Is your process intelligence tech rising to meet the challenges of enterprise scale and complexity?

Process and task mining tools, collectively termed “process intelligence technologies,” have become mainstream among large enterprises in the last few years. This software category has grown exponentially as the use cases expanded along with technological advances in data mining and visualization to better represent and fix how business processes run in the organization. Despite the progress, HFS sees most current enterprise implementations fall short of their potential.

There are two main culprits to blame. First, the current swath of products and solutions do not fully scope for or address the sheer scale and complexity of large-scale, global businesses, and they can’t paint an accurate picture of how operations run. Second, available solutions do not adequately run analysis across all process optimization levers. The gap includes technology-agnostic analysis, such as generative artificial intelligence (GenAI), and more traditional, simpler, non-value-added analysis to standardize, eliminate, optimize, or terminate processes. In this POV, we explore the example of KYP.ai (Know Your Potential, for the uninitiated) and how it accounts for this market gap in collaboration with the largest organizations seeking comprehensive process insights.

Large enterprises struggle to get an accurate, representative view of their operations today

The quest for data and artificial-intelligence-driven, near-autonomous, digitized business operations continues to be a key aspiration for enterprise leaders (take your pick of terminology, but the goal is technology-enabled business operations). But getting to this tech-driven nirvana requires large organizations to undertake major operational transformation. Whether the priority is process automation or infusing analytical insights into business processes, the first stop is understanding and baselining the current state: How are we performing today? Where are our biggest bottlenecks? Process and task mining tools come to the rescue, touting different levels of process discovery and visibility to achieve this goal.

But in implementing these tools, are we really getting the entire organization’s work processes mapped and tracked as part of a “multi-modal command center” view, ready for different digital technology interventions? Our recent research study findings, surveying over 260 enterprise leaders, show that it’s hard to go beyond the basics. Almost 50% of enterprise leaders are still looking for ways to use process intelligence data more predictively (see Exhibit 1), with the next majority expecting this to be a two-to-five-year journey.

Exhibit 1: Almost 50% of enterprise leaders are still exploring ways to become more predictive with their data

Sample: N=260 enterprise leaders
Source: HFS Research, 2024

The challenge with today’s popular process intelligence technology solutions is that they are too often used in siloed use cases and don’t account for the complexity of globally dispersed business operations. We’ve seen the “spaghetti maps” of a typical process discovery, and for good reason—no two people do things the same way, whatever the ideal process flow might dictate.

An enterprise might deploy process mining for one business unit, region, or subfunction, but it rarely maps to cross-departmental process flows or shares data models to provide a full picture of transactions flowing in and out of an organization. Task mining tools, meanwhile, are often set up to study, for example, two dozen employees over two weeks to understand user journeys and their variances. Possibly due to technological constraints of data compute power and storage, these tools are not typically deployed across an entire company’s workforce.

Neither of these approaches comes close to delivering on the goals of an operations command center, where all your processes might be part of the scope, all your systems studied, and all your employees included. The goal is to get near-real-time views of the current state to undertake continuous monitoring and use predictive insights to anticipate process changes and make better business decisions. Our research shows operations leaders view this kind of visibility as a potential game changer. Enterprises seek cross-functional, multi-level visibility into operational performance and monitoring and consider it a game changer for process intelligence usage within companies (see Exhibit 2). The need for real-time insights and better visibility into processes and employee tasks highlights the importance of transparency in cross-functional operational performance.

Exhibit 2: At least 95% of organization leaders see combining visibility into cross-functional operational performance and monitoring as a game changer

Sample: N=260 enterprise leaders
Source: HFS Research, 2024

The case of KYP.ai: What would “holistically” designed process intelligence technology look like?

The potential for process intelligence to impact broad-based operational performance is vast. The need of the hour is a solution that can meet the scale and speed at which enterprises operate and the associated use cases that go enterprise wide, tracking and contributing toward broad-based business performance. KYP.ai, a startup in Berlin, Germany, had a similar realization while developing its process intelligence product in its last five years of engaging with enterprise leaders. Adam Bujak, CEO and co-founder of KYP.ai, pointed out in a conversation with HFS, “Data can be used not only to fill automation pipelines but also to fuel innovation and drive change in cross-team workflows, generating tangible customer outcomes.”

KYP.ai describes itself as a productivity mining company that provides insights into how work gets done with the help of artificial intelligence (AI). Its Productivity 360 platform aims to tackle some of the core challenges enterprises face regarding improved visibility and performance leading to quick decision making. At the heart of achieving these goals lies KYP.ai’s four-element, holistic approach to productivity:

• People: Comprising efficient teams, work-life balance, and hybrid work
• Processes: Led by ROI-driven outcomes, compliance, and shorter cycle time
• Technology: Helping to capture app utilization, performance, and user behavior within apps
• Data: Incorporating the ability to export to other third-party tools in multiple formats

Productivity 360 provides live data visibility with minimal resource impact

KYP.ai believes full visibility into live data is a prerequisite for success in this category. Its Productivity 360 platform can handle multiple applications and customers, including known ERPs, web applications, and remote desktop steps; live visibility and data streaming capabilities; and competitive advantage in technology due to the end-to-end ability to cover processes with minimal impact on bandwidth and CPU.

Some customers have been using the platform for three or more years with no noticeable machine performance impact from collecting data from 4,000 end-user machines. The platform enables strategic moves, tactical changes, and operational adoption of new ways of working, including employing robotics, automation, new workflows, and applications or GenAI as a solution approach. Its adoption in daily work is also expected to be transformational.

Task mining and process mining deliver a comprehensive solution

Apart from its focus on providing detailed process-related information, the KYP.ai platform approach combines task and process mining to deliver a comprehensive solution to customers.

KYP.ai achieves these goals with these capabilities:

• It enables full visibility of the organization’s operations and allows the execution of tasks in real time via a “helicopter view” or multi-modal command-center view that can show processes running live.
• It helps close the data gap with the availability of real-time data, which is imperative to data-driven transformation. It captures existing data within enterprises in various formats, such as user activity data and metadata. It aggregates it using a holistic approach to deliver 360-degree insights to enterprises.
• It makes various metrics and dimensions available with insights into engagement, work distribution, and work-life balance.
• It enables the identification of automation candidates and candidates from other technologies to showcase the impact of transformation on headcount coverage.
• The platform provides easy implementation, scalability, ROI, and flexibility.

Case examples for handling enterprise-wide scale, speed, and complexity

Some of the KYP.ai client stories demonstrate how the company is on the path to becoming a business partner for customers, pushing R&D and product development in the last few years toward meeting the real needs of large, complex organizations. Its goal is to scale beyond small projects and partner to deliver data-driven transformation. We hope this worthy pursuit will expand the current understanding and reach of the process intelligence software category far beyond its current siloed use.

KYP.ai helped an FMCG giant build data and a digital core

For a global fast-moving consumer goods (FMCG) player, technology was the key barrier to moving ahead and utilizing process intelligence to the best of its ability. Application response time was high, CPU usage bandwidth was low, and platform interaction with the end users was also very limited. KYP.ai helped by developing a Productivity 360 suite that helped to build data, the digital core, and, gradually, the APIs. It also enabled aggregating all the data to generate insights on people, processes, and tech. For example, it removed friction and reduced the time required for month-end closing processes.

KYP.ai also helped a leading supply chain organization eliminate global blockages and enable price negotiation based on service elements

The organization faced challenges dealing with the sheer scale of operations and managing multiple stakeholders across Europe, the Americas, Asia Pacific, the Middle East, and Africa. KYP.ai facilitated the management of humans, capacity, and volume using underlying data within the organization to become data-driven and generate live insights. KYP.ai enabled a 5% efficiency gain for the customer.

KYP.ai’s Productivity 360 enables parallel process mapping across various platforms

HFS Research spoke to a KYP.ai client in the digital tech and business solutions space, Mindsprint Digital India. The key stakeholders mentioned choosing KYP.ai as the partner of choice because of its scalability and flexibility. The company started working with KYP.ai in 2021 and has become an implementation partner. R.S. Krishna, the director and operational excellence head, mentioned that one of the key advantages of using KYP.ai’s Productivity 360 platform is the ability to map processes in parallel across multiple platforms in the form of various dashboards. This enabled digital value stream analysis for over 600 processes, which other competitors do not yet have, improving process efficiency and standardization. KYP.ai also enabled the company to reduce dark data and achieve 90% to 95% end-to-end digital sequences in its processes. While KYP.ai offers an overall view of productivity and data management, the core competitors are more focused on specific solutions to a piecemeal problem.

From a relationship standpoint, R.S Krishna mentioned, “From where we started to where we are right now, a paradigm shift has been brought in by working together with the KYP.ai team.”

Regarding the future roadmap, the company is exploring KYP.ai’s GenAI-infused offerings in 2024 to better analyze process variations, improve controls, and implement technologies for hyper-efficiencies beyond what already exists.

KYP.ai aims to be the partner of choice assisting organizations in embracing GenAI

KYP.ai is positioning itself as the partner of choice for organizations seeking to move to the next level with GenAI adoption. Organizations need to be “ready” to make that move, and this is where KYP.ai sees itself as able to help enterprises tackle the three core issues.

Building the digital core to generate real-time insights

Building the digital core involves having the data in place to generate real-time insights. KYP.ai’s agents are deployed on users’ computers organization-wide, where they collect GDPR-compliant data from diverse work-related applications (including remote applications running on the users’ computers). Close to 100,000 apps and activity spots per minute can be collected with live visibility and insights without draining the CPU. The Productivity 360 platform uses AI and computer vision to convert unstructured data into structured information.

Identifying GenAI and automation opportunities using pattern detection

KYP.ai follows a data-driven and automated search approach to identify GenAI opportunities. The agents analyze multiple processes to reduce process steps for quicker results. They also use natural language processing (NLP) for discerning patterns. Pattern analysis scaling is also possible for organizations with a large workforce enabled by supervised learning in-house for pattern consolidation.

Measuring the impact of GenAI deployments

The engine measures GenAI’s impact on productivity and compares user productivity within the organization. This is followed up with progress monitoring via the Productivity 360 platform, enabling real-time visibility into processes, technology, and workforce optimization opportunities and their impact.

GenAI deployments are in full swing, and a positive impact is expected soon

In terms of deployments, KYP.ai has played a crucial role in optimizing investment for a pharmaceutical manufacturing company deploying MS 365 Copilot, a GenAI tool. With the license cost of $30 per user per month, the investment could amount to millions of dollars for a large organization. KYP.ai identifies the right individuals, processes, and country of operation for Copilot licenses, maximizing future financial returns on MS Copilot investments. Additionally, KYP.ai has helped measure the expected boost in employee productivity post-Copilot deployment, revealing potential improvements ranging from 5% to 19%. Using KYP.ai’s capabilities, the pharmaceutical manufacturer expects to maximize monthly financial returns by up to $538,000.

By measuring the adoption level of the new GenAI solution, KYP.ai helps companies and employees in their change efforts. They can use transparency to benchmark adoption levels, learn from each other, and identify new use cases.

The Bottom Line: KYP.ai is well on the path to balancing traditional forms of process improvements via investments in modern-day GenAI integrations with its Productivity 360 platform, but we need to step outside the current narrowly defined use cases and siloed technology uses to see the vision realized.

Process intelligence can—and should—have a C-suite level of impact on business performance in terms of the outcomes going above and beyond regular transactional outcomes, moving more toward strategic business outcomes.

Don’t miss the forest for the trees. Many companies lack a data-first approach and struggle to leverage the benefits of process intelligence beyond initial projects. To reap the benefits of the digital core combined with process intelligence offerings like KYP.ai’s Productivity 360, enterprises need to be ready to push themselves by going beyond what seems to be the obvious and proactively driving change efforts at scale.

The ability to focus on continued gains from process intelligence is not possible unless enterprises empower their teams with data to access real-time insights, which focused investments in GenAI can enable. KYP.ai has started its concerted efforts to drive a holistic offering combining traditional process intelligence with AI-led insights, and we look forward to seeing the fruit it bears over the next couple of months in terms of deployments and outcomes.