Top-Down vs. Bottom-Up: Where to Begin Your Process Transformation Journey

Developing a deep and detailed understanding of your business processes lets you root out inefficiencies, double down on operational excellence, and make better, more informed decisions to reach your goals. But simply mining system log files misses the details in every process, while deploying consultants to map processes takes time and disrupts operations. Instead, intelligently decoding how your people and processes really work, across systems and screens, and across your entire business, is a better approach.

Capturing process intelligence to understand business processes has traditionally been tough to obtain because the methods have been manual. The drawback is that it results in static, incomplete process data. Today’s technologies, which evolved from these traditional methods, offer an automated and intelligent approach that’s both faster and captures more detail. 

Here’s how process insight capture has evolved:

  • Process Mapping is the traditional, human-based route where business analysts and consultants interview and look over the shoulders of your workers. It’s slow and expensive, the sample size is limited and incomplete, and it can’t realistically cover processes across the entire organization.
  • Process Mining is a back-end, system-centric approach that captures a narrow, step-by-step workflow based on how users interact with specific systems. This method requires access to log files, which limits coverage. It also misses tasks like data collection, calculations, or other steps performed in separate applications.
  • Process Discovery is a modern alternative to mining. It tracks workflow at the UI level, no matter who performs the task or which application is used. It excels at capturing discrete sub-processes, but has trouble scaling because it ultimately requires human evaluation of the results.
  • Process Intelligence advances process discoveryby using computer vision and Artificial Intelligence (AI) to uncover actionable process insights at enterprise scale. It has the speed and coverage to capture, record, and analyze granular steps in complex use cases, plus adds intelligence to quickly identify new opportunities.

This spectrum of process insight techniques is referred to as a top-down manual approach, versus a bottom-up intelligence-driven approach. They all help you gain a better understanding of processes, but the bottom-up approach offers more granular insights, faster and across a wider range of processes. The result is more business impact in less time.

Choosing an Approach to Gathering Process Insights

If you have process insight experience, you may lean towards combining multiple approaches to address specific requirements. But if you’re tackling a project for the first time, it can be difficult to determine the best approach. 

A top-down manual approach adds the perceived expertise and guidance of a team of consultants. That can be helpful but adds more cost and time by a few orders of magnitude. On the other hand, a modern bottom-up approach offers deeper insights and faster results but puts the decisions in your hands.

So, the question is, do you take a bottom-up or top-down approach?

Top-Down Misses the Detail

Top-down process mining technologies piece together a process within a single system, but since they do not capture granular user level activity, they don’t capture all the key steps of users or systems. For example, process exceptions and variations are not reliably identified because they may involve activities outside the analyzed system.

Additionally, enterprises often run hundreds of applications. Many of those—including Excel and common email clients—don’t generate usable log files. So, any use of those tools will not be captured, and the resulting process maps won’t represent the complete business process. The missed steps then aren’t included in automation efforts, resulting in costly rework once deployed.

Bottom-Up Provides More Insights and Speed

In contrast, process intelligence and process discovery technologies capture detailed user activity across all systems and tools, covering every granular step, including task interdependencies and connections. There is no need to access APIs or log files to create the process maps, which speeds the entire project, and the more complete insights keep you from automating broken or inefficient processes. Analytics can also quickly compare processes and system usage across teams and tasks.

Speed is what really separates the top-down and bottom-up approaches. You can expect to receive business value in weeks with Process Intelligence instead of months with Process Mining. 

  Bottom-Up
Process Intelligence
Top-Down
Process Mining
ACCURACY
Completeness
Full capture of sub-process activity and variations Limited view of end-to-end functional workflows
SCALE
People & Process Coverage
Full coverage across all systems and teams Limited coverage to systems with log files
DETAIL
Degree of Specificity
Level 5 step-by-step process and sub-process details Level 3 general workflows
SPEED
Time to Value
Weeks to deploy to desktop sensors and collect data Months to integrate back-end systems and map data 
EFFICIENCY
(reduced rework)
Granular activity data is comprehensive and actionable System-only data leaves process gaps

 

Start at the Process Itself

If you are exploring process insights for the first time, Process Intelligence is the logical starting point given its more comprehensive view of operations. It offers a faster time to value, takes less IT resources since you are not integrating with APIs or capturing log files, and is substantially less expensive and disruptive than unleashing a team of consultants into your operations.

As you eventually dig deeper for process insights, Process Mining could complement Process Intelligence, however. Combining both approaches provides the most comprehensive insight on the implications of a process. Interested in how FortressIQ provides process intelligence quickly and efficiently? Read our solution brief to see how you can get started.

Together, Humans and Software Agents Drive Enterprise Automation

“What is the calculus of innovation? The calculus of innovation is really quite simple: Knowledge drives innovation, innovation drives productivity, productivity drives economic growth.”

—William Brody, Scientist

 

Every company – no matter what size – knows that in order to remain competitive, you have to embrace change. Massive economic shifts tend to drive change more quickly and significantly, and this has never been more true or urgent. No matter what stage of your digital transformation journey you are in, the current environment is likely accelerating your process optimization initiatives. Additionally, the traditional emphasis on front-office activities need to be reevaluated. Most transformation programs in the last decade have focused on customer experience, but today, indicators suggest the emphasis moving forward will shift toward back-office operational excellence in departments including finance and accounting, HR, and procurement.  

From the New York Times to the Wall Street Journal, much has been written about the potential permanent job loss from the drive for increased automation in the enterprise. Experts predict up to 800 million jobs worldwide could be lost to automation by 2035. Enterprise veterans know, however, that the human element will never go away – it will merely change. While these headlines spark a lot of article views, they fail to address the positive opportunities and changes we will see in the workforce as a result of innovative automation.

Improved Employee Experiences

When done properly, automation should support and complement human activity. It removes the low-value, manual and tedious tasks that consume a majority of our work hours, letting employees focus on higher-value activities. Identifying areas where employees can add value by applying their skills to more strategic work not only increases productivity, but also overall employee happiness. The shift away from manual tasks has been going on since the Industrial Revolution, and HR departments are hyper aware that retaining employees is more cost-effective. A recent study by Employee Benefits News states the average cost of losing an employee is equal to 33% of their annual salary.

Increased Need for a Human-Centric Approach

When first approaching automation projects it’s important to validate the tasks and processes identified to make sure they are good candidates for RPA. Those who have been involved in enterprise workflow programs know the golden rule that there is nothing worse than automating a bad process; it simply magnifies the inefficiency. On the flip side, automating a good process has the advantage of magnifying the efficiency. Without the use of modern discovery techniques to accurately document the current state and identify process variations, it’s very difficult to distinguish a good process from a bad one. Automated discovery tools like FortressIQ surface the insights of tasks and processes at a detailed level previously unattainable with more traditional methods. Once this data is gathered, however, it ultimately needs a human element for success. Whether internal or external, process optimization experts, business analysts, automation SMEs, developers, project managers, and others will play a crucial part in successful planning and execution.

Enabling the Citizen Developer

The future of automation will see a shift from a more traditional top-down “you must automate” approach led by management to a bottom-up “how can I be more efficient” employee-driven trend. Bots will be packaged up with standard office apps and services to increase usage across organizations. Coupled with no-code offerings this will allow anyone – no matter what department or role they have at the company – to easily automate a tedious task or portion of their job without engaging IT. Imagine if sales executives could spend less time updating CRM systems, sales operations could auto-generate pipeline reports, product managers could consolidate and group customer feature requests from various channels, the finance and accounting department could eliminate copying and pasting of PO numbers into multiple systems, and if call center and support employees could auto-fill customer ticket information, among countless other examples to make life easier for employees. Putting the power of this technology into the hands of your workforce allows them to make data-driven decisions more quickly, increasing overall corporate performance. 

The future of automation will be a seamless blend of the next-generation workforce and software agents, including bots and assistive technology. Enterprises who determine how to successfully incorporate these capabilities will remain competitive and relevant. It will improve their organizations and accelerate the pace of innovation. For a jump start on your RPA efforts, check out our handy guide, “Should my Enterprise Automate That?” available here.