“Digitalize or die” is a reality for most businesses in today’s competitive environment. Companies that fall behind in the digitalization arms race find it more difficult than ever to balance maintaining legacy IT systems while taking advantage of game-changing innovations like generative AI.
McKinsey estimates that 50% of all work tasks could be automated by 2045.1
At the same time, digitalization has radically changed the way we work. Gone are the days when managers and employees spent all their time in the same meeting rooms and cubicles. Gone are also the days when employees shared knowledge or gossip around the water cooler. Today’s digital environment connects skills and responsibilities across global value chains, where the tasks we do contribute to the organizational intelligence that is increasingly difficult to measure.
Only 16% of enterprise leaders feel their data is ready for technologies that would overhaul their processes.2
In this competitive new landscape comes object-centric task mining (OCTM) - a groundbreaking technology that measures enterprise process performance like digital heartbeat. In a world where digitalization is the main competitive advantage, OCTM unleashes the productivity gain of end-to-end process transparency like a digital twin of the organization.
Object-centric task mining will change the way you see digitized business operations for good. In this article we’ll give you the background, key benefits, and what you need to know as an enterprise leader.
What is task mining
Task mining is a technology that automatically captures user interactions within business applications to measure and analyze how work tasks are done.
Task mining can help you answer questions like:
- Are people able to perform the tasks given to them with the tools and resources provided?
- How much time is spent on different tasks and are employees able to focus on productive work?
- Do different teams or individuals perform tasks in different ways, and are there best practices that can be shared?
- What are the tasks that slow up your important processes, or create re-work in your workflows?
Task mining is not a new technology. It emerged from screen recorder solutions in the early 2000s and is a key component of the process intelligence software landscape.
Task mining is typically done by dedicated software programs that capture user interactions on the workstations (or computers) of employees. Task mining software automatically measures and visualizes how digitalized work tasks are carried out using task or process mining algorithms.
In the early days of business process management, business tasks, and processes were often reviewed as part of process analysis projects or time-and-motion studies. Even when process analysis was done by trained Six Sigma experts, it was prone to human error, costly, and only provided snapshots of performance.
Task mining software is much faster, more accurate, and cost-effective than manual task analysis methods. It can measure thousands of answered customer support tickets or purchase approvals to show in detail how these repetitive tasks are performed and can be improved. Task mining brings advanced data science to the field of operational excellence.
Why is task mining becoming popular
There is no denying task mining’s growing popularity. According to the Everest Group, task mining has become one of the fastest-growing areas of intelligent automation, with investments expected to grow by 75-85% in 2023.
Task mining has already proven its value. It gives detailed insights into the effectiveness of workflows and processes, allowing organizations to standardize, streamline, or automate repetitive work-related tasks.
At the same time, task mining has evolved well beyond its original goal of employee tracking and is now a key component of end-to-end process visibility.
When process mining software gives detailed insights into event logs within the main system(s) of record, task mining gives visibility into the 90% of work that happens outside of the CRM or ERP.
In banking and insurance core processes, 90% of processing work happens outside of the core system of record.
Another key driver to interest in task mining has been the need for automated process discovery. For companies that don’t have well-documented process maps or clear visibility into the health of business processes, task mining software can give an “as-is” reality of how work gets done. Not only that - task mining highlights exactly the areas where manual and repetitive tasks can be automated by RPA or other automation solutions.
Task mining reveals gaps in digital performance
The need for task mining is especially great within organizations undergoing the digitalization of work and core processes. Task mining can reveal overlapping workflows, inefficient IT systems, and even unnecessary process steps.
Whereas two decades ago many businesses ran many of their business operations around central enterprise resource planning system (ERP), the number of business applications used has been expanding rapidly. Today, the average large business relies on over 175 different business applications.
As more key tasks and processes have moved into different digitalized systems, businesses need to be increasingly sophisticated in measuring and improving the efficiency of work. Task mining uncovers the reality of how digitalized tasks get done and reveals gaps in operational excellence within and outside of the core ERP and business operations.
At the same time, the nature of work has changed and many employees have experienced challenges adapting to digitalization. A typical office worker now spends 50% of their time on repetitive tasks and up to 10% of their time toggling between different business applications. Task mining can identify how to streamline, automate or remove manual work, so employees can focus on more value-adding tasks.
Not only that - an increasing amount of work is done outside of core business organizations. Many global enterprises now utilize offshore shared services or external business process outsourcing partners. Task mining can give centralized Centers of Excellence and business operations leadership granular insights on how this diversified work gets done.
Limitations of traditional task mining
Despite increasing popularity there are still a few major obstacles in the way of task mining reaching mainstream adaptation.
The core challenge is that most task mining solutions depend on task capture methods that rely on decade-old technology ill-suited to the era of artificial intelligence and cloud computing.
- Many task mining solutions still rely on screen recording technology. While this produces very detailed data on individual work sessions, it can be extremely costly, and quite frankly clunky, to scale up to analyzing large teams or business units.
- Some task mining solutions utilizing Object Character Recognition (OCR) technology to process screenshots leak personally identifiable information (PII) on cloud servers. For this reason, many older task mining solutions are not compatible with GDPR regulations and can not be used within the European Union.
- Most task mining solutions available in the market today are employee-focused. They provide a narrow and limited view of individual employee task performance without providing an understanding of process context and visibility to team productivity.
In response to the many limitations of traditional task capture methods, a number of new task mining software vendors have emerged in recent years with more modern technology foundations taking an object-centric - rather than employee-centric - view into task performance.
What is object-centric task mining?
Object-centric task mining (OCTM) is a revolutionary solution developed in the 2020s that brings task mining technology to the age of artificial intelligence and cloud computing. It's the first time enterprises can really follow processes across business applications and IT systems. OCTM leverages advanced technology such as Work API to give end-to-end transparency to both processes and tasks across business organizations.
OCTM captures business process data from user interfaces of different business applications. This method allows following the process and related object tasks, such as invoicing, customer ticket handling, or loan application across the organization, and automatically generates an end-to-end view of processes and tasks.
The data capture method is silent, non-intrusive, and real-time, similar to the processes that silently and continuously run in the background but are not known to many. OCTM automatically captures process data from the user interface of different business applications. It allows you to follow business objects, ( eg. invoices, customer tickets, and loan applications), across the organization and automatically generate an end-to-end view into processes and tasks.
The OCTM data capture method is silent and non-intrusive to employees. It captures business object data in real-time, similar to the Microsoft Task Manager many desktop users find on their computers. The main difference is that OCTM does not collect any user-level information or data from non-business applications. In other words, it doesn’t track what you listen to on Spotify, what you post on Facebook, or even know who you are. The focus of analysis is the business objects flowing from one application to another.
In the above example, you see task and process events captured through OTCM related to the approval of a purchase order. In this case, the business object tracked is the unique purchase invoice number 4500016565. OCTM can link all activities related to this business object from any other business applications and produce an end-to-end process map automatically with key task and process events mapped in sequence.
OCTM addresses the main limitations of legacy task capture technology. Since the data in the UI is in a structured format, OTCM is able to effectively gather data that is otherwise hard to get from databases. OTCM is scalable, granular, and compatible with data privacy best practices. It gives continuous process insights and seamlessly connects the tasks providing an end-to-end understanding that has been missing with traditional task mining tools.
Case example in credit approvals
Object-centric task mining addresses the real-world challenges of today’s globalized teams and business operations. It can adapt to complex digital landscapes that include both legacy and modern tools.
The core advantage of OCTM is that key business objects, like case IDs, customer service tickets, or individual shipping numbers can be tracked as they flow across business operations without the need for screen recording or additional event log mining from system databases.
Let’s see a typical case example from an international banking organization.
- A new credit application is received in the Salesforce cloud CRM and reviewed by the front office Team Washington in the United States. An earlier credit application is identified and policy compliance is reviewed. After validation, the case moves to the next team. The active work time by the team was measured on the case as a total of 25 minutes.
- The mid-office Team Madrid in Spain picks up the credit application 2,5 days later. The case number CA5324 is double-checked against an internal Microsoft Excel database. The case review is concluded as approved in a total of 30 minutes of active work time.
- Finally, the back office Team Bangalore in India picks up the case 14 days later after approval after the customer has also approved the credit terms. Credit terms are updated in SAP S4/Hana and the credit team is informed over Microsoft Teams.
The total manual processing time of this credit application tracked in OCTM was 75 minutes and the total throughput time was 17 days. These metrics are automatically benchmarked against thousands of other similar transactions, and key bottleneck points are flagged to process owners.
The entire end-to-end process has been measured and prepared for analysis seamlessly in the background on a business object level without need for any employees to change how they work.
OCTM compliments object-centric process mining. It can be used completely independently or in alignment with process mining implementation within a Process Intelligence Center of Excellence.
Object-centric task mining use cases
- Process improvement - re-designing and optimizing the performance of key processes.
- Lean transformation - utilizing data and insights to guide the re-engineering of core workflows and processes.
- Streamlining customer experience - connecting the dots of a customer journey across different IT systems and approval steps.
- Productivity boost - identifying and removing bottlenecks getting in the way of productive work.
- Compliance monitoring - tracking how well different teams and business units follow the agreed processes.
- Standardization - aligning process execution against a plan to avoid the need for rework.
- Prove case for digitalization - quantifying master data management challenges and the need for data integration.
- Advance intelligent automation - identify and prove the business case for automation opportunities.
- Guide digital transformation - measure and increase the adoption of cloud-based software.
Object-centric task mining in the future of process intelligence
With an object-centric view, task mining has experienced a massive evolution from basic employee tracking tools to the key enabler of end-to-end process visibility.
Recent developments in OCTM take process intelligence from the backward-looking field of business intelligence to prescriptive analytics. It gives enterprise leaders an unparalleled ability to predict future performance and orchestrate process execution continuously with automated insights and triggers.
When you’re ready to level up your process intelligence, reach out to Workfellow for a personal introduction to object-centric task mining. Peak performance could be only one quick demo away.