Data is abundant in today’s business environment, but effectively managing and leveraging it for decision-making is a challenge. The 2023 report by Nash Squared highlights that only a quarter of digital leaders consider their organizations highly effective at using data insights to generate revenue, despite recognizing the importance of data and analytics for return on investment. Businesses of all sizes struggle to extract value from data, with medium-sized enterprises particularly lacking the sophistication to handle large volumes of data. To address these challenges, there are five fundamental principles for success:
1. Begin with a bold vision: The data strategy should be led by the business, with IT playing a supporting role. By starting with an ambitious outcome and working backward, IT can align the strategy with the business goals, balancing dreams with practicality.
2. Establish a value exchange: It is crucial for individuals across the organization to have a vested interest in making data work. Data strategy should align with the priorities and needs of different functions, promoting collaboration and mutual reinforcement. This value exchange should be supported by the data architecture design.
3. Look beyond technical aspects: Data strategy goes beyond technicalities; it requires efficient governance, clear ownership, adequate support and training, and a data-oriented culture. A holistic approach that encompasses these supporting features can bring transformative effects.
4. The role of the Chief Digital Officer: The Chief Digital Officer (CDO) or technology leader should be an agent of change, bridging the gap between business performance and data & technology. Technical expertise is important but should be supplemented by the ability to understand commercial aspects. The CDO should have direct access to the CEO and/or Board for effective decision-making.
5. The importance of good data in AI: The increasing interest in AI emphasizes the need for high-quality data. Before implementing AI solutions, organizations should establish a solid data strategy and ensure it meets business needs. AI can enhance data utilization but also creates additional data management challenges. Clear policies on data usage are required, particularly when using Generative AI engines.
Data is a crucial asset for businesses in the digital age, and by following these principles and seeking technical advice, organizations can transform their data practices to drive profitability, customer satisfaction, and informed decision-making.
