Tech leaders urged to develop adaptable data strategies

Many companies are facing difficulties with their data management. Issues like data silos, complex regulations, and rapid changes in AI and analytics can hinder growth. Gowtham Chilakapati, a data and AI expert at Humana, shares insights from his experience transforming data strategies in various industries. A successful data strategy must align with business goals. Companies often falter when they pursue data initiatives without clear objectives. For example, if a business aims to reduce customer churn by 15%, it should use predictive analytics to understand customer behavior. This approach can lead to improved retention rates. To align the strategy with business objectives, companies should define key performance indicators (KPIs) and identify specific use cases. It is also important to secure support from executives to create a data-driven culture and treat data as a valuable asset. As data volumes increase, businesses should adopt scalable architectures. Chilakapati has worked on migrating data systems to cloud-based models, which can enhance processing speed and integrate AI more easily. Suggested solutions include cloud-first models like AWS and Azure, data lakehouse architectures, and API-driven integration for better connectivity. Data governance is essential for maintaining security and integrity. Companies should establish clear data roles, automate compliance checks, and implement privacy measures. A strong governance framework builds trust and aligns operations with regulations. Manual data processing remains inefficient. Technologies like AI-powered ETL pipelines can significantly reduce data processing times. Implementing real-time monitoring and predictive maintenance can also improve decision-making and operational efficiency. Creating a data-driven culture is vital. Companies should offer training in data tools to promote literacy among employees. Leadership should advocate for data-informed decisions and encourage collaboration across teams. Lastly, a data strategy must be flexible and evolve over time. Monitoring systems and regular audits are critical for maintaining accuracy and adapting to changes. Organizations that continuously refine their strategies will remain resilient and gain an advantage in the digital landscape.