sell their property. We explore how different actions become early indicators. This is incredibly important to us as we are trying to create the most frictionless way to sell a property.”

Working in an industry whose mistakes are so often amplified and good work ignored, it’s perhaps unsurprising how Roberts and her team are utilising the ready access to information. “At Optus, we are using big data to listen to what our customers are telling us, and using this to address pain points.” It’s more beneficial to keep loyal customers than it is to find new ones, after all.

As a business that provides help to others who seek to effectively utilise big data, Cognizant has a slightly different perspective. “We help clients create integrated, personalised experiences that engage and influence customers,” explains Pinder. “Whether a business is working on long-term growth ambitions or is facing seasonal, temporary challenges, Cognizant can assist with predictive, scalable, platform-driven AI and analytics which allows businesses to respond quickly and smoothly to market opportunities and changes.” And by equipping other companies with the big data tools to succeed, they constantly improve their own.

If you showed 100 terabytes of business data to Sir Francis Bacon, he’d probably be a little confused. But if you told him (perhaps in Olde English) that this was the sum of your organisational knowledge, he’d recognise it for what it was – the power to grow into the best in your field.

Big data is no longer an extra-curricular subject in today’s marketplace. It’s a must for every business, from the independent retailer to the multinational conglomerate – and learning from those who lead the charge puts you in a good position to succeed in the information age.

Ready to take the next step in your data career? Explore career opportunities at some of Australia’s top companies:

Optus careers

EY careers

Cognizant careers

OpenAgent careers