The Evolution of Analytics: Our process moves through 6 stages that take us from data to direction.
Gain control of your data to improve its accuracy and business value. Set up the foundations of your data structure to improve the strategic value of your data at the beginning. It’s essential to understand how all of the information flows together before you start reporting on data. Building the infrastructure at the beginning ensures optimal data quality and performance into the future.
This is the stage most companies are at in the analytics evolution journey. Used to help identify key metrics and KPIs for business health, reporting focuses on compiling information and showing what happened.
Measure your performance against goals and objectives more clearly. After key KPIs are identified, most companies set up a dashboard with health indicators and fail to realize any further value from their investment. While this is useful information in the short term and to identify trends over time, these dashboards often get confusing and show every available metric without showing the truly valuable information - so you can’t see the real root of issues.
Answering Business, Audience, Channel & Message Questions. Conveying the “why” and “so what” of data. Analytics digs deep into the data to interpret what is going on with your customer to answer questions around improving the business. Critical analytics requires a deep understanding of the business and the industry in which the analyst is working.
Problem Solving through data transformation & automation. Predict and set baselines for projects.
Opportunity detection through advanced analytics and machine learning.
