The long-term planning (LTP) process is typically data rich but information poor. Ever wondered how to use AI and data driven solutions to derive insights quickly and efficiently from your LTP and community consultation? Join us to find out more.

Community infrastructure and investment planning requires decision makers to balance many competing factors, including resource constraints, strategic priorities, statutory requirements, flood recovery, and community feedback.

Artificial Intelligence (AI) and data driven solutions and can be leveraged to draw insights quickly and efficiently from the data heavy, information poor long-term planning process and community engagement surveys, allowing decision makers to collaboratively navigate this balancing act and unlock the value of new and existing investments and assets to.

  • Make the best investment choices for current and future generations.
  • Ensure there is active stewardship (Kaitiakitanga) of Council resources.
  • Maintain a strong alignment between individual investments and the Council’s long-term priorities.

Our presentation shares stories and lessons from working alongside local government authorities to navigate their long-term planning challenges. Embracing the principles of Rangatiratanga (collaborative decision-making) and Kaitiakitanga (stewardship), we discuss the application of AI and data driven solutions to enable informed decision making within complex environments.

Tom Garrett


Tom is passionate about delivering impactful change and continuous improvement for clients, as well as supporting people to grow and develop. He is a Senior Associate within Beca’s Tamaki Makaurau based Programme Advisory team. Outside of work he enjoys fishing, cycling, gardening, and collecting vinyl.

Courtney McCormick


Courtney is a Senior Consultant who leads Beca’s Programme Analytics service offering which focuses on providing data rich trusted insights and creating innovative data solutions to enhance decision making for major projects and programmes.
Concurrent Session A

Rangatiratanga | Tahi

Tuesday 21 May