Data-Driven Decision-Making: Leveraging Data Science to Inform Decisions and Improve Outcomes
By Emily Saras , CEO and Data Scientist , Knowli
Big Data: What’s Next? Agencies, counties, and municipalities are inundated with big data, especially in the health and human services sector. From navigating complex data-sharing agreements, to harnessing big data, to making sense of emerging trends in times of crisis, leaders are challenged to go beyond gut instincts and leverage data insights as a part of their decision-making process. Enter data-driven decision- making : using metrics and near-real-time data insights to guide strategic decisions, identify areas for continuous quality improvement, and improve outcomes. Data-driven decision-making empowers not only leadership, but entire organizations, in making improvements in quality, efficiency, and timeliness of services and operations. The benefits are clear: engaging experts who provide data-driven decision-support enables more alignment across an organization, increases accountability, and promotes transparency on the issues that matter most. Invest in Expert Data Science Services Data-driven decision support begins with expert data science: the cleansing, analysis, and modeling of big data to produce actionable insights. Before committing to a course of action, leaders engage data
and accessible source of key metrics and performance indicators. Empowered with customized data dashboards, leadership and their staff can isolate key trends and spot anomalies faster, without needing advanced statistical training to understand and take action. Partnerships for Effective Data-Driven Decision Support Rapid-response data science services are crucial for organizations aiming to make informed decisions quickly and effectively. Flexible service models tailored to the unique needs of executive leadership and their programs are essential for successful data implementation. Collaborating with proven industry experts ensures that these services are executed with precision and expertise, leading to better outcomes and more efficient operations.
scientists to support the process. Data scientists use statistical methods, computational science, and AI/ML methods to quantify key decision points, create and code metrics and key performance indicators, and develop descriptive and predictive analytics that isolate the key data needed for decisions and action. Visualizing Data to Develop Key Insights Visual analytics – the process of visualizing key data trends in impactful dashboards – offers an opportunity for all decision-makers to engage with data trends, not just the technical folks. Data dashboards ensure that stakeholders are all equipped to make business decisions using the same information. When a data dashboard is deployed, it serves as a single source of truth for the organization by offering a centralized, trusted,
18 – Florida Technology Magazine – 2024 Fall Edition
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