November 11, 2025

Designing Work to More Effectively Solve the Right Problems

1 hour 2 minutes

In this week’s edition of The Management Brief, Josh Howell, LEI President, and Mark Reich, LEI Chief Engineer Strategy, speak with Nelson Repenning, School of Management Distinguished Professor of System Dynamics and Organization Studies at the MIT Sloan School of Management. Nelson also is the co-author of There’s Got to Be a Better Wayi and the Co-Founder and Chief Social Scientist of ShiftGear Work Design, a consultancy that focuses on understanding the factors that contribute to the successful implementation, execution, and improvement of business processes.

This month The Management Brief is presenting theories that are guiding organizational transformations, including Nelson’s dynamic work design, an “anti-initiative” approach for redesigning work to solve the right problems effectively and, in doing so, increase productivity, profits, and associate engagement.

Dynamic work design helps organizations challenge the mindset that they can forecast and plan — budget, strategy, human resources, capital — with accuracy. Nelson’s alternative: “If we accept that the world is not perfectly predictable, we might go back and design some of our core processes a little bit differently to create an organization that not only plans but also is capable of learning from experience and adapting to the new information they get as they go.”

Dynamic work design is based on five principles:

Solve the right problem: This principle is “a charge to focus on bite-sized pieces of important problems and use structured methods, whether it’s the A3 or DMAIC or whatever your preferred version is to make sure that you actually solve that problem in a fundamental way,” says Nelson.

Structure for discovery: This involves configuring every job in the organization so that the individual doing the job learns the right lessons and can get feedback to adjust behaviors to do work in the right way.

Connect the human chain: “Let’s leverage the collective intelligence of the organization by making sure that problems quickly get to the person who is in the best position to solve them,” instructs Nelson. “So it’s essentially a charge to wire together the information flow so that knowledge about a particular issue gets to the right place and gets there quickly.”

Regulate for flow: This is a version of Toyota pull that involves making sure there is the right amount of work in the system to prevent “traffic jams” of work.

Visualize the work: This principle helps to apply visualization usually found in physical work to knowledge work, which frequently lacks such signals. “If we can create a kind of digital twin or radar screen ... so that we can see whether knowledge work is moving or not, it often unlocks a lot of that natural problem solving that you would get in other contexts if the work were a little bit more available to us,” explains Nelson.

Nelson described how the Broad Institute, a research organization dedicated to understanding the roots of disease and closing the gap between new biological insights and impact for patients, successfully applied dynamic work design in a knowledge-work environment to improve research grant workflows. The institute had one grant process that was particularly problematic, time-consuming, frustrated staff, and required workarounds.

Sheila Dodge, COO of Broad Clinical Labs, followed the dynamic work design principles in a direct manner and set clear targets: get grants approved in 10 days rather than the 20 or 30 days that it was taking. “They mapped the process pretty carefully so you could see all the steps that they went through. And then ... they created a really simple visual management system to plot how the work was flowing or track how the work was flowing,” says Nelson. Using a white board they depicted steps in the process, with a sticky note representing each grant moving through the process, which quickly revealed their poor design choices. They then reconfigured resources and the work started flowing dramatically.

The trio also discussed Nelson’s work relating to:

The efficacy of face-to-face communications: When designing processes for getting work done, face-to-face communications should in place where most helpful, such as where there is ambiguity or uncertainty that needs to be processed. “We have discovered that often a daily meeting can replace, if it’s well designed, hundreds of emails a day if you design the meeting [to] bring all the uncertainty into the meeting,” says Nelson.

Seagull management: This refers to the uncomplimentary behavior of managers who, when there is a crisis, “fly in like a flock of seagulls and then sort of poop on everything and then fly away.” Nelson says that “as leaders get more senior, they really underestimate the symbolic impact of their actions... The thing that people don’t understand when they get to those corner offices is that everybody is looking at them to try to figure out what behaviors are appropriate in this organization. They are the chief role model, whether they like it or not. And so I think as a consequence, with the best of intentions, leaders often have really pathological impacts on their organization.”

AI will change work dynamics: “There’s no question that AI is going to change our lives in very material ways,” says Nelson. “But I actually think it is going to put an even greater premium on the kinds of things that we collectively do... It’s best captured by one of my former students [who] said, ‘You know, there’s few ways to lose money faster than automating a process you don’t understand.’ I think that’s going to be very true in the machine learning AI-enabled world, and I think it’s going to put a real premium on understanding how the work actually gets done. And then using these new tools in very strategic ways.”

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By Lean Enterprise Institute

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