Work intelligence is key to winning the market. Companies strive to reduce costs and modernize practices in today’s environment. A complete understanding of how work is conducted is required to make real operational improvements. Complex change is difficult and even harder without an accurate view of the current state.

A new framework for work intelligence

Technologies that automate and monitor business process activities are top of mind for many executives. Advisory firm Deep Analysis has a new perspective to reframe these typically siloed technologies under a single, self-supporting, logical and practical framework. The broad concept of Work Intelligence encompasses a myriad of complementary technologies, including Process Mining, Task Mining, RPA, BPM, Workflow Automation, Decision Intelligence, Process Orchestration, and Low Code and No Code platforms.

An organization’s health can be defined by and diagnosed through the processes that operate within it. The practice of Work Intelligence can provide organizations with a path toward process analysis, augmentation, and improvement through an equal partnership between human and machine intelligence. Rather than digital transformation, Work Intelligence – cognizant of the realities of the current economic landscape – is about digital harmonization. This is apt, as today, there is neither the appetite nor budget for big-ticket platform purchases and ambitious digital transformations.

Through continuous and holistic process management, the concept offers the potential to offset sudden changes in policy direction that can be so disruptive. Work intelligence enables stakeholders to decode the processes and interactions within business operations. By pinpointing where human and machine intelligence are best applied to achieve a desired output and balancing human intuition against AI-driven recommendation, improvements beneficial across the enterprise can be formulated, simulated and applied.

Toward continuous discovery

Process mining is gaining increased prioritization and investment as organizations work to drive efficiencies and enhance their processes. It’s now projected that the global process mining software market will reach $11 billion by 2030. To reach those levels, the use cases must shift from the current focus on episodic snapshots to continuous discovery. As TechRepublic reports, many organizations are seeing the future of process discovery and adjusting to focus on ongoing analysis to uncover, understand and take action toward an organization’s desired KPIs.

At its core, continuous discovery calls for and enables strict prioritization and scientific optimization of processes. Continuous discovery allows organizations to meet targeted processes and business goals.

Modeling real-world modern end-to-end business operations

While traditional process mining works well for analyzing and optimizing a single process in isolation, the reality is that modern business processes are highly complex and interconnected. Diginomica recently reported on a major advancement to address the shortcoming with the commercial introduction of object-centric process mining (OCPM), which enables the creation of a complete end-to-end map of operations.

OCPM overcomes the limitations of traditional process mining by capturing the relationships between objects. For instance, it can analyze and visualize the connections between all the objects involved in a transaction across processes and systems. A single transaction may trigger actions from a retailer’s order management application and their inventory management, procurement, supply chain, and production processes. Still, it wasn’t easy to track activities across the entire workflow.

The introduction of OCPM offers a fuller, more holistic, and more comprehensive view of business operations. The capability moves us closer to delivering an accurate system of record for work.

Alt-Tab … to infinity and beyond.

Most enterprise applications were not designed to connect, forcing employees to operate in ‘swivel chair’ roles while they wrangle data from multiple applications and submit it to other systems. A Harvard Business Review study measured the impact of the toggle syndrome at work.

The average user working in finance, HR, supply chain, recruiting, and inventory management toggled between apps and websites nearly 1,200 times daily. Assuming two seconds per switch to adjust, people in these jobs spent under four hours a week reorienting themselves after toggling to a new application. Over a year, that adds up to five working weeks, or 9% of their annual time at work.

Simulate over estimate

Computer Weekly reported that Abbyy updated its core Timeline product to identify automation opportunities 80% faster and speed process redesign by 30%.

Timeline 6.0 introduces a new analysis module called Simulation. Using the possibilities of process simulation allows you to experiment with process performance by altering the number of transactions initiated per unit of time, varying processing times, or available resources. The feature will enable you to simulate potential changes in processes complexly and evaluate the impact of these changes on the entire business process.

Given the market excitement, it is not surprising that IDC affirmed the growing use of process mining and stated it was the highest-growing subset of the intelligent process automation market, with a 2022-2026 CAGR of 51% and revenues reaching $3 billion in 2026.

Start now, think big, go fast

As companies strive to reduce costs and modernize practices in a challenging economic environment, a complete understanding of how work is conducted is required to make significant operational improvements. Complex change is even more difficult without an accurate view of the current state.

If you want to learn more about how work intelligence helps you win in the market and delivers operational excellence to the enterprise, let’s talk.