Leveraging Dynamic Work Design Should be Fundamental in AI-Powered ERP Transformations

Modern management has a fragility problem. By over-relying on fixed annual budgets and long-term rigid planning, organizations create fragile structures. These systems lack the flexibility required to withstand market volatility or supply chain disruptions, leading to operational failure when agility is needed most.When the market shifts, these rigid structures don’t bend; they break. 

When these rigid systems fail, “corner cases” – those unexpected, edge-of-the-map problems – don’t just remain outliers; they become the catalysts for organizational chaos. According to MIT Sloan professor Nelson Repenning and lecturer Don Kieffer, authors of “There’s Got to Be a Better Way,” the solution isn’t a “fad diet” of inspirational workshops.  

It is a fundamental shift in thinking about how best to optimize workflows for things like ERP automation and to make organizations more resilient in managing market dynamics. Dynamic Work Design is the methodology we have found most effective for our clients.  

The Trap of the Undocumented Workaround 

When a workflow isn’t designed to handle a business reality, positive or negative, motivated employees find their own ways to get the job done. However, these solutions are often private, undocumented workarounds. While a workaround might solve a problem in the short term, it creates a “human-made” corner case for the next person in the chain.  In fast-paced development environments, such cases are not well documented and rarely accurate in the larger context of the system design goals. 

These hidden fixes multiply until the entire system is a web of invisible dependencies. This leads to an organizational mindset that is continually in “firefighting mode.” This is where teams spend weekends solving avoidable problems while leaders push “pet projects” through an already clogged system.  As “hot-fixes” keep stacking, failures become harder to detect or explain. Eventually, the cost is no longer just technical debt, it manifests as delayed outcomes, inconsistent behavior, and a gradual erosion of client trust. When the system eventually breaks, individuals are blamed for failures that were permanent and unintentionally hidden into the workflow’s design. 

To break this cycle, it’s necessary to implement a strategic shift toward dynamic work design. This methodology moves away from rigid, static planning. Instead, it recognizes that workflow is a dynamic process of ongoing problem-solving. By aligning dynamic work design with the reality that daily operations are fluid, executives and managers can uncover these private workarounds and integrate them into a transparent, cohesive workflow. 

AI as the Engine for ERP Transformation Supported by Dynamic Work Design 

Today, the drive for a healthier organizational mindset often centers on Enterprise Resource Planning (ERP) transformations. When done correctly, AI systems that augment new or legacy ERPs, can revitalize ERP assets to effectively address workflow process gaps. Additionally, the AI system can ensure that new data can be connected to legacy data, documentation is maintained, and all of it follows business and security rules. The power of quickly addressing ERP workflow process gaps rests in delivering a single, flexible interface, with the added ability to store data in such a way that an AI system can combine it with ERP data to create seamless reporting of cost, expense, time and thus productivity. The cost of, and speed of, adding that flexible interface to the ERP is much easier to rationalize compared to individual customizations within the ERP for individual corner cases.  

AI systems can be configured and updated to augment legacy ERP implementations that will make it easier for end users to operate, while integrating new data sets with a central data store for reporting – while keeping faithful to all business rules, security rules and the business governance policies of the underlying enterprise software systems. All of this happens while the business is still working, collecting new and old data and providing new levels of actionable intelligence as AI-powered modules are added. 

AI-augmentation of an ERP can allow workflows to be more flexible than with legacy or recently purchased ERP platforms because all workflows must be carefully tested and planned ahead of time. The AI networks become the user interface and are flexible enough to be quickly reconfigured as needed. AI systems can allow workflows to proceed based on logical business rules which can be easily updated.  

Workflow Design is Critical to Success 

AI doesn’t automate manuals; it automates reality. To unlock the true potential of AI, executives must embark on what Repenning and Kieffer call a “journey of discovery.” This requires looking past idealized flowcharts to find the “shadow workflows” employees use to actually get things done. Only by surfacing these informal workarounds can leaders trade wishful thinking for an accurate “as-is” map of the organization.  

Once these gaps are identified, AI can be leveraged to mitigate future workflow workarounds. Instead of a static system that forces a user to find a shortcut, an AI-enhanced ERP acts as an intelligent UI. It can be modified to incorporate new processes while ensuring all business rules are maintained. By building these intelligent guardrails, the system adapts to the user’s needs in real-time, removing the incentive for employees to create the very workarounds that led to chaos. 

Transforming Chaos into Flow 

Kieffer and Repenning’s dynamic work design philosophy moves away from “big bang” changes toward incremental, scientific problem-solving through some core principles:  

Organizations must solve the right problem, and solve the problem right. Executives often hunt for “moonshots,” but massive transformation is usually fueled by small, tactical wins. The positive effects of small wins add up quickly. 

Leaders must structure for discovery. Many managers set goals without understanding the “day-to-day scramble” of their staff. By engaging in shared discovery leaders can see where their targets conflict with reality. 

It is vital to connect the human chain. Technology is often a poor match for complex human interactions. Rather than redesigning expensive software, focus on the handoffs between people. A huddle should be a short conversation focused on “what happens next” rather than a long slide deck. 

Organizations must regulate flow. An overloaded system is an unstable system. When you operate at 100% capacity, a single “stalled car” or corner case grinds numerous activities to a halt. Following the “airplane rule” – not starting more work until the system has the capacity to finish it – allows for better performance. 

Teams must visualize the work. If you cannot see the work, you cannot see the bottlenecks. Whether using digital tools or index cards and string, visual representations drive better decision-making. Fannie Mae famously cut their monthly book-closing time from 13 days to 6 by documenting their handoffs on a physical board with clothespins and string, forcing higher-quality conversations. 

The Path Forward 

AI-based ERP augmentation is the best transformation strategy because it establishes a foundation for continuous innovation. It provides a flexible, modular architecture where new AI capabilities can be plugged in as they become available, ensuring the ERP system – and the business – becomes more nimble, competitive and intelligent.  

An AI-driven ERP transformation embeds dynamic work design directly into the organization’s DNA. Instead of guessing how work happens, this process captures, documents and reshapes workflows in real time. This ensures that every update is fueled by actual business activity, allowing the company to operate with unprecedented speed, accuracy and security. 

About the Author: 

Ken Fischer is the CEO of Atigro, the proven ERP transformation firm that pairs its modular augmentation capabilities with AI-native frameworks. Atigro’s experience and capabilities generate the rapid development and provisioning of new enterprise software functionality that meets dynamically changing business processes.