Measure the metrics that matter
with adoption data

If you have ever had any doubt about the value of measuring enterprise software performance, this quote from H. James Harrington should end it. After a lifetime spent optimizing organizational performance, with 40 years at IBM and 10 spent as a principal at Ernst & Young, his message couldn’t be clearer.

“Measurement is the first step that leads to control and eventually to improvement. If you can’t measure something, you can’t understand it. If you can’t understand it, you can’t control it. If you can’t control it, you can’t improve it.”

However, measurement is only as valuable as what’s being measured. And for digital transformation and service delivery linked to enterprise software, there is often a gap between the expected business outcomes and the reality.

This gap all-too-often consists of how users use technology, and it can be bridged by adoption data. This unique user experience information can highlight successes, areas for improvement and areas of opportunity. It can link usage to usefulness, and convert data inputs to business outcomes. And while information alone won’t drive improvement, as Harrington says, establishing the correct measures and the metrics that matter is the first step on this journey.

How to access and apply adoption data

In simple terms, adoption data is information on users’ interactions within software applications. From logins to navigation, time spent in application and task completions, adoption data tells you which (anonymized) users have done what within software, how long it has taken and what the outcome was.

An example of this would be how many users accessed their profile section on their first use of a new application. Another would be how long it takes a particular user group to achieve a specific task, or the completion rate of users of key processes. Further still, adoption data makes it possible to see the positive and negative influences on successful task completions—such as role, location or prior engagement.

This kind of intelligence is often a blind spot for businesses. To access and apply adoption data to demonstrate the true value of software investments, you’ll need a digital adoption platform that tracks this information and makes it digestible via analytics.

Without this information, the success of software is often judged on either the top-level usage figures that are available from the software vendor, or qualitative feedback. However, real value doesn’t come in the form of number of monthly logins or positive opinions. Software investments are made to deliver time and cost savings, not for the functionality. Adoption data enables businesses to measure the outcomes of their software, not just the inputs.

Once integrated with other data sources, such as support tickets and call tracking, these user experience insights make it possible to report back on the goals and objectives raised in the original business case—demonstrating application performance, as well as ways it can be continually improved further.

For a real example of how this works, we can look at one of our customer success stories. Prudential, the global insurance and finance leader, contacted AppLearn when they realized they needed support with their employee service experience transformation.

Using AppLearn’s expertise, our Adopt platform and the approach outlined above, Prudential were able to identify high volume, high risk processes where users would benefit from tier zero support – and then insert necessary interventions to see the impact of their actions.

An example of adoption data in action

The first step for Prudential was combining the unique adoption data made accessible by Adopt with platform and call tracking data. Once we’d done this, with their ServiceNow front-end portal and Workday® implementation, we created measurable objectives closely linked to their target operating model.

With these goals and our Advanced Analytics in place for launch, as well as the previously inaccessible in-app interactions being tracked by Adopt, Prudential were able to find out how their technology was enabling their vision and operating model at a glance.

Our day one results showed that 95% of people used Adopt on their first session, with 61% actively seeking support in-app. But as mentioned previously, adoption data goes deeper. We could also see that the users who engaged with our targeted enablement content were 150% more likely to successfully complete day one tasks.

This level of performance wouldn’t be possible without the work done to measure and boost readiness for change before launch. However, this insight not only proved the value of the pre-go live work, but identified other areas where the same approach could be applied.

As a result, the performance and level of insights continued to improve in the months that followed. We were able to demonstrate that Adopt interactions not only improved general task completion rates by more than 200%, but drove a 50% time saving on core tasks within 21 days. In fact, for the high volume ‘Request Time Off’ task alone, we saved 3466 hours over this period by reducing average completion time to just 4 minutes.

This kind of data is crucial to evidencing and optimizing the success of a software investment. It means Prudential can not only demonstrate the adoption and business value of their new applications, but access insights to support ongoing demands.

For more information on Prudential’s objectives and how we enabled them with adoption data and in-app support, read our success story.


 

With adoption data, organizations have the opportunity to fill a critical measurement gap and get to the metrics that matter. Whether for internal software or a tool delivered to customers, this is vital to both proving and improving performance.