Tips and Challenges

As we continue to drive data projects, familiar challenges begin to present themselves. By observing, we can become better diagnosticians of systemic issues. Learn what to avoid and how to navigate them better.

🚩Lack of Data Intelligence in Leaders or Stakeholders
💪Model transparent decision making using data at the executive level.
💪Integrate data into decision making across all functions.
💪Set expectations for performance management to apply data effectively.
✔️Infuse manager support mechanisms with awareness and development tools for better advocacy of data intelligence.

🚩Perception that Machine Learning and Artificial Intelligence are a Black Box
💪Balance automation benefits with a focus on organizational culture.
💪Highlight benefits that enable employee and organizational evolution.
💪Tell a holistic value story; do not overemphasize automation as the primary benefit, undermining other benefits.
✔️Align benefits with your organizational culture for a more successful adoption.

🚩Perception that Everyone is an Analyst
💪Leverage data science automation for greater agility and faster decision-making.
💪Aim to become silo-busters to view development-to-production processes transparently.
💪Combine data science with report automation, so dashboards are not the main output.
✔️Use AutoML platforms to empower teams and accelerate data science adoption.

🚩Perception that Data (including ML or AI) is Inherently Ethical & Objective
💪 Consider ethics at every aspect of the data supply chain—from discovery through consumption.
💪Incorporate ethical considerations in generating business models and forming teams.
💪Help drive awareness of how data systems are inherently biased; be aware of the impact of biases.
✔️#Collaboration and consensus are critical to addressing inherent blind spots and ensuring trustworthiness.

🚩Perception that Data is Free
💪Understand that data requires ongoing staff, processes, and technology investment.
💪Invest in workforce digital upskilling for increased data fluency.
💪Drive awareness that data is NOT free; it comes with storage costs. It requires skills to mine and prep. Help drive awareness of the legal obligations and rights associated with its use.
✔️Address legal rights to use data early in the data strategy to avoid unintentional violations and confusion of data sharing or data ownership.


🎯What red flags have you encountered, and how have you navigated them?