A fusion of data skills and human skills to drive performance
Key skills for successful data-driven decision-making
Increasingly, research supports that organisations must take bold steps to break down siloed data cultures and embrace a fusion of skills that can provide a competitive advantage in the digital age. Leveraging data assets to inform business strategies and drive performance requires mastering a range of critical skills, including:
Data skills are critical for data-driven decision-making. These skills include:
● Data analysis: the ability to collect, clean, and analyse data to identify trends and patterns
● Data visualisation: the ability to create visual representations of data to make it easier to understand
● Data management: the ability to store, organise, and maintain data efficiently
● Data ethics: the ability to handle data ethically and responsibly
AI and tech skills are also crucial for bridging the data skills gap. These skills include:
● AI literacy: the ability to understand and use AI technologies, concepts, and applications in the workplace efficiently
● Technical skills: the ability to write code and work with different programming languages
● Machine learning: the ability to develop and implement algorithms that can learn from data and make predictions
Human skills are equally important in a data-driven culture. These skills include:
● Empathetic leadership: the ability to actively listen to problems and empower others to take action based on data-driven insights
● Collaboration and communication: the ability to work effectively with others and communicate complex ideas clearly
● Innovation: the ability to think creatively and develop new and innovative solutions to problems using data.
● Critical thinking and problem-solving: the ability to analyse problems and develop creative solutions
● Project management: the ability to manage projects effectively from start to finish
● Ethics and responsible leadership: the ability to ensure responsible use of data and AI technologies and navigate the ethical challenges posed by the adoption of AI and advanced data technologies
The most important skills identified by senior leaders:
Data analysis
Data analysis is considered the most crucial data skill by 51% of employees, followed by data management (46%), data security (41%), and data visualisation (28%). Senior decision-makers identify gaps in data literacy (37%), management and database design (23%), privacy and security (21%), storytelling and communication (19%), and analysis and visualisation (19%) as significant barriers to their organisations' and teams' success. The average rating of the extent of their organisation's skill gap is 3 out of 5, signifying a moderate gap. This shows that while technical skills are essential, human skills such as leadership, collaboration and communication are crucial for unlocking the full potential of data-driven decision-making. 70% of employees believe that human skills such as problem-solving and communication are just as critical as technical skills for data-related roles. Over a third (36%) of employees believe that developing work-ready human skills (empathetic leadership, collaboration, interpersonal skills) would enhance their ability to interpret and leverage data.
Robin Sutara
Field Chief Transformation Officer, Databricks | Previous CDO and COO
Robin Sutara is the Field Chief Transformation Officer at Databricks and a seasoned executive with previous experience as CDO and COO at Microsoft. Robin highlights the disconnect between leadership and employee perceptions of data proficiency and discusses how AI, particularly generative AI, risks exacerbating this gap. She emphasises the importance of understanding the business implications of AI beyond just the technical aspects. Robin advocates for a paradigm shift in organisational learning culture, promoting a more holistic approach towards skills development and enablement for the future.