We New Orleanians know how to make a good cocktail. One of the great mixology lessons we’ve learned is that nearly every classic drink -- the sazerac, the daiquiri, the French 75 -- share the same basic recipe: start with booze and add something a little sweet and something a little sour or bitter. With this handy, rule-of-thumb recipe, you can make countless delicious drinks.

When we’re not perfecting our Ramos gin fizz, we’re focused on applying data analytics to solve problems facing city departments and the residents they serve. And just like making a good drink, we find it helpful to have a handful of generic typologies (or “recipes”) of how analytics can be applied to create value. With just a few of these typologies at your disposal, you can find hundreds of different applications for data analytics in city government and beyond -- from ambulance placements to zoning inspections.

Looking across the many projects that have been delivered in city governments (in New Orleans and elsewhere), some common typologies (recipes) emerge:

1. Finding the needle in a haystack. Where a department is tasked with finding a small number of individuals - either those at high-risk or those most likely to be non-compliers - predictive modelling can be used to identify targets based on existing data sources. This intelligence can save time and resources and minimize the risk of misfires.
2. Prioritizing work for impact. In many agencies, large backlogs of unfinished work accumulate and tasks are assigned by constituent complaints, on a first-come-first-served basis, or at random. Analytics can be used to prioritize high-impact or easy-to-resolve cases so that better results can be achieved within existing resource constraints. It was former City of New York Chief Analytics Officer Mike Flowers’ insight on how this approach could help departments that started our own analytics journey in New Orleans.
3. Early warning tools. Instead of reacting to the problem after the fact, analytics can help predict service need, allowing predictive deployment of resources, often saving money in the process.
4. Better, quicker decisions. Where services involve repeated operational decisions, recommendation tools can use data on prior cases to assist departments in making better, faster, more consistent judgements.
5. Optimizing resource allocation. When service resources have been scheduled or deployed in the same way for a long time, despite changing patterns of need, analytics can unlock improved efficiency through data-driven deployment of resources.
6. Experimenting for what works. Low-cost testing approaches can bring experimental rigor to refine and improve services, including behavioral approaches to improve service take-up. Experiments can also help uncover those services that work well and those that need adjustments.

New Orleans has a lot of momentum from early wins in applying data analytics to help improve service delivery, but we are just scratching surface of what we can do. This fall we’ll be reaching out citywide, asking you to help us develop new project ideas on how analytics can give departments an edge and deliver services more effectively.

We invite you to review our new webpage to explore the six typologies of NOLAlytics projects we’ve identified and to pitch a project idea. We hope you’ll find this site a helpful resource in thinking through how we can use data to add value to your work.

Please be in touch with your ideas, feedback, and drink recipes.

Oliver Wise is the director of the City of New Orleans Office of Performance and Accountability. Alex Williamson is the Analytics Project Manager with the Office of Performance and Accountability. Richard Todd is a summer fellow at the Office of Performance and Accountability and is a MPA candidate at Princeton University’s Woodrow Wilson School.