Managing the “behind-the-scenes” of back-office operational areas, such as consumer loans and transaction processing, bears a strong resemblance to putting on a Broadway show. You have 1) a script (your list of tasks and process maps that tell you what should be happening when); 2) your cast (key knowledge workers and a supporting team of data entry clerks, billing specialists and order processors); and 3) the stage, costumes and sets (the applications and systems that form the infrastructure of your operations).
Even with all of these elements in place, sometimes the show just doesn’t come together as intended, which begs the question: what’s missing? As an operations manager, you are most likely missing some much needed insight into the connections between the various moving parts. Gaining such visibility and perspective, however, requires analytical tools that can help capture and monitor activities on employee desktops, providing managers with a behind-the-scenes view into what drives the overall performance of your operations. These tools are designed to help answer critical questions, such as:
- How are the applications and tools being used?
- How are the tasks being performed?
- What are the qualities and skills that make one person a star and someone else a poor stand-in?
In any given day, an employee may use up to 10 different software applications, such as Outlook for email, a CRM system to research customer data, a core processing system to perform production tasks or Internet Explorer to monitor industry blogs. Questions regarding how much time is spent in these programs – and whether they align with the activities that should be performed – has been a long-standing challenge for managers to answer, not to mention supervise and measure.
Desktop and Process Analytics tools enable managers to view application usage in a timeline format, helping them understand who is using what application, when and for how long. This data can be compared to schedules, helping ensure the application usage matches the activities planned for proper schedule adherence. This data readily identifies idle time and opportunities for scheduling improvements.
Managers can also dig down into more granular detail. For example, many companies use Application Service Providers (ASP) solutions that provide employees with access to the Internet. With a view into individual Internet urls, managers can determine if their staffers are in the right programs or simply catching up with friends on Facebook. Analysis of desktop activity can help banks’ IT departments understand which software programs are mission-critical and which have perhaps outlived their usefulness. For banks, this can translate into measurable savings with the ability to cancel maintenance contracts on outdated technologies.
These tools can not only help identify application usage, but also capture the steps performed within the applications. By recording start and end times of tasks, managers in operational areas can determine average handle times (AHTs). Previously, AHTs were calculated through time-consuming observations and only reflected a sampling of the work performed. With automated activity tracking, managers have a more accurate view of how much work is processed and how long the work should take. This behind-the-scenes data will help managers more precisely develop capacity resource plans.
Next, operations managers must have the ability to tie activities together so that they can identify the steps within different processes. From there, they can analyze the myriad paths taken by employees in processing work to identify bottlenecks and streamline workflows. Managers will often find a great difference between their detailed process maps and the way in which work is actually performed. Similarly, process paths can be compared between employees to identify best practices and reasons behind deviations.
So now, we know what applications are being used, how tasks are being performed and how work flows across our operations through the numerous processes. But, as managers, we also know our systems and processes are only as good as the people who perform the tasks. So, we need tools to enable us to compare performance and work steps between individuals, highlighting star performers and identifying the “extras” that need coaching and additional guidance. Through stellar performance and best practices, the steps performed by your stars can be cataloged and then disseminated to the rest of the cast to further improve overall performance.
By capturing data directly from employee desktops, managers have a back-stage pass to see how work is actually being performed behind-the-scenes. This new insight can help bring together the applications and systems, the tasks performed, as well as processes and resources to improve performance across the entire enterprise.
Mr. Williams is principal consultant, Desktop and Process Analytics, for Melville, N.Y.-based Verint Systems Inc. He can be reached at firstname.lastname@example.org.