Industry leaders emphasised the importance of aligning data strategy with business objectives through adaptive governance, stakeholder engagement and robust data maturity frameworks to drive real-time decision-making, at the IT Indaba.
Aligning data strategy with business objectives for real-time decision-making was a key topic at the 2025 IT Indaba, where IT leaders explored how organisations can effectively integrate their data strategies with business goals to maintain a competitive edge in the age of AI.
IT strategist Alok Goswami opened the discussion by sharing hard-earned lessons from his experience as a CIO. He explained that many organisations rush to implement data strategies without ensuring they are aligned to core business objectives, often leading to misdirected investments and poor decision-making.
“One of the mistakes we made was finalising the data strategy too quickly. We created what seemed like a perfect data framework, but it turned out to be completely misaligned with organisational goals. The real question to consider is how do you make sure your data strategy is built at the right time, at the right pace, with the right approach,” he said.
He stressed that achieving alignment requires understanding the organisational context, capabilities and readiness to evolve into an AI-driven future. He noted that many long-established companies operate with “tunnel vision”, failing to adapt to emerging technologies and changing markets.
To address these gaps, Alok and his team introduced a data maturity model, an incremental framework that helps organisations assess their current position and progressively enhance their data capabilities. “When you adopt a data maturity approach, you start aligning your strategy to business objectives far more effectively,” he explained.
“It identifies your strengths, exposes weaknesses, and provides a roadmap for closing gaps in real time,” he added.
Alok also highlighted the importance of adaptive governance, moving away from rigid, traditional IT frameworks. “We shifted to a tiered, value-based governance model that considered market risks and business agility,” he said.
This, along with aligning process maps, value chains and federated data operating models, helped with faster, more informed decisions.
Adding to the discussion, Dr Makaziwe Makamba, digital transformation consultant and specialist on 4IR research, focused on balancing AI-driven insights with the pressing need for data privacy and protection.
“The balance requires a multifaceted approach and a robust data governance framework. As AI evolves, many people feed sensitive information into systems without understanding the privacy implications. Organisations must develop clear policies, educate employees and ensure compliance with data privacy laws such as the POPI Act,” she said.
Makaziwe further highlighted the need for stakeholder engagement and collaboration across departments to avoid data silos and duplication. “It’s okay to have fragmented data, but it must be unified in a way that supports decision-making. Without proper communication, organisations risk buying multiple tools that solve the same problem, leading to wasteful expenditure,” she concluded.
