Data is the lifeblood of a business in the information age. Organizations must embrace and institutionalize data as an asset and make it a part of their culture where everyone leverages data to build actionable intelligence for decision-support. Becoming a data and analytics driven organization requires a fundamental shift, almost a cult-like revolution across the organization, where data and analytics is everyone’s responsibility and key drivers of decision-making within an organization. This is particularly important for product and engineering organizations as data analytics can offer insights into customer preference, allowing for personalization and help identify engineering challenges and growth opportunities. The following key building blocks and guidelines can help you implement a data-driven culture within your organization.
1. Data Capture
Enterprise data warehouses designed for capturing structured data from a web application have been the main source of analytics and reporting, as most people within the organization pose bulk of their queries against these systems using SQL. Capturing the data exhaust generated by the users of the web application can provide even more valuable insight into user behavior, preferences and the application itself. An engineering organization must make a conscious decision to permeate this requirement into its culture such that every engineer understands the importance of the data they are logging and the valuable information that can be derived from it.
2. Data Access
Data warehouses with structured data are well protected with tight security and access controls in place to ensure that users see only what they are authorized to. These controls become even more important and challenging, when working with semi-structured and unstructured data. Addressing this requires a process and a platform for publishing the data sets or a subset of the data set to the users.
3. Data Visualization
Data visualization is integral to making complex and large data sets intelligible and intuitive with interactive visualization techniques. One of the highlights of Benefitfocus One Place 2015 was the announcement of Core & Advanced Analytics that provides a data experience with visualization, allowing our customers to tap into vital data points to formulate strategies for cost control and healthcare cost transparency.
4. Benchmarks & Metrics
Data-driven decision-making requires benchmarks and metrics that can help quantify relative performance and evaluate progress. It is important to start with a clear definition of key program-wide metrics and the data sets for these metrics are made available in a structured data store, hence providing the team with data to support decision-making. Getting started with these initiatives may seem like a daunting task, but once the ball is rolling and the team starts using data for decision-making, their appetite for data will snowball and the data culture will flourish organically.