Analyst Perspectives

Enkata used to focus its products on improving agent performance in the contact center. It has gradually expanded that focus to include improving the performance of workers in the back office, an effort that has culminated in a suite of products that help companies improve processing of healthcare claims.

The process begins by tracking how employees who handle claims use their desktop systems. Enkata’s software is loaded on the desktop and captures key strokes, regardless of whether the user runs an application, starts a search or enters or retrieves data into or from a business application. Managers or analysts can group key strokes and the sequence in which they are used to represent a task; that may include, for example, opening a claim through to closing the claim or looking up customer information. The product can analyze the tasks users carry out, spotting variations in how they complete a task compared to how they are expected to do it, and noting when they do the tasks, any unproductive tasks they do and when they are idle. All of this information is displayed in graphical forms that, for example, show where each user spends time, a timeline that maps how each user spends the day, and timeline maps that show how different users spend their days. The analysis can go into greater depth and display the steps users take within a task to flag, for example, if a user misses a required step.

Armed with this information managers and analysts can pick out patterns and variations from the expected. This type of analytic inquiry is becoming important for many organizations. Our benchmark research shows that analytics is the most important business technology innovation for 39 percent of organizations. Enkata’s claims processing product includes a software scripting tool with which users can develop tracking applications that search for defined patterns or exceptions and display the names of users who exhibit the specified behaviors as they carry out their tasks. The final step in the process is to use this information to identify improvement opportunities and display them graphically on forms that include “click to action” buttons showing how the user needs to improve; for example, they can instruct the user to take a training session, receive coaching or adhere to a best practice. Reviewers can use these charts to set out action plans. Broader analysis across multiple users helps managers and analysts identify process improvements and action plans to ensure that more employees follow best practices.

Enkata has always positioned itself in the performance management space, and this product fits there. The end-to-end process of capturing data, analyzing it and creating action plans closes the claims processing loop and enables manages to enforce best practices. Over time the analysis can help companies improve the overall process by informally following Six Sigma procedures: set targets, measure performance against target, identify reasons for not meeting targets and put in place improvement programs to get future performance on target.

The product runs in the cloud and can be run in isolation or integrated with business process management applications; in that case it can input information on activities (processes) completed (including by who and when) and provide granular analysis of tasks within a process or steps within a task. Although Enkata’s first release is focused on claims processing, the concepts behind it apply equally to other processes so I expect to see other packages from the company.

In a tough economy, companies not only have to operate as efficiently as possible but also need to identify the consequences of processes or employee actions, such as the long-term cost of an employee settling a claim incorrectly. Companies also need to know what remote employees are doing and the outcomes of their actions. The analysis produced by Enkata’s software enables companies to do both. I recommend that those involved in processing claims evaluate it as they look to optimize processes and employee performance.

Regards,

Richard J. Snow

VP & Research Director