With a rush to reset priorities, rethink the way our customers wish to engage, and acknowledge hybrid working with many staff likely to never return to traditional office settings, executive teams face a problem. How can we still manage and monitor performance? How can we continue to drive efficiencies in our processes and systems? How can we boost the productivity of workers when they're remote? Productivity improves by 20-25% in organizations with connected employees. ¹

As organizations pivot from business continuity and contingency planning and back to focusing on what will become a new normal, productivity once again takes center stage. With increasing numbers of staff now working on critical content and processes from home, chasing efficiency and applying new systems can be difficult. Many organizations are now turning to technologies like process mining and task mining to support their robotic process automation efforts and address conformance and compliance risks. And employees are continuously being dedicated to performing these error-prone tasks, not without impact on operations and customer experience. Meanwhile, process mining and robotic process automation (RPA) technologies are becoming a key element of digital transformation efforts worldwide.

Anticipating unexpected risks is built into the DNA of every organization. A Gartner survey suggests that 69% of organizations have increased their digital transformation spend, primarily focusing on investments that foster improved customer experience and support better business insight.

Despite increased spend to achieve operational resilience, a McKinsey & Company study found that digital transformation projects haven't moved beyond the piloting phase or grown significantly since 2018. While RPA continues to be the impetus behind digital transformation initiatives, there's been a consistent undercurrent of reports intimating that companies frequently get stuck after deploying just a few bots, with up to 50% of RPA deployments initially failing, according to a recent Forbes article. The article also points out that RPA is not a silver bullet when it comes to digital transformation. RPA's "robotic" nature means that it's geared toward well-defined data formats, steps, and outcomes. Throw in unstructured data or process variation and RPA struggles, at best, or breaks, at worst.

Empowering and engaging the workforce to boost productivity

The best personal assistants in the modern digital enterprise won't be fueled by coffee, rather they will be powered by ones and zeros – they'll be robotic. When you think about the needs of these robots, most of the tasks they'll complete will require a human skill. These skills can be found in Digital Intelligence, the understanding of how your operations, how your processes are currently work, and the content that fuels them – empowering you to make impact where it matters most: customer experience, competitive advantage, visibility, and compliance.

In today's business environment, driven by digital technologies like RPA and other automation tools, a higher level of intelligence is required when it comes to processing content. Smarter technology is needed, but it must also be easy to train and consume in the automation tools. When you want to identify where these new robotic assistants will add the most value and impact to your organization, you need to understand how your people work.

Task mining captures and analyzes how people interact with systems through recordings and snapshots, helping companies identify and have a deeper understanding of what employees actually do when they perform a particular task and identify the common actions. This data is then used to improve processes and guide automation efforts, and provides a more in-depth view of the processes. It allows companies to monitor how tasks are performed, aids automation efforts, and ensures those automation efforts are aimed at where the greatest productivity gains can be made. Additionally, task mining can bring the following benefits to an organization:

• Task mining supplies unique productivity data that you can't get from business data alone. There are two types of productivity analysis:
  • Resource Productivity: It helps see how productive each user is and the amount of time each user has spent on different applications and websites. It also helps discover which applications and websites are frequently used and identifies which users are highly productive.
  • Task Productivity: It helps you dive into the details of each task in the process to determine which tasks the most productive users are working on and which tasks are being worked on in parallel.
• Improvement Evaluations
  • Uncover Automation Opportunities: It uses insights on performance, productivity, and frequency to help surface the biggest opportunities for automation. It also helps automate common processes and unproductive, repetitive tasks.
  • Alert to Process Violations: Protocol analysis uncovers areas where required process execution rules are violated, including the order in which the tasks and process steps should occur, time limits of how long certain events should take, and when any step is missing or repeated.
  • Reduce Process Gaps: It helps develop strategies to narrow the most critical process gaps by addressing the corresponding root causes.
  • Discovery, Compliance, and Performance: It helps combine task mining (user interaction data) and process mining (business data) when conducting business process analysis to provide a new level of insight, such as:
    • Process discovery
    • Conformance checking
    • Root cause analysis
    • Segregation of duties
    • Performance analysis

Task mining offers considerable advantages for all modern organizations because it allows them to discover the inefficiencies of manual work models outside of their transactional systems and to measure and optimize the productivity of their staff.

Understanding the intersection of your people, processes, and data is the starting point for true business transformation. The ability to connect the dots between user task data, system logs, and business data empowers organizations to reduce process friction, improve customer service, and accelerate digital transformation.

The approach to task mining – often confused with monitoring employee actions as part of their performance – is to surface optimum patterns of task execution so that organizations may shift away from highly-repetitive tasks and empower employees to focus on higher value tasks. It can also be effectively used as a personal productivity tool for employees to see how they're working, how they can improve, and identify areas where additional automation can assist them. For example, if an employee doesn't see the benefit from a program in place, they can show their employer how many hours they lose with the current program in place or how it's negatively impacting their work productivity.

The future of task analytics

Task mining enables companies to understand how they manage tasks by collecting and analyzing user interactions. It has parallels with process mining, but it uses user interaction data, rather than logs files and business metrics, to analyze processes.

Advanced task mining tools have protocols and settings in place to safeguard users' personal data since they log user interactions in real-time, helping avoid infringing on users' privacy. With the increasing popularity of this technology, this could be one of the main challenges for task mining vendors.

It's not enough to be able to extract data from any system of record. To deliver a complete view of your business operations that enables true business transformation connecting people, processes and data, you need to mine user interactions and their impact on overall process execution.

The future of work requires us to think about work in a more fluid way. We must reimagine the way work gets done, across multiple people, machines, and interactions. Breaking it down into tasks is the most sustainable way to segue into a sustainable hybrid human and machine workforce.

Getting started with task mining

If you're interested in starting a task mining initiative, you can get started by first identifying the pain points and the data. Which groups of people are most frustrated with your current systems? Or which systems are complained about most? Redirecting your thinking from the technology to your business problems. Pick a problem that matters to the business and your employees, and that you can realistically tackle with task mining. Then determine the value of solving it and what metrics you'll use to measure success.

Additionally, ask yourself: What is your corporation vision? What are you looking to achieve and how does your business' operations perform? Ultimately, the right process mining software varies depending on the size of your organization, business needs and goals.

Author: Mark McGregor

A former Research Director with IT industry analysis firm Gartner, where he covered EA Tooling, Mark McGregor is now Head of Process Intelligence Strategy at Milpitas, Calif.-based ABBYY, a Digital Intelligence company. Mark has an extensive background in BPM, Enterprise Architecture and change management. Much of his 25 years has been spent working with or for vendors in the modelling markets, giving him unique insight into these specialist markets.

Mark has authored or co-authored four books on business and process management, including "Thrive! How to Succeed in the Age of the Customer" and "In Search of BPM Excellence," and "People Centric Process Management."

Widely respected for his knowledge and views on business change, he is the creator of "Next Practice" and has variously been described as a "BPM Guru", a "Thought Leader," and a "Master of Mindset." For his latest work on "Customer Excellence," he is collaborating with Jim Sinur, and Gero Decker.