In the U.S., an employee’s workday is riddled with routine inefficiencies, such as drafting unnecessary internal emails, toggling between 30 or more applications per day, and manually copying/pasting information between programs. When you expand this over months and years, these routine efficiencies turn into costly lost time, approximately more than $100 billion per year.
More importantly, these avoidable tasks take time away from better serving existing and potential customers. This not only contributes to customer unhappiness, but frustrates the employees as well. These inefficiencies are ultimately sabotaging an employee’s ability to maximize customer lifetime value and increase revenue.
Workforce analytics can help businesses get a better handle on these hidden process issues. These tools can help them identify, mitigate, and eventually resolve the roots of the inefficiencies in their systems. Which applications are enabling productivity? Which ones are causing operations to stagnate? Are there processes that are overloading staff with redundant or unnecessary work?
Workforce analysis reveals problems
Companies measure outputs in several ways, from customer satisfaction ratings to tracking profit margins. Yet when it comes to internal processes, most businesses are flying blind. Businesses cannot fix problems without the data that tells them a problem even exists. Their attempts to do this without this data unsurprisingly and often fail.
Organizations should start by understanding what’s happening on the desktops of their employees where most of the work is taking place. Once observable data is compiled, business leaders can measure the amount and types of applications being used in order to understand employee capacity, identify hidden challenges, and empower leadership to target areas for improvement. Artificial intelligence systems can now be used on this data to look for patterns in the work, ripe for productivity improvements not easily spotted by business process improvement experts.
To start with, for back office and contact center functions, work applications can typically be broken down into two key categories: structured and unstructured applications.
- Structured applications: These applications are purpose-built to support key business processes at maximum efficiency. They function much like an assembly line, providing an efficient and repeatable process for a specific task, such as logging a service call.
- Unstructured applications: These applications are more free form in function, like e-mail, word processing, and a vast myriad of productivity applications, built over the years to plug gaps in the structured applications. They indeed are helpful at work, but introduce more chance for errors or going off-task.
Studies show that unstructured applications are more time-consuming and error-prone than structured applications. Employers should identify as many processes as possible that can be recreated in a more structured environment. This will enable employees to speed through repeatable tasks more efficiently and free them up to give attention toward tasks that require more concentration.
However, the answer isn’t always found in providing more technology. Often, too many apps can just exacerbate the efficiency problem. Workers are often forced to switch between as many as 35 different applications, thousands of times in a single shift, creating a ‘swivel chair effect’ as they go back and forth. As the number of applications used in a single work shift increases, so do error rates. This virtual swivel chair prevents workers from achieving an efficient workflow, adding unnecessary complexity to everyday work that hinders overall productivity.
Consolidating applications through process automation
Robotic process automation (RPA) is making lots of noise in the market as a way to streamline bad processes and simplify mundane tasks.
Bots can eliminate the swivel chair effect between systems and applications by automating tasks that previously required manual work, bridging the digital gap caused by poorly designed processes. RPA is particularly useful for businesses with underlying legacy systems that they can’t just rip and replace for a shiny new architecture. These bots serve as digital bandages to help business squeeze more utility from existing systems, putting the company on their first steps to digital transformation.
RPA removes the need for employees to perform repetitive structured tasks, such as processing claims, onboarding customers or employees, reconciling financial data, or searching for and manually updating customer information. It enables that work to be processed digitally, with greater speed and efficiency. This automates work with end-to-end processes to accelerate work outcomes and eliminate opportunities for errors, helping businesses deliver more purposeful applications to workers that can connect across systems for better outcomes.
Digital process automation: the big picture approach
But RPA is only the first step in what should be a larger and more strategic business automation transformation.
Once they have found their digital footing with RPA, organizations should develop more long-term solutions to efficiency challenges through digital process automation (DPA). DPA strategies use a variety of Intelligent Automation technologies to address work automation opportunities to the greatest extent possible. In other words, DPA doesn’t focus only on the automation of distinct tasks in isolation – it also provides automation and digitization, often combined with AI across the entire enterprise, and across all customer and employee processes from end to end.
The types of work DPA can address are primarily broken down into three categories:
- Programmatic: Almost all steps of the work in question – from tasks and decisions to flow, inputs, triggers, and resources – can be prescribed and designed in detail. This type of work is often clerical back-office administration, which lends itself to automation, particularly RPA.
- Transactional: In processing mortgage applications, many of the tasks and decisions involved, as well as workflow, can be prescribed and designed in advance. However, human discretion and expertise is needed to carry out some tasks, as well as in deciding when, how, and where work needs to be progressed—which requires a more strategic approach (potentially with some support of RPA).
- Exploratory: Similar to tasks such as complaint resolution and fraud investigation, the goal of the work is defined initially, but the sequence of tasks and decisions that need to be performed, and the people or roles needing to perform them, are unlikely to be known beforehand. Participants must ‘explore’ a set of possibilities rather than follow a recipe, necessitating DPA strategies beyond what RPA can offer.
While RPA can play a role in a digital transformation strategy, DPA is necessary for a successful, long-term strategy that looks to automate both the finer applications and the big picture processes.
By itself, RPA can deal with problems rooted in legacy systems that don’t account for today’s digital processes. A broader DPA strategy, by contrast, lets enterprises hit a “reset button” one process or application at a time, to create a foundation for their digital future. It uses several integrated and complementary tools to help companies address present and future needs in more fundamental ways.
These two different solutions together can create a cohesive, customer-centric, and future-proof digital transformation strategy. Using intelligent automation, especially DPA, can unlock unprecedented efficiency that enables employees to stay focused on work that moves their organization forward, meeting and exceeding the needs of modern customers.