Cognitive Productivity Automation or CPA solutions focus on increasing user output while working with existing processes and software.
For professional services providers relying on well-paid knowledge workers who have problem-solving and critical-thinking skills and can function independently, higher productivity leads directly to increased profitability. That’s why these organizations are always looking for effective productivity solutions that knowledge workers will actually use. The best of these solutions not only reduce the inefficiencies associated with administrative tasks, but also provide increased value to clients, mitigate compliance risk, and help generate data-based institutional knowledge across the organization.
Improving on Legacy Approaches to Automation
Traditionally, professional services providers have applied end-to-end solution automation for specific, well-defined problems — activities like calendaring, application tracking and email management. In this implementation scenario, there is a lengthy R&D cycle on the vendor side, after which a solution is applied virtually out of the box in the client’s environment and is fairly adaptable.
However, professional services firms using this approach can enjoy the benefits of such solutions only for a small subset of automated administrative tasks while absorbing costly change management expenditures to support the switch to new applications and workflows.
Alternatively, robotic process automation (RPA) — which operates at the UI level — focuses on automating particular processes inside an organization. This approach to solution implementation is best applied to relatively mundane and repetitive tasks like data entry, order processing, reporting and onboarding. Transitioning to the new solution often relies on time-consuming and error-prone manual processes, like inputting data into new software and extracting names from spreadsheets. If the organization makes any updates to the UI, they also run the risk of a corrupted RPA script causing data loss.
End-to-end solution automation and RPA share common limitations on scalability and flexibility — and both involve contending with the ongoing investment and organizational disruption associated with adapting to new software.
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Further, once implemented, application performance is inherently static: These approaches do not help organizations build and leverage institutional knowledge over time, nor can they mimic the nuances of human cognition that is essential to the specialized roles of knowledge workers.
Harnessing the Power of Cognitive Productivity Automation (CPA)
Unlike end-to-end solution automation and RPA, cognitive productivity automation (CPA) places a cognitive layer between the user and legacy software — meaning that CPA powers automation that mimics human cognitive functions. Using artificial intelligence, CPA “trains” itself to perform specific tasks like email management, time capture, and form handling — without requiring users to switch applications.
Cognitive Productivity Automation or CPA solutions focus on increasing user output while working with existing processes and software. Users can apply these capabilities to a wide range of tasks, including tracking deadlines and project stages, classifying emails based on content, automated task creation and cross-team collaboration.
Consisting of a set of “virtual agents” designed to perform specific tasks and unify models that work across an organization, CPA includes cognitive models for behavioral tracking, behavior pattern recognition, unstructured data analysis and user interaction models. Designed with a common architecture, a variety of virtual agents can be dynamically added to the system to perform new sets of tasks.
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CPA is highly adaptable to unstructured data and undefined processes. It builds expertise continually by learning from users’ input and adapting based on their behavior to provide proactive assistance or suggestions. Whereas the efficacy of an RPA implementation can degrade up to 50% due to process changes and maintenance problems, CPA continuously increases efficacy over time, adapting to each user’s behavior and unique requirements while providing the most flexible automation solution possible. In the process of learning and adapting, it also builds collective knowledge across the organization that can yield valuable and actionable business intelligence.
CPA’s ability to adapt to individual processes — without engineering involvement — makes the solution indispensable in handling a high volume of small processes applied to unstructured data. Further, CPA’s unique ability to mimic a human’s decision-making process is of particular value to knowledge workers. Adaptability, ongoing knowledge accumulation and the ability to transfer behavioral patterns from top performers to the rest of the group allow CPA to play a critical role in scaling an organization’s automation strategies.
Tapping into the Value of Knowledge Accumulation and Transfer
For purposes of illustration, let’s say that in a typical professional services firm, 20% of staff are diligent about adhering to the guidelines for administrative tasks, and 80% are lackadaisical. This lack of alignment can have a significant collective impact on the firm’s productivity, utilization and profitability.
Consider this example taken from the legal industry:
Some lawyers in a practice group capture time data contemporaneously, filling in the activity description correctly without involving the b****** partner. Because invoices are timely and accurate, clients pay faster with fewer instances of contested bills. This positively impacts practice-group profitability.
Conversely, other lawyers in the practice group put off time capture, and struggle to reconstruct their activities when it comes time to release an invoice to the client. Dealing with the fallout of the reconstruction process impacts the entire team: With the reliability of the bills and associated narratives in question, invoices are more likely to be delayed or rejected by clients.
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Applying CPA, the 80% of staff who aren’t meticulously following the rules not only automatically receive suggestions based on the best practices of the top 20%, but also benefit from automated time capture they can check at the end of the day, instead of having to choose between recalling activities long after they are completed or interrupting their work multiple times per day to make entries. With cognitive productivity automation, reviewing auto-completed timesheets takes users about five minutes; reconstructing activities can sometimes take hours.
When you consider the collective time savings and improved efficacy for the 80% of staff struggling with time capture on a global scale, the direct impact on utilization, client service and value, and operational efficiency cannot be overstated.
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If we look at this example from the legal industry as a model, it’s easy to see how other types of professional services firms can apply CPA to a wide range of mundane, high-volume administrative tasks while accumulating data-based knowledge on both an individual and collective level.
For instance, CPA can prevent users from accidentally sharing sensitive information with unauthorized individuals. This is particularly useful for firms engaged in M&A matters. The solution can also identify missing fields in documents like contracts and intake forms, and automatically issue an email request to appropriate users to provide the necessary information. CPA can even eliminate manual processes associated with cutting and pasting to produce a document — a particularly useful application, for example, for HR staff who mine data online to identify and build profiles for recruitment.
Across these and other use cases, a CPA solution not only streamlines tedious, high-volume functions, but also prevents costly user-generated mistakes, which undermine productivity.
Reaping the Rewards of Increased Productivity with Cognitive Productivity Automation
Professional services firms using solutions based on CPA are achieving favorable results and rapid ROI by implementing passive productivity enhancements that don’t require the disruption of ordinary business activities to be implemented.
Knowledge workers continue to use the applications to which they’re accustomed and don’t need to learn new workflows or take on training. At the same time, the aggregate effect of small productivity improvements achieved at an individual level have a big impact collectively, helping firms improve business agility, profitability and competitive advantage.
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