The Paradox of Training for Cloud Applications

The Paradox of Training for Cloud Applications
When the shift to cloud went mainstream, seemingly every application began promising ease of use and accessibility for users at all skill levels with no training needed. Gone were the clunky enterprise applications of yore, which usually required extensive training to administer, maintain, and occasionally navigate unfriendly interfaces.

When the shift to cloud went mainstream, seemingly every application began promising ease of use and accessibility for users at all skill levels with no training needed.  Gone were the clunky enterprise applications of yore, which usually required extensive training to administer, maintain, and occasionally navigate unfriendly interfaces.

What the old-school apps lacked in surface-level polish, though, they made up for in functionality of features.  After all, ease of use was not always the end goal for these programs— analytic performance was.  Traditionally, each application came stacked with maintenance, administrators, and user training to ensure that, across an organization, there existed deep and consistent understanding of its nuances and capabilities.

The promise that anyone could use the new generation of cloud applications all but eliminated the thorough training that accompanied widespread use of the app throughout every licensed organization.  Getting rid of training would seem valuable to a user, after all, because less downtime learning how to generate reports and more time actually generating reports sounds like a win-win.  But we’ve found that, counterintuitively, the absence of training ends up limiting the users’ likelihood to leverage the tool’s full capabilities. They become comfortable only with the aspects of the tools they need for day-to-day operations.  This means that a business user might skip out on exploratory analysis altogether because they aren’t sure which numbers to crunch and were never trained in the strategy required to make complete use of the application, for example.  It’s easier to stick with elementary reporting, anyway.

This paradox can be summed up by understanding that, previously, users were trained on how to use the analytic tool, and now, they need to be trained on why to use the analytic tool. 

Perhaps doing away with training altogether is not the best way to adopt new applications, even if they are much easier to use than their forefathers.  Instead, organizations should incorporate training that promotes consistency of use across the enterprise and encourages creativity when answering questions using an analytic tool.  This will provide for stronger analytics and cross-functional reporting by minimizing the data quality issues associated with scattered metrics.

As applications become increasingly intuitive and technologically advanced, we anticipate that training will continue to fall by the wayside as organizations push for less time learning and more time doing.  If this trend persists, users will become less and less likely to seek out training, even though forgoing training means the tool is not used completely enough to yield the highest possible ROI for the product.  With this in mind, we encourage IT leaders and data analysts alike to remain open to training as a critical step in the application adoption process, even though the definition of training is changing, a step that readies the user to perform analysis that far exceeds the depth and quality they previously thought possible.


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