Oct 22 2020

California Unveils Strategy to Help Navigate Data Landscape

The Golden State’s data strategy focuses on streamlining data access, improving data management and governance, and spurring data use and skills.

California’s open data portal contains a multitude of data sets, including COVID-19 hospital data, sea level rise maps and areas in the state deemed suitable for affordable housing development. Now, the Golden State has a strategy to govern all of the data it collects.

On Oct. 1, California published its statewide data strategy to help evaluate the effectiveness of state programs. California Chief Data Officer Joy Bonaguro sees the plan as a way to connect the state’s various data collection efforts — and to see what is and isn’t working.

“A well-written strategy serves not only as glue and alignment but also as a filter,” she writes in a Medium post explaining her decision to craft the strategy. “If a project isn’t well-aligned with the strategy, you know to avoid or minimize it.”

In a separate message announcing the strategy, she notes that governments are tasked with managing enormously complex problems, including education, balancing public safety with social justice and providing services to vulnerable citizens.

“This means that we cannot afford to guess how well our services are working,” Bonaguro writes in the announcement. “The lives of Californians depend on us knowing what works and what doesn’t. Good use of data is the tool we can use to navigate that complexity and ensure that our programs and services are working well for all Californians.”

What’s in California’s Data Strategy?

The strategy has three main goals:

  • Streamlining data access
  • Improving data management and governance
  • Spurring data use and ability

“California’s statewide data strategy is structured around the analogy that in order to successfully navigate the ‘data landscape’ we need to intentionally build the roads, craft the rules of the road, and boost the drivers,” Bonaguro writes. “Much like in the real world, we want to avoid data roads that lead to nowhere, are poorly maintained, or confuse our drivers. Our virtual data world requires the planning and care that we put into the roads and bridges of the real world.”

In terms of building the data roads and streamlining access to data, the strategy focuses on longitudinal data sets to measure people and programs over time, as well as objective to assess statewide open data efforts and develop a plan to strengthen them.

On the data management and governance front, the strategy calls for an approach that prioritizes and supports “the identification, documentation, development, and distribution of authoritative” data sets. The state will also put in place a statewide interagency data exchange agreement and create or change playbooks for ethical data governance and management throughout the data lifecycle.

To spur the use of data, the state will look at the need for data skill development and existing training programs to develop a statewide approach for data skills. California will explore pilot projects to showcase the power of data science and analytics. The state also will work to create formal and informal data communities across the state and set up a working group to develop recommendations to help it accelerate its use of evidence in all of its practices.

“As change agents, we should exemplify transparency and accountability in our work. In the data world, we encourage ongoing measurement and evaluation,” Bonaguro writes. “A public, declared strategy is about modeling how we plan to measure and be held accountable for our work. It’s saying I’m taking a stand: here’s what I’m committing to. With the California strategy, I’m now on the hook for doing what I said I was going to do or explaining why I didn’t get there and what I learned.”

EXPLORE: How has the pandemic opened up opportunities for cloud-based data collection and analysis?

The Role of Tech in a Data Strategy

In the strategy, Bonaguro says that there is confusion about the roles and responsibilities of data management and use, and in particular a division over whether the business or technology staff should drive data work.

Business, she notes, can encompass everything from operations management to policy and planning and program management. To help clarify, she uses the analogy of a “data gym.”

The business staff are those who want to get in shape and meet their fitness goals with respect to the use of data, how quickly they want to achieve their goals, when they want to work out and where they want to focus.

Data teams are the trainers in this scenario, she explains. “They help you understand how to use the equipment to best meet your goals. They identify opportunities to optimize and advise on how to best target problem spots.”

Technology provides the gym and equipment, Bonaguro notes. “They can house the data infrastructure and build and maintain it in response to the demand and requirements from the trainers and customers as well as their knowledge and expertise in managing gyms.”

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