As much as I enjoy dramatic reinterpretations, for this blog post I’m just going to talk to you about the complex challenges municipal organizations face in setting spending priorities. The complexity stems from competing aspects of the various projects vying for funding. Some of these factors are related to the funding source and whether or not the project requires debt and what kinds of debt are available. Can they be funded with cash, and if so, is it general fund or enterprise fund cash? Does it have a dedicated source of funding such as impact fees, grants, etc? Other factors that must be considered before establishing spending priorities include:

• Is regulatory approval is needed and where in the regulatory process is the project?
• What is the timeline for the project from design to construction?
• What is the project schedule in the Capital Improvement Plan (CIP)?
• Is the project propelled by a regulatory mandate or legal requirement?
• Is there a public demand for the project?
• Will it improve operations efficiency in some way?

The problem is further complicated by the fact that the information related to each of these factors resides in different places in the organization. Putting it all together in a coherent format and preventing important details from being forgotten or overlooked is a daunting task each year for budget directors and city managers. Frequently, at the end of the budgeting process, managers and elected officials are left wondering whether or not the correct spending priorities were set.

How can technology help? Data quality, data integration, business intelligence and analytics can be used to integrate the information and create a system that assigns a weight to the various factors. It could create priority spending recommendations that forecasts the most efficient and effective use of the funding sources available.

Data from finance, accounting and investments, CIP data, engineering, budget, programming, public sentiment, regulatory, legal data and other relevant data sources could all  be integrated and analytics applied to create the priority list. Managers and public officials could see which investments create the most long term efficiencies; which have funding and whether cash is available to avoid the long term expense of debt, all approvals, public support and CIP designation. The result is a higher degree of reliability and confidence in a process where uncertainty has reigned.