Tasks, Processes, and Journeys (oh my!)

"We cannot solve our problems with the same thinking we used when we created them."
— Professor Albert Einstein

The swirling maelstrom of thought leadership about our GenAI revolution sometimes misses the granularity of business transformation that these tools can bring. In this week's post, I want to create some simplicity on how to think about these granular transformational elements. Like in particle physics, our society has come a long way in understanding how 'work' gets accomplished within organizations over the past 125 years. To truly harness the potential of GenAI and associated tools, we must adopt new ways of thinking about work, much like how Einstein's theories revolutionized our understanding of the physical world.

This post is going to be a fundamental first-principles post – those of you with strong backgrounds in operations design and transformation, please forgive the oversimplifications and any omissions contained here.

What I want to do today is three things:

1. Introduce a stylized history of how we went from thinking about three levels of 'work' - from tasks to processes to journeys.
2. Consider the 5 forces unleashed by these new tools and ways of working
3. Set up our future conversation about the impact on business models and target operating platforms.

3 Levels of 'Work' in an Organisation

Dr. Ernest Rutherford transformed our understanding of atomic structure in 1909, moving from the solid spheres of the ancient Greek philosopher Democritus. Niels Bohr further refined Rutherford's model by introducing fuzzy indeterminate electron 'orbits', separated by specific energy 'quanta' between these orbital levels.

Just as these models revolutionized physics over the past 125 years, new models have transformed our understanding of 'organizational work':

Tasks

Frederick Taylor and Frank & Lillian Gilbreth pioneered Scientific Management in the early 20th century, focusing on tasks—the individual actions required to achieve a small objective. Taylor's work on tasks involved standardizing and perfecting individual actions by stripping away unnecessary and inefficient elements. In today's world, a task could be defined as precisely as 'writing a marketing email.'

Processes

By the mid-20th century, Total Quality Management (TQM) emerged with a focus on end-to-end process optimization. Processes were defined as the aggregation of tasks into a linear flow of work (i.e., workflow) from task to task. TQM emphasized incremental continuous improvement across these sets of tasks by focusing on customer satisfaction, process optimization, and waste reduction. More recently, disciplines like Six Sigma and Lean Operations drove even better incremental optimization. For instance, instead of just 'drafting an email,' a process description might be 'executing a marketing campaign.'

Journeys

At the dawn of the 21st century, the concept of 'work' expanded to be defined not by internal processes but external customer journeys. These journeys represent the end-to-end experience of a stakeholder interacting with an organization. Unlike tasks and processes, the journeys' perspective takes an outside-in view, focusing on customer needs, emotional engagement, pain points, and interaction preferences.

'Service Design' has become a catchphrase for methods that emphasize the design and reimagination of a company's delivery of these customer needs. Instead of just executing a campaign process, a new service design might involve reshaping 'how a consumer goes from first brand discovery to repeat purchaser.'

The 5 Forces of LLM, Machine Learning, and Agentics

Over the past century, tasks, processes, and journeys have defined how organizations deliver value. From Taylor's stopwatch to Service Design's customer-centric lens, each era brought tools to optimize work.

Enter generative AI (GenAI) and large language models (LLMs)—technologies that don't just optimize but fundamentally reshape work at all three levels. Unlike past automation tools, GenAI combines creativity, reasoning, and adaptability, enabling it to augment human capabilities, automate repetitive tasks, eliminate inefficiencies, re-orchestrate complex workflows, and reimagine entire business models.

These five forces, sorted from least to most disruptive, show the enormous impact even in simple augmentation of basic tasks using these tools. Many companies are just at the nascent stages of deploying tools against high-value and/or repetitive tasks. Pilots of Microsoft Co-Pilot are now commonplace among the client companies I support.

Real-World Examples

Where companies haven't yet progressed to that early augmentation stage, straightforward 'use cases' can immediately catch senior leadership attention. For example, when getting ready to see a dear friend for dinner after a long gap, I used an LLM Deep Search agent to tell me about the business they now help lead. Over a chicken shish, I interjected, 'By the way, did you know your consumers really dislike X in your current service provision? People online say that the equipment provided is a piece of junk.' Not only was my friend shocked I could know something that specific about their business execution, but they immediately followed up with an even more precise prompt.

We also see highly impactful examples of how process automation may drive impact through AI tools. Researchers from the University of Zurich conducted a recent covert experiment on Reddit to investigate how AI-generated comments could influence human opinion. The findings revealed that AI responses were between three and six times more persuasive than those made by humans. This study highlights the potential of AI to mimic human behaviour and influence opinions more effectively than any human customer service agent.

Even with these powerful examples of high-value task augmentation and process automation, the real promise lies in the re-imagination of whole customer journeys based on these technologies.

Much has been made recently of start-up technology SaaS companies who have achieved $10M+ in ARR with barely any full-time employees. Companies like Lovable, an AI-driven SaaS startup, achieved a reported $17M in annual ARR with only 15 employees, demonstrating how AI can reimagine customer experiences and enable scalability with minimal hiring. Similarly, Anyword reached a reported $10M in annual ARR with 50 employees, using natural language processing and predictive analytics to deliver targeted campaigns and drive growth without requiring a large workforce.

Where Are We Heading?

The operational transformation basics this post describes are fundamental to how we will change how work gets done; but, they are insufficient in understanding how our industries and our world will be transformed over the coming months, years, and decades. Among the industries I work in most, the shift of revenue and profit pools is going to be profound. I will argue in coming posts that the shift of revenue and value will at least match if not exceed what we saw as industries 'went digital' from 2000 to 2020.

My fear is that many companies will fixate on the short-term efficiency and effectiveness created by manually augmenting tasks and processes and finally achieving basic automation in a few highly repetitive tasks and sub-processes. I can imagine that many of these short-term benefits will be eroded away quickly as competition commoditizes these benefits away in everything from accounting through media to telecommunication services.

In short, the speed of commoditization may be just as fast if not faster than the median producer in those sub-industries benefits from these tools. Just as we saw with 'digital', these firms will work extremely hard to – at best – standstill in relative terms. This relative stagnation will take place even as the absolute size of their overall industry revenue and profit pools compress quickly.

Indeed, these narrow lever-focused companies will miss the much more fundamental re-imagination of customer journeys that these new tools help enable. It will be this re-imagination where value will be created and defended as business models shift and entire elements of the customer proposition are re-thought.

Again, I hope everyone is finding these thought pieces helpful as we navigate together some fundamental questions about the new world we inhabit.