How to leverage data analytics and AI for business success

Rapid advancements in data analytics and AI can be daunting, especially when it comes to harnessing these technologies to create tangible business value. It is crucial for board directors to understand how to harness the power of data and AI to drive strategic outcomes.

Melbourne Business School's (MBS) Centre for Business Analytics (CfBA) business analytics expert Yalçın Akçay said the fact that generative AI is available to anyone is a game changer, putting very powerful tools in the hands of a much broader audience. But for an organisation to have talent and skills, plus a data ecosystem is not enough, he said.

"On top of that, you have to have the right culture and a solid governance structure to ensure the right decision-making process is carefully embedded throughout the organisation. Then on top of all of that is a need for clear strategy and strong leadership, which includes the role of the company board.

"These factors are critical to achieving analytics maturity. They are often the difference between success and stagnation for an organisation's analytics journey. Understanding where you sit helps you understand your growth."

About 20 per cent of organisational data is "structured" and the remainder is "unstructured" data, according to Gartner Inc research. Directors should be assessing what data types drive their board decisions and strategies, said experienced director and Melbourne University Deputy Chancellor Wendy Stops GAICD.

Other board considerations should be about how to maximise the potential of data across your operations and for unstructured data, including social media, emails, blogs and other web-based information, having a clear assessment of risks they might pose was essential, said Stops.

The board also should know where the organisation is using AI and understand whether it is aligned with what you're trying to achieve and the business strategies you have.

Return on investment

Global spending in big data and analytics was valued at US$272 billion in 2022 and US$308 billion in 2023, according to Fortune Business Insights, Market Research Report, 2023. The projected spend for 2030 is US$745 billion.

Return on investment is not always clear, noted Akçay, but Centre for Business Analytics research indicates that the impact can be significant.

"In today's ultra-competitive business environment, where organisations have very limited leverage to improve profitability, data analytics represents a powerful opportunity to unlock additional value and essentially drive sustainable growth," he said.

Successful analytics leaders have a clear data analytics and AI strategy and a roadmap that is aligned with their broader business goals. "This is not something left to chance or treated as a side project. Instead, it is spearheaded by a C-suite or a director-level executive, ensuring it remains a top priority for the organisation," said Akçay.

"These organisations understand the critical importance of knowledge and training, including their executive leaders and board directors when it comes to analytics, so this commitment to continuous learning is actually a key factor in their ability to extract maximum value from their data and keep them in the leadership position."

He added that simplifying the roadmap can enable comprehensive analysis and truly informed decision-making:

• Identify the relevant data that supports key business objectives
• Secure this data, its efficient storage and make data accessible to the right people when they need it
• Integrate the data from various sources into a single, unified view

The key enabler of the data strategy is governance. Oversight used to be centralised into the IT department, however, now a more modern approach is "very decentralised and involves accountability across all stakeholders in the organisation".

"It ensures that data is managed and used responsibly by everyone," said Akçay. "Governance supports regulatory compliance in a more flexible way, so it enables innovation while still maintaining the legal and ethical standards."

There should be a typical governance approach to AI, said Stops. However, the issues of ethics, privacy, bias, fairness and discrimination will require a slightly different lens in terms of risk management.

To avoid failure, Stops stressed that organisations could begin with deciding, "What's our strategy? What are we trying to achieve? What problems are we trying to solve and how can we go about solving that problem?"

Governance needs to be addressed at the enterprise and the board levels, she added. "Who is leading the analytics governance at the executive board level? If it's too far down the organisation, then you're not leading from the top. It needs to be led from the top and at the board level."

Stops highlighted some questions directors could be asking, including, "Is it the audit and risk committee that's taking the oversight of this? Is it the board as a whole? What's the right answer for your organisation? Is there sufficient accountability and drive from these top levels?"

This is an edited version of an AICD webinar presented by the Melbourne Business School (MBS) Centre for Business Analytics (CfBA) live on 24 October 2024. The full recording is available until 14 October 2025. Download the recording now.

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