Converting data analytics into maximum business value — Wendy Lynch // Analytic-translator.com

Show Notes

• 01:39
  Striking a balance between complexity and clarity when communicating data insights

  Data scientists need to focus on delivering clear, actionable insights instead of presenting overly complex scenarios or technical details. They should prioritize addressing the core question or decision the business seeks to resolve, aiming for concise and relevant communication.
• 04:44
  Best practices for communicating value for a business via data analytics

  To communicate effectively, data scientists must consider the audience's expertise level and align results with the action or decision to be made. Simplify results to concise, specific statements without complex qualifiers, ensuring clarity in the presentation.
• 07:32
  Optimizing data communication with an analytic translator

  An analytic translator can help bridge the communication gap between data scientists and business stakeholders. They can convert complex data findings into understandable language for practical use without devaluing the discoveries of the data scientists.
• 10:11
  Aligning business goals with analytics requests

  Many companies arent aligning their goals with the analytics they request because leaders dont know the right questions to ask data analysts. Its crucial to have a go-between to translate what the data scientists can accomplish to executives in order to achieve alignment.
• 12:34
  Fostering collaboration for successful analytics and business goal alignment

  Both data scientists and business leaders need to have an openness and willingness to learn when it comes to analytics and business value. Clear goal setting and a shared understanding of purpose at every level are crucial for successful outcomes.
• 14:01
  Data literacy and its limitations in organizations

  Beyond data literacy, people and business literacy must be taken into consideration. By taking an integrated approach, individuals can be trained based on their different literacies to bridge gaps rather than enforcing universal data literacy across the board.
• 17:14
  Insight driven decisions vs. data literacy across an organization

  Fostering insight-driven decisions, not universal data literacy, is key across the organization. Leveraging data literacy, translation, business and people literacy skills within teams maximizes success more effectively than expecting data literacy.
• 19:25
  Maximizing business value from analytics

  Business leaders should be open to learning and asking bigger questions about the possibilities within their organization's data. Having a high-level analytic translator can help leaders grasp what's possible and bridge the gap between data scientists and business needs for better value from analytics.