A productive workforce can lead to time savings, better customer retention and, ultimately, higher profits. However, trying to achieve productivity isn’t always easy—there has been a long trend of declining productivity growth in the U.S. Many businesses are using a myriad of techniques to encourage a more productive workforce, from providing flexible working hours to offering different working spaces to implementing the latest productivity-boosting technology tools.
In the past, analytics has been noted for its benefits to worker efficiency. No longer do employees have to wade through mountains of data manually. Instead, nearly everyone has data insights at their fingertips with the push of a few buttons. However, the traditional analytics process—which forces users to leave the applications they’re already using and go to an entirely different system to analyze their data—is hardly the most efficient process for an organization, and certainly has its own negative impact on productivity levels.
Over the last five years, we’ve notice a recurring trend in businesses around the world. IT departments have favored standalone self-service analytics tools to improve the capabilities of different business teams. However, evidence shows these analytics tools are being rejected by users. The 2017 State of Analytics Adoption Report has shown that only 21% of users who have access to these tools actually use them.
But why is adoption so low? End users want analytics to make their jobs more efficient. But they rarely adopt standalone tools because they’re difficult to use. Instead, they want easy access to analytics as part of their daily workflows.
With these thoughts in mind, it’s not surprising that standalone analytics tools aren’t just a source of frustration—they’re a waste of time. Anyone who has ever had to flick between their data source and a different analytics application knows this well. Nucleus Research estimates that this swivel-chair effect wastes up to two hours of productivity per worker each week, something most businesses can’t afford.
Users are already calling for more efficient analytics tools. In fact, 84 percent of business users want access to analytics within the applications they use. Thankfully, application teams and product managers are listening to this demand. The 2017 State of Embedded Analytics Report found that adoption of embedded analytics is on the rise. Usage has consistently grown since 2013, which is no surprise considering embedded analytics gives people the analytics intelligence they want inside the applications they use every day.
Embedded analytics also now has an adoption rate that’s three times that of standalone self-service tools. It helps increase the stickiness of applications, too: 84% of application teams stated that time spent in their applications increased after embedding analytics.
By encouraging users to spend more time in these applications, companies are placing more value on the experiences their products deliver and improving user satisfaction. This is critical if you want to improve productivity levels, as it’s well known that individuals are more likely to be productive if they enjoy using the tools they have been given.
Embedding analytics can also boost productivity beyond your end users. By giving users access to self-service tools embedded within applications, IT departments are able to decrease the ad hoc requests they receive from users for analytics support. More than 64% of companies that embed self-service capabilities saw a decline in ad hoc requests from users, according to the 2017 State of Embedded Analytics Report. This in turn frees up IT teams to focus more on business-critical tasks—a win all around for the many businesses trying to balance productivity across the board.
The 2017 State of Embedded Analytics Report surveyed 500 people, including members of product management, product development, software engineering, IT, and executives from Independent Software Vendors (ISVs) and Software as a Service (SaaS) providers.
Josh Martin is the Product Marketing Manager at Logi Analytics. Prior to joining Logi he was an industry analyst covering bleeding edge distribution channels and their impact on the consumer market. In this role he was a thought leader and advised clients on how to successfully benefit from market shifts while positioning products and services for long-term success. Josh holds a Bachelor’s degree in Business from Babson College.
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