Why most data analytics projects fail — Wendy Lynch // Analytic-translator.com

Show Notes

• 01:40
  Delivering business value through data analytic projects

  A data project failing means it doesn't deliver the intended business value, which happens 85% of the time. Even when analytic executives claim success, the provided data often doesn't align with what the business team wanted.
• 02:35
  Factors driving data project failures

  Achieving success with data projects is challenging because there's a lack of effective communication between business executives and data scientists. Both groups often lack communication training, hindering the understanding of each other's objectives and needs.
• 04:06
  Communication barriers between data scientists and business leaders

  Data scientists' inclination to present uncertainties and complexities can leave business leaders unsure of their credibility. Additionally, data scientists' pursuit of innovative tools and elegant solutions can overshadow fulfilling the needs articulated by business leaders.
• 07:17
  Bridging the communication gap between data scientists and business leaders

  Empathy and embedding people on different sides of the organization will foster a deeper understanding of each other's challenges and needs. Additionally, adopting analytics language that makes sense to business leaders and offering data literacy training helps bridge the gap.
• 09:22
  Overcoming misunderstandings when handling analytic requests

  Requestors often have difficulty expressing their needs precisely, but analytic translators are trained to uncover a deeper understanding of the request. It's crucial to pinpoint the request's origin, its intended use, and the target audience to understand the requests objective thoroughly.
• 12:57
  Getting executive leadership buy in for an analytic translator

  Highlight the financial impacts incurred from redoing projects, wasted time, low morale, and reduced productivity due to misunderstood requests. Emphasize the potential gains in efficiency and improved decision-making when communication gaps between teams are bridged.
• 16:14
  Appreciation and understanding between data scientists and business teams

  Appreciation fosters understanding and acknowledgment of the challenges each team faces, promoting a collaborative environment. Failure to appreciate and understand each other leads to silos, decreased trust, and potential downward spirals in outcomes and relationships.
• 17:35
  The value of an analytic translator for organizations and data analytics projects

  By having an analytic translator bridge the communication gap between data scientists and business teams, you can double the return on analytics. Ultimately, data projects would be more successful, and employees would feel more appreciated in terms of their contributions.