The quarterly publication of the International Legal Technology Association
Issue link: https://epubs.iltanet.org/i/116777
best practices are optimal for a user base of 10 to 100 and can span several departments, but this tier of solution may require a stand-alone database to support larger amounts of data. Many third-party solutions can connect to data sources in real-time, so a standalone database may not be required. This means the tools can "latch on" to existing data sources. Reports for medium solutions can be deployed to users over the Web and leverage features of third-party solutions, such as data visualizations (graphs, charts and maps), interactive functions and ad hoc querying. A medium solution is optimal for data volumes of at least 10 gigabytes, limited budgets and smaller user bases. An in-house analytics solution is a cross-functional, multipurpose platform for understanding data. Enterprise solutions handle big data volumes while supporting all the reporting features available with smaller solutions. Enterprise solutions typically require additional infrastructure and IT resources for development, implementation and maintenance, which lead to an increase in cost. These solutions, however, connect to a variety of data sources, feature out-of-the-box and custom reporting, and are more scalable to the organization's data requirements. Enterprise solutions are provided by major enterprise resource planning (ERP) vendors, are highly customizable and can support large amounts of structured and unstructured data. These are the most expensive solutions from an infrastructure, implementation and maintenance perspective. On the other hand, they can be the single source for accessing key organizational governance, financial and operational data from numerous systems. When considering an enterprise solution, note that they strain existing data management systems and infrastructure, which can lead to performance issues if other users or applications access those resources. Enterprise solutions are optimal for plans aimed at aggregating and analyzing large amounts of data from multiple systems. When evaluating vendors, it is important to take a few things into account: requirements. For example, if real-time, Web-based access to data and reports is a critical business requirement, ensure the solution supports that feature. Along those same lines, there is no need to select a solution designed to support big data when your plan does not require it. • Complexity: Determine whether the solution will be so complex that it requires a third party to develop new reports or perform administrative and maintenance functions, or whether it can be supported by in-house resources. • Costs: Evaluate both variable and fixed costs, including the annual and one-time costs of licenses, implementation and training. Throughout the vendor management process, it is important to provide your organization's data requirements and data structure in order to receive the correct product and services. Communication is necessary throughout the relationship to ensure all required features can be implemented within the budget. The Right Tier for the Requirements An in-house data analytics solution can yield valuable insights into an organization's performance, but implementing the correct solution requires careful planning. Assessing critical requirements is the first step in determining what type of solution should be selected. A careful plan should be developed and followed in order to address every requirement with key stakeholders. Many types of solutions exist, but identifying the correct solution is made possible by matching your requirements to the right solution tier. By following this process, the task of selecting the correct solution is made less daunting and much simpler — and with fewer unwanted surprises — for everyone involved. Joe Sremack is a Senior Director in FTI's financial and enterprise data analytics group of the forensic and litigation consulting practice. Joe provides clients with data analytics solution consulting, customized reporting and data analysis services. He can be contacted at joe. sremack@fticonsulting.com Joe Knight is a Director in FTI's financial and enterprise data analytics group of the forensic and litigation consulting practice. Joe provides technical consulting services in the areas of • Key Requirements: For each vendor's solution, perform a comparison that includes key features, security options, methods for deploying reports, data capacity and 12 Peer to Peer complex data analytics and implementation of business intelligence and reporting solutions. He can be contacted at joe.knight@fticonsulting.com.