Show Notes: The Umbrex Business Analytics Diagnostic Guide that is discussed in this episode can be downloaded at no cost here: https://umbrex.com/resources/business-analytics-diagnostic/ In this episode of Unleashed, Will Bachman and Adam Braff discuss the creation of a data analytics diagnostic guide. Adam, a former partner at McKinsey and a consultant on data analytics, discusses the importance of data analytics in solving business problems in any company or investment firm. He explains that a business analytics diagnostic is designed for organizations with multiple people, computers, and analytics processes. The goal of this diagnostic is to determine the performance and alignment of the data science or analytics function with the overall mission of the company. He explains the size and type of company that uses this and who would monitor and manage the data analytics of a company The Diagnostic Guide Format Explained The diagnostic guides follow a format with scorecards for individual pieces of an area, typically 15 to 25 different scorecards, and within each one, objective criteria ranging from nascent to optimized. These guides are divided into categories and subcategories, such as analytics strategy, data management, advanced analytics, AI, talent, decision-making process, tools, and infrastructure. Adam explains the format of the diagnostic guide, beginning with top level categories including analytics strategy, strategic alignment, performance measurement, and future roadmap. Analytic strategy involves understanding the business objectives and problems to be solved, such as growth, customer retention, risk management, and problem-solving.  Strategic alignment also involves determining the location of analytics people, whether centrally located in a Center of Excellence or distributed across different functions.  Performance measurement involves tracking key performance indicators for the analytics function, such as cross-sell, revenue, pricing, and marketing ROI teams. Benchmarking this number against competitors can help determine if the company is on track and if it is underinvesting in analytics. Performance measurement also includes ROI, which is the understanding of specific goals and projects that the analytics team is working on. By tracking these metrics and reporting the total impact analytics has on the business each year, the analytics strategy part can be evaluated. A Roadmap for the Analytics Strategy Adam emphasizes the importance of having analytical people distributed throughout the business and dedicated resources for analytics initiatives. To round out the analytic strategy, it is crucial to have a roadmap of the next eight quarters, such as tackling Net Promoter Score analysis, customer satisfaction drivers, or adopting a new data management tool. This roadmap should include hiring and development strategies, cutting-edge innovation, and research, which can be revisited and changed strategies as needed. This helps ensure the analytics team is effectively working towards achieving their goals. Data Management: Warehousing, Sourcing and Integration Adam goes on to talk about the importance of warehousing, data sourcing and integration involving sourcing data from internal systems or external sources, such as customer satisfaction surveys or third-party surveys. This is crucial for asset managers who need to acquire data for investment analysis and decision-making. Automating data loading processes is also important, as it allows for efficient data flow. Business intelligence is another important aspect of data management, which involves creating interactive dashboards and alerts for all stakeholders. Data quality is a critical aspect of data management, involving conscious decisions on the quality of data. More mature businesses have higher standards for accuracy, timeliness, and completeness of data, with constant profiling and monitoring to ensure data meets these standards. Data governance encompa