Your business runs on processes. How you recruit, onboard, and train new employees, for example, is defined by the processes, subprocesses, and tasks that make these actions a reality. And processes extend to every area of your business. It’s how your products and services are sold, made, packaged, priced, shipped, delivered, invoiced, and inventoried. It’s how you invoice customers, pay suppliers, cash checks, publish reports, change production, maintain equipment, upgrade software, and, obviously, everything else that makes your business go.
Every step that makes up each individual process is important to not just delivering the end result, but in the quality, risk, cost, speed, and other attributes they introduce into your business. Therefore, having a deep understanding of your processes is critical to improving the quality, risk, cost, speed, and other attributes of your business. And, any business transformation requires first understanding what it is you’re expecting to transform. You must decode the work that’s being done today to understand what to improve, automate, or optimize tomorrow.
But how do you uncover the details that make up your business processes?
Most businesses, especially those of enterprise scale, don’t truly understand how their processes work on a granular, day-to-day level. This is at the level of how workers, applications, and data interact. The traditional methods of understanding processes are process mapping, process mining, and process discovery.
- Process Mapping is a manual method for documenting processes. Teams of consultants interview and monitor workers as they track a process from start to finish. It’s slow and expensive, and the sample size is limited and incomplete, especially for larger businesses.
- Process Mining is a back-end, software-centric technology that records the narrow, step-by-step workflow based on user interaction with specific systems. It requires access to application log files, but it’s limited in coverage because it misses steps performed in separate applications or applications (like email clients) that do not produce log files.
- Process Discovery is a modern alternative to process mining. It tracks workflow at the software user interface level, no matter who performs the task or which application is used. It is good at capturing discrete sub-processes, but has trouble scaling because it requires a manual evaluation of the results.
Each of these traditional methods return an incomplete view of processes and a snapshot of how the process was executed at a single point in time. Manually monitoring a process will undoubtedly disrupt and alter how workers perform that process. You do things differently when someone is looking over your shoulder. Application log files can be captured automatically, but they miss process steps performed manually or outside of a limited set of applications. And, manual process mapping and evaluation methods can show what happened today, but that data is then stale tomorrow.
The pressure is on enterprises to become more data-driven and less reliant on intuition and incomplete, siloed data. We live in an always-on, connected world, yet businesses make billion-dollar decisions using estimates and gut instinct. When it comes to business transformation and the lack of accurate, current, and complete process data, it’s no wonder McKinsey & Company found that just 14% of business transformations return any sustained performance improvements and 70% of enterprise-scale change programs don’t reach their stated goals. The result of that failure is $900 billion in wasted effort.
The traditional methods of understanding processes leave businesses struggling to paint a complete picture of how processes are actually being run. In order to make effective decisions, you need 100% of your process data at your fingertips, whenever you need it. Not just a snapshot, but complete data. Not from last year, but from today. Not with gaps, but capturing every discrete step along the way.
The data also must provide granular process details, down to time durations, frequencies, and the people and roles involved. It must provide the metadata to reveal how identical processes are completed differently across regions, teams, or applications. And, it must allow for drill-downs into the screens, data fields, and actions to clearly highlight (or rule out) opportunities for automation and process redesign.
Process intelligence is the automatic and continuous acquisition of process data at scale across any system in your enterprise. It provides clear and accurate visibility into the current state of your organizational processes to improve business process automation, digital transformation, and enterprise optimization. Process intelligence helps you understand today, so you can plan for tomorrow.
Process intelligence finally allows the traditional guessing game of process understanding to be replaced with a fast, accurate, data-driven alternative.
Process intelligence uses AI and computer vision to automatically create a detailed blueprint of the digital processes across all applications and departments, and across your entire enterprise. It does it without disrupting workers or the process, and can automatically create detailed process definition documents (PDD). By capturing this process data at scale and providing the details needed to understand it, you get instant visibility into the context and meaning behind your process data.
Process intelligence empowers you to then utilize your process data to improve every initiative and every decision. By collecting, aggregating, and cleaning this process data, you’re left with a centralized system of record for work.
This process data nirvana — real-time, comprehensive, usable — was not technically or economically feasible…until now.
Process intelligence finally allows the traditional guessing game of process understanding to be replaced with a fast, accurate, data-driven alternative. In turn, it makes your transformation and process optimizations initiatives also fast, accurate, and data-driven. Using process intelligence lets you respond more quickly to internal and external pressures, and empowers your teams to make better decisions in real-time.
More specifically, process intelligence brings process data to every worker, interaction, and decision. By adding human-in-the-loop functionality and data agency, your workers can use process intelligence data when and where they need it. By integrating process data into your existing data landscape, you can eliminate gaps between existing systems, processes, and customers to accelerate your transformation initiatives. It also streamlines automation efforts and the creation of bots by providing all essential elements necessary.
At the most granular level, process intelligence reveals exactly which tasks employees are spending time on within a particular application. This allows you to focus on specific segments of the process that could return the most value, impact, or time through redesign or automation. If, for example, employees are spending an inordinate amount of time in a text box on a particular screen, process intelligence will help you determine if you can drive text entry standardization through a drop down box, or even if that text entry is required at all.
Process intelligence lets you respond more quickly to internal and external pressures, and empowers your teams to make better decisions in real-time.
Process intelligence is the data enterprises need to fuel intelligent automation, value engineering, process redesign, system optimization, and employee experience. It’s also used to improve compliance, expand governance, and improve operational efficiencies across the enterprise.
Enterprise transformation efforts frequently fail because of the simple magnitude of the impacted processes. You’re trying to produce change on an enterprise scale using a snapshot of data that cannot possibly reflect the realities of the actual process. But process intelligence changes your perspective by giving you the detailed process data necessary to see how your decisions will impact your business.
Process intelligence goes well beyond traditional process mapping, mining, and discovery methods in six essential ways:
1. Scalability. Process intelligence quickly captures the granular detail in all business processes across your organization so you can find those improvements that provide the most impact.
2. Accuracy. Process intelligence combines cross-application data collection and AI modeling to provide a level of data-driven detail that allows you to confidently make strategic decisions for the most impact on your business.
3. Speed. Process intelligence eliminates slow, manual steps, making it up to 90% faster than traditional methods, and improving your time-to-value and return on your digital transformation investments.
4. Unbiased. Process intelligence uses intelligent, automated, and non-intrusive business process capture to eliminate bias or errors of manual capture, and enables workers to continue without influence or distractions, adding accuracy to avoid the rework that slows digital transformations.
5. Continuous. Process intelligence eliminates small sample sizes and estimations to continually capture process variances that happen across different shifts, locations, roles, and more, helping you refine or tailor processes for unique needs.
Of course, we believe FortressIQ Process Intelligence is the best way to capture these benefits. Our platform offers accuracy and insights unattainable with traditional methods and creates a system of record across your entire enterprise. The result is better, faster decisions on process automation, digital transformation, compliance improvements, and more.
Jon Knisley helps companies leverage process intelligence to jumpstart and scale their automation and transformation programs. He is currently FortressIQ’s Principal for Automation and Process Excellence and can reached at firstname.lastname@example.org.