With people working in parallel with machines and increasingly yielding autonomy to them through analytics and AI, data is playing a larger role in business decision making. However, many Australian executives are still struggling to fully trust data and analytics. KPMG’s Guardians of Trust survey reveals one in four C-level executives in Australian organisations don’t trust the way data is used.
Australia isn’t isolated. Globally, only a minority of executives have a high level of trust in their own organisation’s use of different types of analytics. A significant proportion have limited trust or active distrust, which includes a reluctance to even use analytics. Worryingly, the trust gap is not reducing with experience or time.
Part of the problem is that it’s unclear who within the organisation has primary responsibility for ensuring the trustworthiness and accuracy of advanced analytics and models. Most say it should be the domain of IT, but responsibility is currently split across a wide number of roles and departments, from data scientists to “all users of data and analytics within the organisation”.
The specialised nature of analytics is an issue. Executives and managers are asked to make major decisions based on the output of an algorithm they didn’t create and don’t always fully understand. AI systems are seen as a “black box”.
Across different departments, trust is lowest among Australian marketing departments. Only 53 percent proclaimed their trust, and 44 percent their distrust. In Australia, Human Resources was the most trusting, at 74 percent, followed by IT departments at 69 percent.
Perhaps IT departments are likely to be more trusting because they have the technical grasp of how the data is gathered and stored. By comparison, as guardians of the customer, CMOs and CXOs understand accurate data relies on a deep value exchange. Accuracy and depth comes with valued connections with your brand, an area in need of continual improvement for most organisations, in addition to turning data into actionable insights.
What is clear is businesses want the benefits digital and automation can deliver. This means they need to be able to trust the underlying analytics that power those machines.
What is needed is a new approach to data and analytics, building governance of AI into the core business.
AI systems are seen as a “black box”, which makes it hard for people outside the creator to trust them. As we’ve seen with consumer technologies such as online shopping and chatbots, it can take repeated use over many years to build trust. Education can help bridge this trust gap earlier, demonstrating how and why technology initiatives can empower an organisation.
Board level buy-in
Building an effective framework must be a board priority, from structure, roles and regulations to processes, technology and alliances. There needs to be a more holistic strategy and accountability, which means better alignment at executive level and real collaboration by the people on the ground.
Data and Analytics needs to be proactively governed in ways that build integrity, quality and effectiveness. This will allow Australian organisations, as well as their global counterparts, to build trust in the technologies that they are staking their future on, and realise the benefits of their investment.
In the digital age, trusted analytics is a critical source of competitive advantage. Because of this, trust in data is critical. Bad data quality has dangerous implications for organisations, with short and longer-term ramifications on staff, suppliers, customers and reputations.
Gone are the days when IT can be the catchall for anything related to technology. Instead, it’s time for the business to take responsibility for its analytics and AI. CEOs and other executives will need to manage machines as rigorously as they manage their people. Such an approach requires standards and controls that go beyond the operational to also focus on the cultural, ethical and other emerging considerations for managing advanced technology across the enterprise.
As organisations increasingly use data to drive better decisions and their business models, those actively leading in trust and accountability will be most likely to see benefits flow through to the bottom line.