As a national nonprofit organization, CareQuest Institute is in the business of improving lives by creating a more accessible, equitable, and integrated oral health system across the U.S., especially for those from marginalized and underserved communities.To be successful in their mission, CareQuest needs to use their data in an informed and impactful way for grantmaking, research, health improvement programs, policy and advocacy, as well as education. It’s a tall order, but one that is achievable with a successful data strategy.CareQuest already had an idea of certain areas that were limiting the value and support that their data was providing the business. They realized there was more power and insight in their data that they could—and should—be leveraging to better serve their customers and the community.The first step to unleashing the power of their data was to start with a strategic data assessment to better understand what needed attention, where to prioritize, and how to best build out a data strategy roadmap to support their mission.Starting with a Strategic Data Assessment to Identify Gaps and Plan Improvements For CareQuest to expand their services to help even more communities, they needed to understand:What was required—time and cost—to become technology independent from their affiliate company, DentaQuest.How a new data architecture would impact both internal and external initiatives.What to put in place—people and processes—to support their growing organization and its mission.Why is a strategic data assessment important? “It’s a way to identify the best path to provide business value. We have conversations with all stakeholders–business team, data team, IT, etc.—to understand their pain points, thread the needle through those challenges, and provide solutions that will enable them to do their job better using data.” – Rebecca Zeni, Data and Analytics ConsultantCareQuest engaged Analytics8 to perform a strategic data assessment. Through the process, we interviewed 24 stakeholders across the organization, evaluated their existing landscape, and reviewed data documentation to capture their current state and challenges to achieving their goals.We asked questions such as:How are you currently moving data? Are there immediate concerns with this process?What is being utilized as an operational/analytical tool? How do you want to use this?How are manual processes creating bottlenecks?What needs to be moved from DentaQuest to CareQuest, and why?Get started with your own data strategy assessmentBuilding a Roadmap that Addresses Key Elements of a Data StrategyBased on those initial conversations and evaluations, we identified key areas of focus CareQuest needed to address in order to meet their goals, including aligning data strategy with business strategy, data and analytics maturity, architecture and technology, data analytics team, data governance, and culture change. Alignment with Business StrategyPositioning CareQuest’s data strategy and the activities within to directly support their mission of achieving better health for all helped in several ways. The early access to stakeholder insights earned us executive support, buy-in across the organization, and momentum for the project. It also allowed us to:Prioritize the data and analytics initiativesUnderstand business user objectives and technology needs to get their jobs doneMake informed decisions about data organization, architecture, and modelingIdentify opportunities for low-hanging fruit that would provide immediate value and a basis for future iterationsWhy is alignment with the business strategy the single most important part of building a data strategy? “A common quote that we hear from companies is that they have lots of data but no insights. This is an indicator of misalignment between business strategy and data strategy. The biggest risk to any data or analytics project is that it is not aligned to the business objectives or business needs.” – Christina Salmi, Managing Director of Data StrategyAnalytics and Data Maturity EvaluationAlthough CareQuest exhibited characteristics within different analytics and data maturity levels, they were somewhere between ‘Reactive’ and ‘Defined’. As we worked through the data strategy assessment, we identified key areas for improvement to move to the next level of maturity, including:Building the infrastructure and team to provide and promote data democratizationAdding additional staffing positions to support growthMigration to the cloud and leveraging modern technologiesRemoving technological dependency from DentaQuestDeveloping tech stack to house a single source of truth with both a data lake and data warehouseWe use the Analytics8 Maturity Model to define where our clients are today and what it would take to move them forward on the scale.Data Architecture and TechnologyTo support their business objectives, we needed to design a future-proof, scalable solution for CareQuest—one that considered:The need for independent data management and securityDifferent types of users—data analysts, data engineers, BI developers, etc.—and the unique data needs of eachAutomating data integration from disparate data sources and creating a single source of truthPromoting data democratizationWe made recommendations specific to CareQuest’s current and future needs and suggested implementing a modern cloud technology and architecture that would support the range of their data management needs and planned growth in research and analysis, as well as support data ingestion for organizational initiatives.The right-fit data architecture for CareQuest was Azure Data Lake as a persistent staging layer and for ad hoc data science and analysis requests, and a data warehouse in Snowflake for curated and modeled data, as well to support self-service analytics.The Data Analytics TeamTo support new processes as well as a new data architecture, we assessed the existing data analytics team’s skillset. Some of the challenges we heard included:Too many informal requests of data analysts and data engineers; not able to effectively prioritizeSome data requests are asked for more than onceThe team is stretched thinCleaning data when it is needed rather than when it comes inLack of collaboration organization wideAs we built the data strategy roadmap, we included recommendations for:Training and user enablement for new technology and self-serve analytics for everyone, not just the data analysts and engineersData literacy for internal and external users, as well as the need for a data catalog, so that everyone in the organization understands what data is available and what it meansTeam roles and structure, especially as the company grows, to support data-driven decision making across the businessData GovernanceThroughout the assessment, we worked with an existing data governance committee at CareQuest to better understand the challenges, which included:Data was not always conformed and there were multiple definitions for the same terms throughout the organizationThere was a need for compliance with HIPAA and HI-TECH before they could be technologically independentIt was unclear what data was available, or what metrics might be contained in a reportThere wasn’t any standard documentation, and files were difficult to findData governance should be practical, maintainable, and proportional so that it leads to high quality data.After evaluating their current state, we suggested key areas to get started with including:Identifying governance standards and processes that were previously handled by DentaQuest and would now need to be adopted by CareQuestBuilding a data catalog to address concerns over data literacy and improve data transparencyCulture Change and AdoptionWith any change comes the need to ensure everyone involved understands what is happening, and how they play in a role in making it happen. Throughout the entire process, from assessment to designing their data strategy roadmap, CareQuest communicated intentions and progress to everyone in the organization and this was key to their success.Stakeholders in each department were accessible and played an active role throughout the process, making it easier to design a data strategy with user adoption in mind, cater to the needs of the business and prioritize data projects that were immediately valuable to the business, and build momentum around culture change across the organization. Business users began to perceive the possibilities of data differently and were prepared—and excited—for the upcoming changes. Culminating the Data Strategy Initiatives into a Roadmap We built a data strategy roadmap for CareQuest that included a backlog of 45 prioritized use cases—homing in on the low hanging fruit and urgent priorities such as technology independence, while also building a solid foundation to make progress toward—and prioritize—any new goals.How do you work through prioritizing use cases when building out a data strategy roadmap? “We use a business prioritization matrix based on technical feasibility and business value derived from the conversations we have with stakeholders. It’s important to keep in mind, that things can change along the way. CareQuest was a fantastic client to work with because not only were they active in giving us feedback on the use case prioritization, but they went the extra step and weighted different values for different things. The communicated any changes early and often.” – Rebecca ZeniGet started with developing your data strategy roadmapA data strategy roadmap helps you prioritize your use cases, as well as any design, build, training, or re-engineering of a business process. The data strategy roadmap had multiple phases with associated time, costs, and necessary resources for:Modern cloud technology and a new architecture stackA plan to migrate and ingest data sourcesStaffing and training recommendationsData governance programConsolidation to one analytics platformA plan to prioritize use cases with quick wins and foundational projectsData Strategy Leads to Impactful Changes for CareQuest Planning, communication, and executive buy-in and support all contributed to CareQuest’s success and quick progress in increasing analytic maturity. With renewed trust in and accessibility to the data, CareQuest is seeing progress toward their organizational goals.Improved analytical capabilities to enhance and expand service offeringsCareQuest can rely on analytics to monitor and uncover correlations and indicators of medical and dental health for the communities they serve. They are also able to see gaps in oral health access and care for specific populations, such as veterans. This information helps them identify where and how they can improve their offerings.Improved data democratization and self-serviceCareQuest implemented a self-service dashboard that provides analytics to business users, who in turn share insights with the public for advocacy and educational purposes—further promoting CareQuest’s mission.Established data governance practicesThe development of a business glossary template and data catalog, along with updated security practices improved the role of data governance. Additionally, CareQuest’s external partners can feel confident with the robust security, confidentiality, and integrity of the data and analytics environment, creating more opportunities to collaborate with data and gain powerful insights which will improve people’s lives.