How Orange County Courts’ Data Modernization Became a Benchmark of Judicial Innovation

Transcript

This has been generated by AI and optimized by a human. 

Show ID [00:00:00]:
The power of data is undeniable, and unharnessed, it's nothing but chaos. 

The amount of data was crazy. 

Can I trust it? 

You will waste money. 

Held together with duct tape. 

Doomed to failure.

This season, we're solving problems in real time to reveal the art of the possible. Making data your ally, using it to lead with confidence and clarity, helping communities and people thrive.

This is Data-Driven Leadership, a show by Resultant. 

Jess Carter [00:00:34]:
Hello, everyone. Welcome to today's episode. I'm really excited about this conversation because we're diving into the world of the judicial system, specifically the California courts. Courts are obviously an indispensable part of our society. They play a critical role in administering justice, resolving disputes, and ensuring that legal rights are upheld, which affects all of us.

What makes this topic particularly intriguing is that while we're exploring in the context of the judicial system, we're going to uncover things that all data-driven leaders face today. Many organizations struggle with data management, transparency, timeliness, and those are just constant themes we hear about on the podcast. Today, as we focus on California, one of the things I didn't know until we started working on this episode is that it has the largest court system in the United States, serving over 39 million people, about 12 percent of the total U. S. population. This vast system includes the Supreme Court, the Courts of Appeal, the Superior Courts, each handling a wide array of cases ranging from minor infractions to significant criminal matters. But let's narrow it down even further. Our spotlight today is on Orange County, one of the largest counties in California and a leader in judicial innovation.

I've never said that sentence before, judicial innovation. Wait till you hear more. Did you know that Orange County has a population larger than the entire state of Arkansas? Orange County has been able to lead in integrating advanced technologies into its court system, making it a benchmark for others to follow.

They have so many awards, it's kind of unbelievable. They were experiencing something I imagine many of you data-driven leaders have experienced. Things like disparate data across multiple systems that was keeping them from the outcomes they wanted. Today, specifically, we are talking about how they turned to Snowflake Data Cloud, centralizing all of their data into a single platform.

This move enabled them to streamline operations, reduce case backlogs, and make more informed decisions using analytics. Snowflake's secure data sharing feature also facilitated better collaboration with other counties in the state, leading to improved resource allocation and even securing 60 million dollars in additional funding.

Today, I have the honor of speaking with Darren Dang, the chief financial administrative officer at Orange County. He has been at the forefront of these initiatives and will share insights on how they were successfully executed. His expertise and experience make him the perfect person to explain why Orange County stands out as an innovator in court data management.

I am thrilled to hear Darren's thoughts on the challenges they faced, the successes they achieved, and the opportunities that lie ahead. And we give you a quick blurb at the end for any data-driven leader that's maybe passionate about leaving the world in a better place than they found it. And whether you should step into the public sector as well.

We couldn't help ourselves. So without further ado, let's dive into this exciting conversation. 

Welcome back to Data-Driven Leadership. I'm your host, Jess Carter. And today we have Darren Dang, chief financial and administrative officer at the Superior Court of California, Orange County. Let's get into it.

Darren, welcome.

Darren Dang [00:03:50]:
Thank you for having me.

Jess Carter [00:03:51]:
Yeah, thank you for being here. So first things first, I would like to make you uncomfortable immediately as we get to know each other and make you gloat about some awards I believe you guys have won recently. Are you familiar with, it looks like there's three different, I don't know what they are. Do you say NACM, NACM awards?

Darren Dang [00:04:11]:
NACM.

Jess Carter [00:04:11]:
NACM. Can you tell me about those?

Darren Dang [00:04:13]:
National Association of Court Managers. We've won so many different awards, so I'm not exactly sure which ones you're referring to. It's a good problem to have. It's probably for data-driven insights and a couple more. So, uh, refresh my memory, but it's really not about awards. It's, you know, what we're able to do. So let's just move on with the program and get to the core. Who cares about awards?

Jess Carter [00:04:42]:
I think that that is awesome and spoken like a true civic-hearted leader. And so, um, I really appreciate you being here, but truly, I mean, it is, it's impressive and it's, it always stands out to me when a public entity wins awards for data-driven leadership or insights.

And so, you know, I wanted to invite, if you had anything you wanted to talk about that you know, if you know what projects led to those awards, or if you just want to start to talk about, you know, some of this Snowflake project, we can do either way. What, where would you like to begin today?

Darren Dang [00:05:11]:
Well, I think it's kind of related and, and it is not to gloat, but I think our approach and our court in Orange County, in California is slightly different than most other public sector or public entities in the sense that, you know, I came from the private sector.

And I purposefully entered the public sector for a reason, because I want to lift all boats, and I really wanted to make a difference. Actually, I think September 29th is going to be my 10 years at the Orange County Superior Courts. And so it's been a long celebration, but really, the reason why I entered public service and I've been in public service for at least 25 years now is to make a difference.

And one of the ways that you can make a difference is, throughout my entire career, I've been very data driven, and it's all about data. Communication with data, and how do you tell that story in an impactful way? Because many of us are very visual, right? And so I think part of the reason why we won the award was because of our use of data.

But more importantly, it's about our court and our data culture and evangelizing data. And not only that, one of our core mantra is to make sure that whatever we do is portable and scalable. And what I mean by that is I understand the pains of the challenges being in public sector. We never have enough resources.

We don't have access to the best quality resource. So we've been able to really work with public-private partnerships and to really with the core architecture in mind of, hey, whatever we design, it should be something that another court, whether it's a two-judge court, a really tiny court, or a large court can leverage the work that we've done.

So that to me is portability and scalability is whatever we do. A small, tiny two-judge court can use that or, and not just limited to courts or public sector, other public sector entities could use it as well as private. So we try to look for universal problems and universal approaches that is not just very specific to our geography or our domain.

And so I think that's, that's where we have been recognized. Uh, and not only just, we don't just focus on the technology. We focus on people, process, and technology. So it's really kind of the culmination of all those things, all those components and pieces coming together. And we share, share a journey and really at the end of the day is about change management.

And, you know, I really eventualize that. And how do we incorporate that and, and really focus on the business needs, right? What are the key drivers?

Jess Carter [00:07:47]:
Yeah, absolutely. Well, and when I, when I listened to the story and I want to call some of these points out as we talk is, to me, it resembles these changes. I like that you talk about people, process and technology.

It's not just technology for technology's sake. I always say that if we're doing that, then we just have too much funding in an IT department. It's for the intended outcomes of your business and to fulfill your mission, right? But it seems like your technology advances really led to operational efficiency, statewide data sharing, improved funding advocacy.

Those are three things that really stood out to me. So I was going to ask you if you'd, can we kind of talk through each of those three things?

Jess Carter [00:08:25]:
So operational efficiency is the first one. And so I think, you know, when I, when we talk about operational efficiency, what does that mean to you in this project? What efficiencies did, were you actually able to gain in the core system?

Darren Dang [00:08:36]:
So, as I mentioned earlier, the core is always to look at what business problem are you trying to solve? Right. So for us, it's not just about operational efficiency. We have this acronym and you'll find that I'd love acronyms. It's CASE, C-A-S-E, CASE for Improving Capacity, A for Enhancing Access, S for Service and E for Efficiency.

So it incorporates all those things. And really at the end of the day, you just need to look at what are the key drivers, what is your organization about? And so CASE really encapsulates our mission and key drivers, right? And so, data really helps us get insight into each of those different areas. And so for us, access is really important.

Like, who do we serve? So we need to know who our customers are. And one of the core things for the courts is really due process. So for example, when COVID came, one of the key things is that. It's specifically when it comes to felony cases that in terms of due process is within ten days of arraignment that you have to have a preliminary hearing.

Right? For due process. And as you know, during COVID, places shut down. So by having data, we knew exactly which defendants, which cases are pushing that ten days. So we, we knew what our pipeline is, what our work queue is. And then from a capacity standpoint, we need to figure out who's available, what departments are available, what staffing is available.

And then also there's working with our stakeholders, too. Uh, the sheriffs to transport people and social distancing and all those different things. But all the data components came together to make sure. So we use all those to arrange the scheduling to make sure that, you know, due process is in place. We were one of the first courts to have hearings.

Other jurisdictions took a long time. So by having data, it really helps provide visibility into our, our pipeline, our workflow. Right? And an insight into our business. And it doesn't matter what domain or what industry you're in. There's definitely some sort of workflow, some sort of process, right? That you have to go through, whether it's customer acquisition, customer service, or expanding market share, marketing.

There's still a pipeline. There's still a process. And having data gives you insight into where you are along that pipeline, and looking for opportunities to make it more efficient and more effective. For us in public service, access is also very important. Like, who do we serve? How do we, you know, being, being a refugee and English as a second language, the self-represented language is very important for us, right?

So, another area where we've been able to use data is to figure out who we serve and where the services are. This is for self-represented legal against people who can't afford an attorney. So we have workshops in different areas. So by looking at the data, we can see where the concentration of usage are.

So during COVID, we consolidated some of that. So we had fewer, but more impactful workshops, right? And then we went to online, too. So we were able to be fewer resources, be more efficient.

Jess Carter [00:11:40]:
Listening to your perspective, there's this really interesting reflection on how do you actually make a difference and what are the right KPIs, like timeliness, accuracy, etc.

And your ability to leverage. I mean, I just. I can't stop thinking about that example of how do you drive the right workshops in the right places for the best outcome and for the most value, not even resourcing, but social distancing just created a limiter there. You guys were able to be, you know, highly effective in that way.

Did you already have your Snowflake solution set up at that time?

Darren Dang [00:12:11]:
So we had a couple of years in the works. We had maybe three years in the works that in terms of building our data warehouse, and we had some support from the outside, you know, Resultant helped us design our data warehouse.

And so we were pretty well up and running by then. There were some additional data points that we didn't have. Our Snowflake data warehouse was primarily case management information. So, basically, we had three different case management systems: Criminal, Civil, Family Law, and Juvenile. And they were all different, by different vendors.

Some Oracle, some were SQL. And so, by having that data warehouse, we, for the first time, were able to get a global view of all the cases, all in one place, without having three different teams run three different queries. And so, having this universal dashboard, universal visibility into our business process was very helpful.

COVID was, uh, was a nice test, but having some of that infrastructure in place was very helpful.

Jess Carter [00:13:14]:
So, Darren, another question I had for you was about one of the things we talked about that was a real value add, was the statewide data sharing. So, I was trying to understand, does the work that you've done using Snowflake, et cetera, has it changed the way you guys collaborate with other courts or other counties?

Darren Dang [00:13:30]:
Yes, it has. So there's a statewide standard that we all use to report information to our administrative agency, to a centralized agency. So, so there's that standard. So having standards is really important for shareability and portability. Nationally, there's some other standards, NODs, National Open Data Standards.

And so, once we had JBSIS, we're now in the process of porting it over to NODs. So that way we could share and we could create that blueprint.

The schema that we use became kind of the blueprint for other courts. And so there's a process, there's a phase one where five to six courts.

Uh, came on and then we're now in the middle of phase two, another five to ten courts. And so there's a statewide rollout and then nationally we can share it with other courts, and other states, too. And the same blueprint can be used by, by other agencies.

Jess Carter [00:14:20]:
That's amazing. And when it comes to data sharing, are there better outcomes? Like, are you seeing more timely decisions being made because of that data sharing?

Darren Dang [00:14:29]:
By us all having that data, the same JBSIS standard, other courts can take what we do, and when it comes to advocacy, and also public accountability, those reporting structure facilitates better aggregation of data, right?

So, so you're looking at things from the same perspective. Now, there's going to be slight variances in terms of how different entities, uh, code different things, right? So it's getting that data catalog and getting alignment in how is a Fuji apple a Fuji apple, not a Gala apple, right? And so, once you have all those alignment, then we can use it for advocacy, because a lot of times, the legislature wants to know, you know, what kind of backlogs do you have?

How quickly are you clearing it? So, for example, during COVID, we were able to show that because of, we had, our governor declared an emergency, so we had to shut down, and we showed, we were able to use data to quantify the impact of the backlogs, and we got some one-time funding to help reduce some of those backlogs.

So from a funding perspective for public agencies, that's really important, and you can use that for advocacy. And a lot of times you're held accountable for, you have to meet certain metrics. And so having that data, Also helps you tell the statewide story rather than, oh, it's just one particular county, one out of 58.

Jess Carter [00:15:47]:
Yeah. And you just touched on my third topic, which is improved funding advocacy. So to your point, and I've worked in other agencies like, um, workforce development and unemployment too, where they have federal reports for a reason is that some of those reports determine funding for those agencies from the state, from the federal agencies perspectives, but having the right data and having most accurate data allows you to either request for unique additional funding.

Or just to get the right amount of funding in the first place, right? Is there anything else about funding advocacy you want to add?

Darren Dang [00:16:15]:
Yeah. So that was more from the global perspective. Uh, there's also, uh, advocacy from an internal perspective. As I mentioned, we have different areas and different case management systems.

And so one of our, a supervising judge in family law actually used data to show that, hey, I've got a huge backlog. I don't have enough judges. I don't have enough resources compared to other areas. And by having that global data and being able to see court wide that supervising judge was able to get two additional resources, that's probably like a ten percent increase in resources.

And so, data can be used for advocacy for resources, right? Resource allocations. And so, and it levels the playing field. And it gives you, the data doesn't, one of my staff says, data doesn't lie, right? But there are also data quality issues you need to be aware of. Right? At least by looking at the data, it gives you better insight.

And, you know, based on gut, you might be able to identify some data quality issues that you can start doing the data cleanup, right? Versus just flying blind.

Jess Carter [00:17:19]:
Yeah. I mean, I think data quality issues might be like, I use the phrase, um, so forgive me, uh, like the least sexy part of data, like people hate doing data cleanup, they hate looking at data quality, but it is, in my opinion, the most important thing that you can do if you're analyzing data, because it's either gonna be someone else's caveat to your story.

You're gonna tell the story and they're gonna say well, you know you're not counting for these unique exceptions. And if you have the data to say hey, statistically that's actually under 4 percent of the findings and it's statistically irrelevant, it's insignificant, we can move on. You can better your case for anything if you understand the caveats.

Like I always talk about if people aren't familiar with a Pareto chart, it's a really simple chart that just helps to lay out, you know, that normally 80 percent of a problem is identified in the first three or four categories of why it's a problem. And if you can figure out what those are and solve for them, you can usually solve for 80 percent of a problem with three or four solutions.

And then you, you don't worry about the rest because it costs more to figure them out than it does to solve them. You know, to cost your business just to eat the cost. And so I think in some of what I try to understand, too, from a data quality perspective is, you know, don't shy away from it, lean into it as much as it makes sense for your, for your business, for your public, public or private sector.

Does that make sense?

Darren Dang [00:18:39]:
Right. Absolutely. And there's a saying that if you really. If something's really important for you, you start measuring it, right? So now some people might have different agendas or different purposes, objectives. So it's really up to kind of the, and we haven't even talked about governance, but you know, whoever controls the data or whoever has the responsibility to look at things globally.

Whether it's your chief data officer or your executive team or whatever governance level you have, you know, it's up to that team to kind of ferret out, okay, what are the key, the core business questions? And then you can start looking at the key metrics that are the key drivers that are surrounding those, those business challenges.

And, and you gotta start somewhere, right? And when you start looking at it, data quality issues will surface. And then you can be, you can go upstream and, you know, correct it at the source as much as possible.

Jess Carter [00:19:33]:
Absolutely. Man, I love, I love hearing that. I love that phrase. If it's important, um, you'll measure it. Let me ask you this. So you, you guys have done so much that when you look forward to your ten-year anniversary there next week, what's next? Like, what's the next big thing that you're passionate about working on or doubling down or improving? What are you looking at? What's next?

Darren Dang [00:19:55]:
I created sort of a road map when I was private industry.

I was the product line manager. So I have to think about a road map or product line and kind of the life cycle as you go forward. And you kind of shift. You look at three to five years, right? And so, since I have a background in artificial intelligence, AI has always been one of the interesting areas. Way before generative AI, but really at the end of the day, whether it's generative AI or AI, data is the fuel for machine learning and artificial intelligence, right?

So you really need to have that culture, that data-driven, model-driven culture. You need to start focusing on good quality data to be inputs to be fed into, whether it's predictive engine or generative AI. So that the next big area for us, now that we, we’re fairly established in our data practice where we have a governance structure, we have a data culture, we have training programs, and we have a pipeline to really help our, we have 1,500 people in our organization.

So we're starting this data academy and training so that we are increasing data fluency. The next big area is really around AI and ML.

So, it really works hand in hand. We created a strategic innovation team, kind of like an R&D group, to really help fast track some of these projects, proof-of-concepts, and then we're combining that with our data insights. To really help particularly around case delay reduction. So public service, you know, how do you be more efficient and improve that workflow?

Jess Carter [00:21:34]:
Okay. So that just sounds one, extremely cool. Two, when I look back and I think about another court system that maybe wants to follow in your footsteps, and I think about. Where you started and it wasn't, this wasn't just a story about Snowflake. It wasn't just a story about a single source of data.

It's this larger story about how you brought, you know, to your point, people and process along for the ride to make sure that you got the right outcomes. What advice would you give another court system that wants to emulate some of this, or just a, you know, a private sector company that wants to do some of what you just described?

Darren Dang [00:22:10]:
Again, people process technology, right? So those components have to work together. But first and foremost, you need to have an understanding of, you know, some of the problems, what problems are you trying to solve, and then, you know, focusing on the really low-risk, but high-impact problems. So once you have that list of all the problems, and then you can kind of assess Okay, do we have the components in place to solve those problems?

And so, sometimes it may not be a big impact, it might be a smaller problem, but you know, we also think about foundational, you know, I really push for foundational building blocks, right? So, so I knew bringing all the data together is important. And so, when we first started our journey, Our small start was in the area of legal research, our general counsel, and it was around resource allocation and he needed to be able to assign staff to support judges, legal research attorney.

But the important part is he was a very good ambassador. So you start small and you find ambassadors who will really tell that story. And I always joke like, oh yeah, if our general counsel can, can do it, anybody can. So, so you, you, you need these small wins and you need people, you need to build that trust and that, hey, it's not overwhelming that it's doable.

Right. And so, and we also create these small video vignettes, right? So focus on, focus on the problem. that you're trying to solve, make sure that you have the technology, the building blocks to enable that, and on the people side is build that culture, get your ambassadors, get your evangelists to really help you tell that story that, hey, it's really doable, and then work with each of those business units to really help them build out the capability so that you have some something tangible to show, and again, being the product line manager is always having that roadmap, so at least you kind of know where, what your workflow and your capabilities are going to be. 

So having that strategic roadmap and, you know, it can change, right? You can refresh it every three months, every six months, to be honest, the roadmap that we developed six, seven years ago, that included document intelligence, so there's AI machine learning, and we're still sticking to that roadmap.

Yeah. Then there are some little tweaks, but overall, strategically, that roadmap is still there. So that's what I would recommend in a nutshell is think about your business problems. Find your executive sponsors, find your low-risk, high-reward, and cultivate your, your ambassadors and make sure that whatever you're in place, you have in place that you're building upon it incrementally, and you're not just focusing on problems that are very narrow in scope, but that doesn't, that doesn't have the legs to expand.

Jess Carter[00:24:51]:
Yeah, that is phenomenal advice. And something that I really appreciate, too, I might just ask you one more question, if you can spare the time, which is, you obviously came from private sector and were successful there. I think that your leadership and your ability to kind of crosswalk yourself over to public sector, it's neat and it's really interesting. 

And so if you don't mind, my other question was, this isn't going to be, if there's someone else in the private sector who wants to give back, is passionate about jumping over to the public sector, you obviously did do some of that crosswalk of, you know, okay, what's in, you know, in manufacturing, here's my pipeline and in my caseloads or my pipeline over, like what you kind of had to do that for yourself and translate public to private.

What advice would you give someone in their first 90 days as they jump from private to public? I'm just curious what you'd say.

Darren Dang [00:25:43]:
My biggest advice would be to be very patient because sometimes in the public sector, we don't move that fast. We don't always have the best resources, whether it's funding, whether it's technology infrastructure, whether it's staffing, or skill set.

So everything, because I came from a management consultant background, so everything that you would need to approach a problem to solve a problem is the same. It's the pace at which you're able to solve that problem or the resources that you need to go and solve it. The resources that may be required.

So you have to be really agile. Don't lose sight of the problem that you're trying to solve, but the path to get there may not be as direct as it is in private, because in private, if there's a decision, we're going to go solve this problem. We're going to give you all the resources that you need. Or as quickly as possible, right, to solve the problem, because you want to be efficient, you want to fail fast.

And you may not have that luxury in public sector, and it may be circuitous to get there. And so the, and that's why I really emphasize public-private partnership. So we always try to form strategic partnerships with, with our partners. And so, Resultant fortunately was, uh, before that it was Teknion, uh, that was later acquired by Resultant, was a very good strategic partner for us.

That we've had a long relationship where it's a win-win both ways. And so that would be my advice is to be patient. Don't, still focus on the problem. Don't lose sight of the problem. Don't give up, be committed. Be purposeful and keep at it and find the right resources. And sometimes it may take a little while to get those resources, but you can get a lot of help from outside if you can convince your private partners to help you with some aspect of it.

Jess Carter [00:27:45]:
That is inspiring. And it's really, it's, I think it's probably very helpful to people that are listening. I think that your expertise and your leadership skills. It would be very easy to assume that people who have those skills are probably impatient because they've been held to a bar where you have to move quickly all the time.

And it's neat to me to think how do we help other people who step into bringing those skills to the public service and the public entities do so as gracefully as possible so they can be as effective as possible. And I think that's awesome. Thanks for sharing that. 

Before we wrap up, is there anything that we haven't talked about that we should?

Darren Dang [00:28:20]:
I think I've mentioned most of the change management, but it was really interesting, the question that you asked me about people from the private want to make the jump to public, and this is more of a call to action and to really the public sector needs a lot of help. And there's a lot of good that we can make a big difference.

And a lot of times there's a stigma that public sector is not innovative. We don't move fast enough, but there's a lot of room for improvement to really make a difference. And particularly what we're seeing with the younger generation is they really want to give back, right? They really want to do something meaningful and there's a lot of opportunities.

To be had to make a difference, right? And so I would highly encourage anybody interested in anybody I run across who, you know, shows a remote interest. You know, I highly encourage them to really look at public sector. And really, it takes leadership to really do that. You know, sometimes you, you have to bring your ideas and you have to be committed to it, right?

And so, don't take no for an answer. Find ways and there's a lot of difference that you can make by, you know, if you're coming from private. And search out peers who are aligned in that drive to make a difference, to give back, and you can do a lot of good. So again, I hope that more people, particularly from private industry and also you bring in a a different perspective that's really healthy.

Right? That diversity is important. And, you know, to me, a good mix, 50/50 of private/public is a very healthy mix. And we don't have enough of that, you know, if I had to guess, probably 80 public and 20 federal, or much less than that. And so that infusion of new ideas is super critical.

Jess Carter [00:30:13]:
One of my favorite parts of public sector work is you're no longer, like I remember working in private sector before and there's a target audience and it's, you know, a certain age group or certain demographic, something you get into public sector.

And it's like, no, actually we give driver's licenses to anyone who passes a driver's test of any age. And you start to realize that the solutions get actually much more interesting. Because they're solutions for a much more complex group of individuals because it's citizens. And I just think that that gets, I've always chased the biggest problems I can solve in life as my career.

That's something I've just enjoyed. You don't think you get more interesting than some of the public sector problems that we have because they're. They're societal problems. They're problems that can't be solved very quickly or easily. And so if you can make a dent, I mean, what's, what's more meaningful, you know?

So here's Darren Dang and Jess Carter's pitch on why you should join the public sector if you're a data-driven leader. 

Thank you guys for listening. I'm your host Jess Carter. Don't forget to follow Data-Driven Leadership wherever you get your podcasts and rate and review letting us know that these topics are transforming your businesses and what else you'd like to hear about.

We can't wait for you guys to join us on our next episode. Darren, if they want to follow you or listen along, where can our listeners find you?

Darren Dang [00:31:30]:
Probably LinkedIn is the best way to get a hold of me. And I speak at a number of national conferences. So, but LinkedIn is probably the best way.