Software developers take advantage of product usage information to enhance performance and make quick software changes to maximize utilization. These capabilities aren’t limited to just software developers, though. Users of the software can also gain valuable insights from this information. From understanding which features aren’t being used to which days of the week people are most active, there is much to learn from usage statistics.
Perhaps the most important factor many organizations consider while purchasing enterprise software solutions is Return on Investment (ROI). However, this calculation assumes that the new software solution will be utilized by all users to the fullest capability. If modules aren’t fully adopted or users are slower to get up to speed, the predicted ROI might never be realized.
Having access to product utilization statistics allows administrators to identify weak points in their department's use of the software. When an organization implements a new feature or changes its methodology, it should be monitoring usage to determine if the rollout was successful. Each methodological change or new feature will vary in complexity, but adoption can be expected to follow the same pattern. There’s an initial uptick in usage, then a gradual rise until adoption reaches 100%.
A secondary benefit of analyzing usage data is understanding the behavior of your department. Usage analytics can identify behavior trends such as a surprising amount of work being done on Sundays or a spike in work before quarter-end. These insights can unlock hidden efficiencies and help management understand its user's work habits. For example, if users spend the most amount of time in the solution on Wednesday or around 2 PM every day, then meetings can be blocked for those time periods to minimize distractions.
Organizations are constantly assessing their business environment to understand which trends are working and which product ideas are falling behind. Why should your software be any different? Maximize your ROI by assessing user behavior and feature adoption to make system adjustments and provide additional training where needed.
