Previously, we’ve discussed how to kick start an analytics initiative with Strategy and Discovery, a process where you compare the current state to a desired future state for the purpose of creating an Analytics Roadmap.   

This exercise can illustrate the value in a completed engagement.  But since analytics engagements are long processes of continuous improvement, it’s often important to understand what (and to some degree, when) results and impact to expect along the way.

For this, we can consider three stages of value that occur during a data analytics initiative.

Optimization – This means you’re doing what you already do, only better.  Often this value can be obtained just be using the base features of a product or an early iteration of a custom solution.  In the case of data analytics, solutions offer easier access to current data and rich visualizations.  Value from optimization is primarily at the individual level or within a single department.  For example, associations typically notice, when compared to their previous systems, a new analytics solution is:

  • Faster – saves time compared to manual processes to collect data and create reports.
  • More Accurate – single version of the truth means consistent numbers and metrics. Less handling and summarizing increases accuracy.
  • Visually appealing – new visualizations are more attractive and accessible than tables and spreadsheets.

Process Improvement – When individuals are able to perform tasks faster and more accurately, this optimization can be leveraged to change how you do business.  This means improving processes that may span multiple departments, implementing new processes that were not possible, or retiring processes that are redundant or just don’t make sense anymore.  Process Improvement value spans across functions and business areas in order to increase productivity.  For example;

  • One source of data for analysis – no more pulling data from multiple systems/departments
  • Targeted communications – Membership and marketing messaging and content can be tailored to particular audiences, reducing waste and increasing effectiveness.
  • More personal service to customers and prospects increases engagement
  • Rich customer insight drives decisions on products and services
  • Implicit and explicit behaviors are better understood
  • Financial forecasts and comparisons use current data.

Strategy – this highest level of value occurs when the strategic objectives and the mission of the organization are advanced.  Examples include:

  • Increased dues and non-dues revenue
  • Improved Member satisfaction
  • Increased Membership
  • Finding New Audiences
  • Increased Relevance
  • Higher lifetime value of members

All this from analytics?

Strategic value is the cumulative effect of optimizations, process improvements, and various other factors.  Because of this, it’s naturally the most difficult to achieve or to attribute to a single cause.  Analytics is one important element to drive and measure strategic value.