Jun 16, 2026 · 24 min · 9 segments
How does a city turn raw permitting data into real operational insight? In this episode, Accela CEO Noam Reininger and e.Republic Chief Innovation Officer Joe Morris talk with Rob Liddicoat, Deputy…
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Rob LiddicoatGuest
Noam ReiningerHost
Joe MorrisHost
Now, Rob, in terms of Stockton, maybe take us through what prompted the shift from using anecdotal data to true workflow KPIs.

Well, historically, and I suspect like most agencies, we've been relying a lot on assumptions and subjective explanations about our performance.

And, you know, if there was a complaint about a specific permit, it was easy enough to look into that one particular incident to figure out exactly what happened.

So a few years ago, when we added the enhanced reporting database, we were really excited to tap into our data to start seeing what we could do with it because we knew that the raw information that we needed was in there.

So we knew that we wanted clarity about our performance, but we also wanted better tools for our supervisors to be able to manage their teams and manage the projects that were in their queues.

And that was a really important point for us because there's usually several reviewers involved in a project and, you know, a single missed review will cause the entire project to miss its target.

We wanted clarity about where our sticking points were, where we needed to focus our improvement efforts, and how we could verify that those improvements were actually having the intended effect.

We knew we had a lot of raw information in Acela already, especially the workflow history data, but there wasn't a readily available way to turn that into actionable operational visibility.

And honestly, and this was super frustrating for me, being asked a very straightforward question like how long does it take to issue a permit? Very straightforward question on the surface, but we couldn't provide a straight answer to that because and it just wasn't acceptable anymore.

You know, what kind of a permit is it? How many review cycles did it go through? How long did it take the applicant to resubmit? Those are all very valid points.

But the raw data to be able to answer those types of questions was in the system.

We just needed a way to turn it into quantifiable information that we could really use.

Now, Rob, in terms of Stockton, maybe take us through what prompted the shift from using anecdotal data to true workflow KPIs.

Well, historically, and I suspect like most agencies, we've been relying a lot on assumptions and subjective explanations about our performance.

And, you know, if there was a complaint about a specific permit, it was easy enough to look into that one particular incident to figure out exactly what happened.

So a few years ago, when we added the enhanced reporting database, we were really excited to tap into our data to start seeing what we could do with it because we knew that the raw information that we needed was in there.

So we knew that we wanted clarity about our performance, but we also wanted better tools for our supervisors to be able to manage their teams and manage the projects that were in their queues.

And that was a really important point for us because there's usually several reviewers involved in a project and, you know, a single missed review will cause the entire project to miss its target.

We wanted clarity about where our sticking points were, where we needed to focus our improvement efforts, and how we could verify that those improvements were actually having the intended effect.

We knew we had a lot of raw information in Acela already, especially the workflow history data, but there wasn't a readily available way to turn that into actionable operational visibility.

And honestly, and this was super frustrating for me, being asked a very straightforward question like how long does it take to issue a permit? Very straightforward question on the surface, but we couldn't provide a straight answer to that because and it just wasn't acceptable anymore.

You know, what kind of a permit is it? How many review cycles did it go through? How long did it take the applicant to resubmit? Those are all very valid points.

But the raw data to be able to answer those types of questions was in the system.

We just needed a way to turn it into quantifiable information that we could really use.
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