SASchat: Seven Thought Leaders explored the Power of Analytics Leadership
In a recent SASchat 7 thought leaders discussed with interested participants why analytics leadership is essential for a prosperous modern organization. This article is a summary of a lively discussion of the following experts:
- Jack Phillips – CEO & Co-Founder of International Institute of Analytics (IIA)
- Prof. Riaan de Jongh – Director Centre of Business Mathematics and Informatics (BMI), Senior Manager - Chief Scientist
- Dr. Daniel Yar Hamidi – Expert by Research and Practice; Corporate Governance & Digital Transformation
- Christer Bodell – Director Automotive and Manufacturing at Capgemini
- Josefin Rosén – AI & Analytics Leader at SAS
- Murray de Villiers – Director Education at SAS
- Patric Hellgren – Director Analytics Value Training EMEA at SAS
7 thought leaders explored various aspects of analytics leadership. They defined analytics leadership as encompassing both analytical leadership and leaders of analytics, emphasizing the ability to make analytics valuable, understandable, and drive change.
They highlighted the importance of investing in analytics leadership for long-term organizational success, enabling informed decision-making based on data driven insights, leading to optimized profitability and reduced costs. It serves as a catalyst for driving strategic initiatives, identifying growth opportunities, managing risks, and ensuring sustained business success.
The key disciplines of analytics leadership were identified as mathematics, statistics, AI, machine learning, operations research, and information systems. Additionally, analytics leaders should have a deep understanding of the application area, proficiency in project management methodology, and creative thinking. They should address disciplines such as the Analytics Lifecycle, Competencies, Organizational Analytics Maturity, Business Deployment, Value, and Ethics. Collaboration among Business, IT, and Analytics disciplines was stressed, along with establishing a common understanding of AI.
Critical qualities for analytics leaders included business knowledge, understanding the unique aspects of AI transformation, operationalization, and use cases, as well as empathy and a people mindset. They should possess a combination of hard skills in technology and AI, along with soft skills in communication, problem-solving, curiosity, and teamwork. Analytics leaders should demonstrate a balance of IQ, EQ, XQ, and AQ, foster collaboration, and have a track record of successful project delivery.
To develop necessary skills and competencies, experts suggested focusing on developing weaker areas, gaining hands-on experience through diverse analytical projects, participating in structured Analytics Leadership Programs, and engaging with industry networks and communities for knowledge sharing.
In terms of universities' role, it was discussed that they can integrate theory with practical examples by involving professionals from the business and public sectors to share insights on applying AI, including compliance and ethics. Collaboration between industry and universities, with government support, was emphasized to address the skills gap. This collaboration can lead to specialized programs, investment in training, and the establishment of data science communities. Universities can engage with the industry through industry-standard methods, hackathons, and aligning AI use cases with business issues. Higher education institutions were seen as crucial in training future leaders, offering relevant programs, conducting research, and promoting knowledge sharing. Industry support was expected in providing opportunities and financial assistance.
Overall, the spirited discussion emphasized the crucial role of analytics leadership in harnessing the power of data and driving organizational success in the digital age.
