Build an organization that can survive the challenges you face today
GenAI, tariffs, wildfires and supply chain disruptions arrive faster than your plan updates itself. You fix one problem, only to have its sibling reappear somewhere else. It’s whack-a-mole. Instead of applying band-aids one at a time, I help you fix the system that keeps creating the problems. Surprises will still come. The goal is to handle them without a crisis.
Common situations
“Our strategy doesn’t survive contact”
The plan took over a year to write. Six months later, it’s out of date. It doesn’t matter what happened. Taking a year to create a plan doesn’t work now, and it never did.
“We have a strategy. Nobody is acting on it”
You announced the strategy. Months later, it still isn’t being acted on. Without clear priorities that everyone agrees on, people work on whatever they think is urgent.
“Teams are pulling in different directions”
Everyone sees the same strategy with different eyes. Each department finds its own way to “follow” the strategy.
“People are afraid”
People fear that GenAI will replace them. Some won’t touch it. Under pressure to adopt it, others churn out so much stuff that it causes problems elsewhere. Your best people look for the exits.
“We’re using AI, but can’t show it’s helping”
The board, an investor or a vendor pushed for it. A miracle has been promised. People produce more output. Too bad you can’t see more value.
“I’m the last to hear about problems”
Every status report says “all good” or “we’re on track”. The people on the ground know it’s not “all good”. By the time the real news reaches you, it’s late and hard to fix.
Working harder won’t fix it
These problems aren’t confined to software development. They appear anywhere that humans work together: software development teams, a 40-person engineering firm, hospitals, law firms, colleges and government departments. Most of your people are working hard and doing their best. The problem isn’t the people. It’s the system they work in.
W. Edwards Deming said it best: “A bad system will beat a good person every time.” More meetings or a new tool won’t fix a system problem.
Solving a problem feels good, until it comes back somewhere else. In the Canadian criminal justice system, when cases run past their time limit, the accused’s rights have been violated and the case must be thrown out. The obvious solution is “hire more judges”. When I looked at the whole system, I found that most of the time is spent waiting between steps. Hiring more judges is the most expensive way to “fix” the waiting. In most workplaces I study, work items spend 80-90% of their time waiting between steps, whether it’s a new feature waiting for user testing or a decision waiting on a busy manager’s desk. Adding more people or GenAI to the wrong step just makes the waiting worse.
“A bad system will beat a good person every time.”
What resilient organizations do
Finding the underlying problems improves the system. Building resilience takes more:
Work towards a common goal
Everyone understands the vision and strategy the same way. We know this is working when people agree on decisions and priorities across departments.
Get feedback early and often
Get direct feedback from the people who use the system. More frequent feedback means more opportunities to adjust.
Try small changes you can undo
A small experiment shows what works before you bet big.
Keep some spare capacity
A team that is 100% busy can’t respond to anything new. Spare capacity keeps work flowing when surprises arrive.
Decide close to the work
Leaders provide the direction and boundaries. The people on the ground make day-to-day decisions without waiting for approval.
Hear bad news fast
Bad news doesn’t get better with age. In a workplace where people feel safe, raising red flags early is easier.
When people are afraid
One of the biggest messages I’ve heard this year is that people are afraid. Will I be replaced by AI? If that happens, how long will it take to find a new job? People who are afraid protect themselves. They hoard information, bury problems, avoid risks and wait to be told what to do.
Under pressure to show productivity gains from AI adoption, people do what they can to demonstrate “productivity”. They use GenAI to churn out volume, because they think that’s what’s expected.
Whether people hide or churn out volume, nothing meaningful changes. And your best people don’t wait. They have options, so they leave.
Is GenAI paying off?
Use GenAI in the wrong place, and it creates waste on an industrial scale, faster than anyone can check it. Picture a slide deck full of AI-generated images that don’t make sense. The person who created it is proud, because they used a lot of AI. That deck is a work-shaped object: it looks like work, but it delivers nothing. Worse, if someone else needs to read it, it wastes their time too.
GenAI can be useful, but it’s not the magic bullet claimed by the people who sell it. Before you invest more, you need to measure how your system works today, and then see the impact of these tools, both on the work and the people doing it.
Are you using GenAI in the right place?
Some work goes faster with GenAI. Some goes faster but with lower-quality results. Some work shouldn’t exist at all, and doing it faster is still waste.
Do you know what happens downstream?
Faster work on one task can create new problems further down the line. GenAI writes code faster, but the code still waits for a person. Only a person can decide whether it’s the right thing to build. The same happens outside software. When GenAI churns out more reports, someone later has to check them for usefulness and accuracy. Are you watching for it?
Is it delivering the value you expected?
Measuring tool use doesn’t tell you whether the work was valuable. Making the wrong thing go faster is not productivity.
It feels like AI adoption is repeating the mistakes of failed IT projects such as the Phoenix pay system:
- Changes are made one department at a time, and nobody looks at the whole system.
- Nobody agrees, before they start, how they’ll know it’s working.
- Nobody goes back to check the benefits that were promised.
These are all system problems.
How this work unfolds
A free call
30 to 45 minutes. We talk about what you want to achieve, how you’d measure it and what it’s worth to you. If I can’t help, I’ll tell you.
A strategy session, when it’s needed
Some problems are bigger than one conversation. If yours is one of them, I’ll suggest a paid session: one to two days inside your organization, looking at how the work actually flows. You get a summary, my recommendations and a proposal for the next steps. Even if we don’t work together, you can use the next steps to start on your own.
The work
We start by making sure everyone shares the same understanding of the vision and strategy. Then we look at the whole organization, pick a few measures that matter and start running small experiments. Some experiments fail. A failed experiment still shows us how the system behaves. Sometimes the best fix doesn’t involve GenAI at all.
Business strategy workshop
Two to three days with your leadership team and people from the front line. We work out where you really are and what to tackle first. Strategy that isn’t grounded in the reality of the people doing the work is wishful thinking.
A three-month start
We pick two or three measures that match your problems. For example, are day-to-day decisions following the strategy? Is GenAI improving results, or just adding volume? Then we run the first experiments together and decide what to keep. By the end, your people can run the next one without me.
Ongoing engagement
A few days a month. I work alongside your leaders and teams. As your people take over, I step back.
About me
Earlier this year, GenAI helped me design a set of experiments for my business. They looked like a real plan, complete with target dates. Then they sat out of sight, and I forgot about them. When the dates had passed, GenAI told me the experiments had failed. None of them had ever run.
GenAI is very good at producing work-shaped objects: things that look like work but deliver nothing. I help you tell whether something is a real improvement or just a false promise.
I’ve run Agile Pain Relief for over 16 years and trained over 8,000 people. I read the research, so you don’t have to rely on vendor claims. Before you make a change, I look at the whole system to see where it’s likely to lead.
Recognize these?
Leadership said they had a plan
I worked with one client for over a year and never saw the strategic plan. Stakeholders kept changing the team’s direction, and work waited months for a steering committee. We set up a short meeting every six weeks. The stakeholders and the people who set the team’s priorities decided together what came next. It’s not perfect, but most decisions now get made without waiting for a steering committee.
Why does everything take so long?
Using public court data, I drew the stages a criminal case goes through. Four of the nine stages are mostly waiting. The same picture works for a hospital, a planning department or a software team.
When your key business assumption changes overnight
In 2024, the federal government cut international student permits by 35%. Ontario colleges that had just finished six-year plans found them out of date at the stroke of a pen. Most never updated them. The one college that reviewed its plan regularly and published its progress was set up to change direction.
Common questions
I can’t help organizations that aren’t interested in making deeper changes. I won’t help organizations that are trying to replace people en masse with GenAI.
No. After an initial ramp-up, most engagements are a few days a month until your team is self-sufficient. We know you’re self-sufficient when your organization is designing and measuring its own improvements.
Yes. If your team needs training rather than consulting, see private training.
No. Most of my background is in software, but the same problems show up anywhere work waits in a queue. Code waiting for review and a contract waiting for a partner’s signature are the same problem.
No, and be wary of anyone who says they can. What I can do is help you respond faster when it arrives.
Yes, although I can’t make the uncertainty go away. What helps is being honest about what you know and what you don’t. Then involve people in small, visible experiments, instead of announcing a big change from above or pushing AI on them. People who have a voice in the change are far less afraid of it. Further, don’t assume GenAI can replace people. It changes work, but so far it can’t replace taste and human judgment.
There are no miracles here. We make one change in one area, check the result, then pick the next. You should see the first useful evidence within two to three months, such as decisions that no longer wait for you, and a clearer view of what’s working.
My goal is that your team keeps improving without me, or any other outsider.
What people say
I’ve had a fair amount of success thus far introducing and implementing the concepts at the agency I work for. … We identified quite a few issues with our systems within the first couple of days and are now radically overhauling how we assign budgets to projects.
Mark is a good facilitator who is honest and understanding about the technical and organizational challenges.
I loved how interactive and applicable it was, especially for myself outside of the software industry. … I am excited at how it can improve the value we offer to clients at my organization.
Mark is very knowledgeable on the subject and always had good arguments to overcome the “we couldn’t do this in our organization”.
If nothing changes, the next crisis arrives and makes all the existing problems worse. In a software company, that might be a growing GenAI bill while quality drops. Outside software, the list of challenges keeps piling up; soon it will reach the ceiling.
Picture teams that respond to surprises without waiting for you. They tell you what’s really going on and find their own improvements. They understand the strategy so well that they can explain it better than you can.
You set the direction. They fix the problems, or ask for help when they need it.
Ready to build an organization that doesn’t need a hero? Let’s talk it through.
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