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Post 4: Defining Measurable Objectives

Post 4: Defining Measurable Objectives

Now that the organization has a documented strategic vision for AI and a responsible, ethical approach for architecting and implementing, we can start defining individual projects, success metrics and key milestones.

For the first set of initiatives, we return to the short-term (1-3 year) objectives defined in an earlier phase, as those can yield results in as little as six months.  It is crucial for these initial AI projects to succeed, even if they're not the most technologically complicated or earth-shattering. Quickly showing an initial return on investment will help build organizational trust in AI system, win over additional champions, and secure additional funding for more complex initiatives.  

Projects must be technically feasible. Approaching AI with a grandiose vision will result in project selection that is impractical with current capabilities. Having trusted AI engineers conduct due diligence before starting a project can boost your confidence in its feasibility.  For these early projects, your AI team will likely need outside assistance from vendors and consultants; be sure to work with those that have domain knowledge into your specific needs.

Each initiative should include both quantitative and qualitative performance metrics to assess the progress of your AI strategy. Quantitative metrics could include:

  • Accuracy, Precision, and Recall
  • False Negative and False Positive Rates
  • Response Time
  • User Adoption
  • Overall System Throughput
  • Error Rate

Qualitative metrics could include:

  • User Satisfaction
  • Ease of User
  • Employee Adoption and Engagement
  • Stakeholder Feedback
  • Alignment with Defined Strategic Goals

For services with multiple components, establish milestones for each to demonstrate tangible progress to the team and the broader organization. One critical milestone is developing an early prototype, or minimum viable product (MVP), to gain credibility and deliver initial value to stakeholders. An early prototype can also help identify critical gaps in technology, usability, or scalability that need to be addressed.

In conclusion, by focusing on short-term objectives and ensuring initial projects are feasible and impactful the organization can build trust and secure further investment in AI initiatives. Early milestones such as developing a minimum viable product are essential for demonstrating value, gaining credibility, and identifying areas for improvement, and incorporating both quantitative and qualitative metrics will provide not only formal and informal feedback to your team, but the greater organization as a whole.

Contact us at right away to start a journey towards AI integrations that are based on facts. Let us show you the manifold possibilities on how to optimize your operations and strategy for your company.

Jayson Tobias

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