5
Business leaders often focus on high-level decision-making that can change the course of the game.
But it’s impossible to get a clear high-level view without also having visibility into the details of how work is performed. A workflow-level understanding is only as good as the data on the user-driven data interactions that feeds it. Task mining is one method of uncovering how the smallest actions take place at your organization and how they contribute to wider-scale work.
Here, learn everything you need to know about task mining, including how to leverage it to make more informed workflow improvements and help your tech tools and team members do what they do best.
What is task mining?
Task mining analyzes user interactions on desktops and within applications, tracking tasks and micro-workflows. Part of the process intelligence framework, task mining provides insights on how work gets done. Software traces actions like mouse clicks, keystrokes, time spent in applications, manual file updates, and data copying between systems.
The goal of task mining, like other process intelligence methodologies, is to highlight inefficiencies in business processes, like bottlenecks or redundancies that slow work down. Organizations can then use this information to spur process improvements and more wisely integrate AI automation opportunities.
How task mining works
Task mining happens in three steps: data capture, aggregation and pattern recognition, and insight generation. Here’s more on each.
Data collection
In the data capture stage, software on desktops or in internet browsers tracks user actions—ranging from keystrokes to app switching—in real time. The lightweight task mining software, once configured and approved, runs discreetly in the background of work, never distracting users or slowing work.
Aggregation and pattern recognition
After data has been captured, the software uses artificial intelligence and machine learning to read the information, mapping patterns and pinpointing inefficiencies. Task mining tools look for slow processes and repetitive tasks, while creating flow charts of how work really gets done.
Insight generation
Finally, the software offers AI-powered insights on how to streamline work. Recommendations may include eliminating redundant tools or processes or speeding up time-consuming tasks, especially those that can be automated. Leaders can then use this information for data-driven decision-making on improvement opportunities that help businesses achieve operational excellence.
Task mining vs. process mining
Task mining and process mining solutions are both process intelligence initiatives that help businesses track and optimize work.
While task mining focuses on user interaction data, process mining looks at system-level data, like event logs, monitoring the end-to-end processes that comprise key workflows. In other words, it performs process analysis not task analysis. For example, process mining might be used to assess a procurement department’s payment process flow, identifying slow handoffs or redundant manual invoicing tasks.
Process mapping has a similar goal to task mapping: to provide companies with real-time data on inefficiencies that are ripe for improvement. Used together, task mining and process mining are duly powerful. Businesses gain metrics and maps on how work happens on a task and a process level.
Scribe levels up the intelligence gathering even further, performing workflow mining. These three mining styles provide a comprehensive total view of work—so you can actually understand how work happens across teams and tools.
Benefits of task mining
Task mining has countless different use cases, able to help virtually any department work faster and smarter. Here are a few real-world business applications that show how task mining benefits organizations.
- Visibility into hidden manual work: No matter how well you understand your team’s workflows, you don’t always know where there are bottlenecks. Task mining pinpoints slow manual tasks that could be done faster by automated tools, freeing up the humans in your department for more meaningful contributions.
- Faster identification of repetitive or inefficient tasks: Task mining also uncovers repetitive work that could be performed in fewer steps (or not at all). For example, an accounts payable team might be wasting time entering data into multiple spaces, like their ERP and an internal spreadsheet.
- Reduced copy-paste errors and tool switching: When people copy data from one system to another or have to jump between interfaces to complete a single task, they lose time and generate errors. For example, an HR team that manually enters new hire data into its CRM and then into its payroll software opens itself up to several opportunities for information-copying mistakes. And a simple error could become costly, causing payroll or benefits administration snags that negatively impact the employee experience or imply compliance issues.
- Better standardization across teams: Not everyone works the same way, and task mining outlines how different teams perform the same work, highlighting the most efficient routes. Leaders can then standardize the most functional workflows and ensure everyone adopts them.
- Stronger business cases for automation and process redesign: A company may feel ready for its grand digital transformation. But the reality is that if the organization runs on disorganized processes, high-powered tech, like automation, won’t be able to run optimally. Businesses should first leverage task mining solutions to spot and rectify inefficiencies, so that they can only integrate time-saving when the underlying workflows are ready for it.
Limitations of task mining
Task mining gives businesses laser-sharp visibility on task-level data, but it doesn’t provide a high-level picture of workflows—at least not on its own. You’ll need to use task mining in conjunction with other process intelligence initiatives to get a more holistic sense of how work happens.
Here are a few other limitations of task mining to also consider.
- Accuracy issues: In environments where users switch between functions at lightning speed, task mining may not be able to keep up as it doesn’t consider the full context of user interactions. For example, if a sales representative quickly toggles between their CRM to record a customer interaction and their company’s website to find a product, the task mining tool might not fully track these actions (or understand how they fit together).
- High implementation effort: Task mining tools need high volumes of quality data to work well, and if these aren’t available, they may struggle to generate coherent maps and insights.
Workflow Mining with Scribe Optimize: Turn task insights into action
Scribe Optimize elevates task mining beyond static recordings to generate the most complete picture of work possible. Here’s how Scribe is different.
- Workflow-level capture: In addition to capturing micro-level tasks and process data, Scribe assesses workflows. For example, Scribe can analyze your entire cross-functional employee onboarding flow, from signature gathering to training.
- AI-driven recommendations: Scribe’s Workflow AI leverages artificial intelligence to suggest automation opportunities and other business process optimizations.
- Cross-tool visibility: Scribe takes a comprehensive view of work, even when it happens across dispersed tools or business areas.
- Continuous improvement: Workflow AI performs iterative monitoring, meaning that as you make business process improvements, it continuously tracks tasks and workflows, offering insights for further positive shifts.
Measurable improvements from everyday task mining
Task mining helps teams understand how they really work—not just how they think they work. With hard data in hand, businesses can make informed improvements and ready their workflows for scalable tech integrations like AI automation.
In the end, organizations enjoy better productivity, higher-quality outputs, and improved employee and customer experiences. Plus, team members get to put their talent to work, instead of wasting energy on menial tasks.
FAQs
What types of workflows benefit most from task mining?
Task mining is best for workflows that include many manual, repetitive tasks. Examples include invoice processing (accounts payable), help-desk workflows (customer service), employee onboarding processes (HR), payroll management (HR and finance), and order fulfillment (operations).
Is task mining difficult to implement?
Task mining runs on lightweight integrations that are generally easy to implement. That said, some employees may have privacy concerns regarding data monitoring that you can dispel by explaining what type of information these tools collect (and don’t) and the software’s security features.
How do organizations handle privacy and security in task mining?
Organizations can start by transparently explaining how the task mining tool works to employees, highlighting that it only tracks essential data on approved applications. They can also use software that masks employee identifiers and requires password-protected access.
How does Scribe use task mining insights?
Scribe Optimize uses task mining information to suggest business process and workflow improvements, helping teams save time and resources and avoid errors (like copy-paste mistakes).
