While digital transformation has been on the minds of state and local government leaders for years, COVID-19 changed modernization from a long-term goal to an immediate need. Constituents across the nation are relying on local governments more than ever before, which means the demand for digital services has dramatically increased.
Simultaneously, legacy technology that was tolerable for traditional work environments is sapping the productivity of remote workers. Leaders within state and local governments understand that they need to invest in better customer experiences for their constituents and employees, but they are also facing a budget shortfall of $300 billion through the fiscal year 2022.
This is where data analytics comes in. State and local agencies can use enterprise-wide data analytics to gain insight into their constituents' wants and needs, measure the impact of policies and programs, improve employee productivity, and prevent waste and abuse. Moreover, doing so pays off – government transformation efforts that use data analytics are twice as likely to succeed as those that do not.
Best Practices for Driving Long-Term Success with State & Local Data Analytics
Data is a powerful tool that agencies can use to bring themselves closer to citizens in more efficient and effective ways. However, that can only be accomplished if agencies truly embrace an enterprise analytics culture. Anything less than this and data analytics efforts are likely to fall by the wayside, costing time and money without realizing any true gains.
Keeping this from happening requires taking steps that go well beyond considering or testing data analytics practices in localized parts of the organization. It requires a broad and committed effort that, once started, must be continually improved and iterated upon to produce the best possible results.
The City of Boston provides an example of what can happen when departments and agencies invest in analytics. The City hired Qlarion to build a data sharing and visualization platform called Snow Cop. that allows city managers to monitor 850 miles of roads and 750 ice and snow removal vehicles charged with clearing them. The tool permits public works managers to pinpoint the location of citizen calls for service and easily direct trucks to those locations from a centralized platform.
Best Practice #1: Understand Your Starting Point
Begin by determining your organization's current analytical maturity through an Analytics Maturity Assessment, a comprehensive evaluation that scores the initial maturity stage in four dimensions: data, technology, processes, and organization. We evaluate the gaps between the current and future state, then build a roadmap that plots out the best path to analytics maturity. The roadmap takes into consideration the value, timing, level of effort, resource availability, skills, constraints, organizational priorities, and interdependencies.
Best Practice #2: Foster Trust Among Stakeholders
Trust is fundamental to success in data analytics. Data owners must trust security and data governance policies, business users must trust that the data aligns with their business goals, and constituents and government workers alike must trust that the data is accurate.
A Data Trust is the first step in establishing trust in data analytics programs. It eliminates both the legal and cultural roadblocks to cross-agency data sharing and delivers peace of mind to data owners. Likewise, a formal data governance framework codifies measures for monitoring how data is managed and how regulatory compliance requirements are met.
Over the past several years, Qlarion has partnered with the Commonwealth of Virginia to build the FAACT platform, a critical component of the state's response to the opioid epidemic. When COVID-19 hit, it was clear that FAACT could help the Commonwealth respond to this crisis as well. The data-sharing platform, data trust, and data governance provided the scalability and flexibility required to frictionlessly include COVID-19 data sources, allowing leaders across Virginia agencies to securely share data and track key metrics, including case numbers, PPE inventory, and vaccine distribution.
Best Practice #3: Build for Change
Creating an enterprise architecture that is flexible and designed for a change instead of merely capable of change will reduce risk and decrease time to value. Investing in a secure cloud, automation, and modern data center operations can also dramatically reduce costs.
Best Practice #4: Focus on Incremental Improvement
To ensure the long-term success of your analytics program, it's imperative to show results as soon as possible — we call this the Quick Win. A Quick Win will build confidence for the analytics program within your organization and ultimately drive user adoption.
Start by finding a high-value use case. These questions can help identify the right use case for a quick win:
- Do multiple stakeholders see the use case as tedious, inefficient, or generally difficult?
- Will it have an immediate impact?
- Can we produce results quickly?
- Is there a champion to support it?
For more information about driving change through analytics, check out our Imagine™ Innovation Framework white paper.
Qlarion is a government innovation firm that provides data and analytics solutions for federal, state, and local government agencies. We work with our clients to identify, design, and implement data and analytics solutions that create a lasting impact for our clients and the communities they serve.
Our expertise includes:
- Enterprise Data Management: Through our proven approach to business intelligence and data analytics, we create programs that can be rapidly built, tested, and scaled.
- Business Intelligence & Analytics: Through our proven approach to business intelligence and data analytics, we create programs that can be rapidly built, tested, and scaled.
- Cross-Agency Data Sharing: We develop secure, cloud-based, highly scalable data-sharing platforms that transform the way government agencies operate.