Unlocking Enterprise Sales For Tech Companies

The Speaker’s Background: The speaker has been working in the data field for 15-18 years, holding roles in management consulting, banking, and currently as the Group CDO for a large organization. Their team focuses on creating a data culture within the organization, enabling better decision-making across various business units. Defining Data & IT Roles: The speaker clarifies the distinction between IT and Data teams: IT: Responsible for infrastructure (cloud, servers), applications, and operational systems. Data: Focuses on data management (capture, storage, governance) and data science (analytics, insights). They emphasize that while individuals should have a general understanding of all layers, specialization is key. The Team’s Approach: Innovation & R&D: The team acts as an internal R&D department, developing and experimenting with new data-driven solutions. IP Creation & Transfer: They aim to create reusable Intellectual Property (IP) and transfer it to other business units for implementation and scaling. The 3W Framework: A framework for operationalizing data culture: Ways of Thinking: Aligning with business strategy, governance, and AI maturity. Ways of Working: Talent development, funding, ecosystem partnerships, and adoption. Ways of Doing: Data science, data engineering, and data architecture. Working with Startups: Early-Stage Flexibility: During the experimentation phase, the team is open to working with various partners, including startups, with minimal initial guidelines. Production-Stage Rigor: As POCs move towards production, stricter guidelines are applied to ensure sustainability and mitigate risk. Focus on Business Needs: The primary focus is on solving business problems, not simply evaluating tools. Learning from Failure: Even failed experiments provide valuable learning experiences. Championing Solutions Internally: Framing is Key: Instead of pushing solutions on other teams, the focus is on understanding and addressing their specific business needs. Outside-In Approach: Solutions are presented as aligned with the business strategy and priorities of the target team. Creating a Library of Reusable Components: Sharing successful solutions and learnings across different business units within the organization. Working with System Integrators: Focus on Business Outcomes: Evaluation of system integrators is primarily based on their ability to deliver business value and solve specific problems. Knowledge Transfer: The team emphasizes the transfer of not just technology, but also knowledge, skills, and relationships with ecosystem partners. Overall, the speaker highlights a focus on: Business-driven innovation: Prioritizing business needs and aligning data initiatives with strategic goals. Collaboration and knowledge sharing: Fostering a culture of collaboration and knowledge transfer across the organization. Continuous learning and adaptation: Regularly reflecting on experiences and adjusting approaches based on learnings. Building a sustainable data culture: Developing the necessary capabilities, frameworks, and mindsets to enable long-term data-driven success. This summary provides a high-level overview of the speaker’s key points.