Tag: Leadership

Why Curiosity Is the New Competitive Advantage

Imagine two managers sitting at their desks, both using the same AI tool.

The first asks it to write the same weekly report, just faster. Three hours saved. Nothing new learned. Box checked.

The second uses the AI differently. She asks it to analyze six months of data and search for hidden patterns. It reveals that half the metrics everyone tracks have no real connection to success. Two new questions emerge. She rebuilds the entire process from scratch.

Same tool. Different questions. One finds speed. The other finds wisdom.

This is the divide that will define the next decade of work.

For a long time, leadership revolved around structure and repetition. The best organizations built systems that ran like clockwork. Discipline became an art. Efficiency became a mantra.

Books like Good to Great showed how rigorous process could transform good companies into great ones through consistent execution. When competitive advantage came from doing the same thing better and faster than everyone else, process was power.

AI changes this equation entirely. It makes these processes faster, yes, but it also asks a more unsettling question. Why are you doing this at all?

Speed alone means little when the racetrack itself is disappearing.

Curiosity in the age of AI means something specific. It asks “why” when everyone else asks “how.” It uses AI to question assumptions rather than simply execute them. It treats every automated task as an opportunity to rethink the underlying goal. And it accepts the possibility that your job, as you currently do it, might need to change entirely.

That last part is uncomfortable. Many people fear AI will replace them. Paradoxically, the people most at risk are those who refuse to use AI to reimagine their own work. The curious ones are already replacing themselves with something better.

Many organizations speak of innovation, but their true values show in what they celebrate. Do they promote the person who completes fifty tasks efficiently, or the one who eliminates thirty through reinvention? Most choose the first. They reward throughput. They measure activity. They praise the person who worked late rather than the one who made late nights unnecessary.

This worked when efficiency was scarce. Now efficiency can be abundant. AI will handle efficiency. What remains scarce is the imagination to ask what we should be doing instead. Organizations that thrive will use AI to do entirely different things. Things that were impossible or invisible before.

Working with AI requires more than technical skills. The syntax is easy. The prompts are learnable. Connecting AI to our applications isn’t the challenge. The difficulty is our mindset. Having the patience to experiment when you could just execute. The humility to see that the way you’ve always done things may no longer be the best way. The courage to ask “what if” when your entire career has been built on knowing “how to.”

This is why curiosity has become a competitive advantage. The willingness to probe, to question, to let AI reveal what you’ve been missing. Because AI is a mirror. It reflects whatever you bring to it, amplified. Bring efficiency-seeking and get marginal gains. Bring genuine curiosity and discover new possibilities.

Here’s something to try this week. Take your most routine task. The report, the analysis, the update you’ve done a hundred times. Before asking AI to replicate it, ask a different question. What would make this unnecessary? What question should we be asking instead?

You might discover the task still matters. Or you might realize you’ve been generating reports nobody reads, tracking metrics nobody uses, or solving problems that stopped being relevant two years ago.

Efficiency fades. What feels efficient today becomes everyone’s baseline tomorrow. But invention endures. The capacity to see what others miss, to ask what others skip, to build what nobody else imagines yet.

The curious will see opportunity. The creative will see possibility. The courageous will see permission. Together they will build what comes next.

The tools are here. The door is open. Work we haven’t imagined yet waits on the other side. Solving problems not yet seen, creating value in ways that don’t exist today.

Only if you’re willing to ask better questions.

Photo by Subhasish Dutta on Unsplash – the path to reinvention

Seeing What Comes Next

The difference between reacting to the moment and preparing for it.

Most leaders spend their days responding. A problem surfaces. They fix it. A crisis hits. They mobilize.

Urgency crowds out importance. By Friday they’re exhausted from fighting fires they never saw coming.

This is leadership without anticipation.

Every action sets something in motion.

-Launch a product without considering support capacity, and you’ll be drowning in angry customers in three months.

-Promote someone before they’re ready, and you’ll spend the next year managing the fallout.

-Ignore the quiet signals in your market, and you’ll wake up one day wondering how you got disrupted.

Some outcomes can be seen in advance. Leadership is the discipline of noticing what’s coming and readying your team to meet it.

Wayne Gretzky once said, “I skate to where the puck is going to be, not where it has been.”Most leaders skate to where the puck was. They optimize for yesterday’s problem. They staff for last quarter’s workload. They strategize for a market that no longer exists.

Leaders who matter skate differently. They think past the first step and see how decisions unfold across time. When they make a choice today, they’re already anticipating the second and third-order effects.

They connect short-term actions to long-term outcomes, asking not just “Will this work?” but “What happens after it works?”

When you cultivate this habit of anticipation, something shifts. You stop being surprised by the predictable. You create space before you need it. You move with a quiet confidence that comes from seeing the terrain before you cross it.

Your team feels it too. It’s the difference between reactive and ready, between scrambling and intentional.

We can’t eliminate uncertainty. The future will always bring surprises. But we can change how we manage it. We can choose to be the leader who sees what’s coming rather than the one who’s perpetually caught off guard.

Dwight Eisenhower said, “In preparing for battle I have always found that plans are useless, but planning is indispensable.” Plans will change. They always do. But the act of planning, of thinking through trajectories, testing assumptions, and imagining scenarios, prepares you to lead when the moment arrives.

The leader who anticipates doesn’t wait for clarity. They sense it forming and courageously move toward it. They shape the path while others are still reacting to it.

Photo by Aleksander Saks on Unsplash

Bring Them On the Journey

You can tell people what to do, and sometimes that’s the right call. Yet, direction without participation creates compliance instead of commitment.

When people understand the purpose, see where they fit, and have a voice in the direction, they’ll take emotional ownership.

The best leaders invite that ownership by asking questions that open doors to insight. What are we missing? What would you try? Where do you see the risk? These questions are invitations to shape the work and the results.

When a product manager asks her team, “How would you approach this?” instead of presenting a finished plan, the solutions that emerge are sharper, and the team building them gets stronger.

Humans are built for both independence and belonging, desires that often pull in different directions. Wise leaders guide this tension well. They give people space to grow while connecting them to something larger than themselves.

To bring others on the journey is to build together. Growth is shared. Trust expands. When the path gets steep, they’ll keep climbing with purpose.

They remember the reasons, because they helped shape the path.

Photo by Powrock Mountain Guides on Unsplash – Unsplash has a ton of amazing hiking photos, mountain climbing photos, pictures of maps, legos, and winding paths. All would have represented the themes of this post admirably. But this photo caught my eye.

How do you see it connecting to this post? What makes this photo stand out? How hard do you think it is to hike across to that gleaming white mountain in the distance?

The Mirage of Strategic Clarity

Strategic Planning That Can Survive Reality

It was the second day of a two-day strategic planning retreat. Revenue projections stretched across the screen. The CFO walked through all the assumptions in his spreadsheet. Customer acquisition costs will flatten, churn will improve by two points, and the new product will capture eight percent market share within six months.

Everyone nodded along, acting as if these forecasts represented knowledge rather than elaborate guesses built on dozens of assumptions, any one of which could be wrong.

Three months later, a competitor launched an unexpected feature. Customer behavior shifted. The CFO’s projections became relics of a reality that never existed. The entire strategic planning process had been built on an illusion.

What we pretend to know

In his 2022 memo The Illusion of Knowledge, Howard Marks explored how investors mistake confidence for clarity. He began with a line from historian Daniel Boorstin:

“The greatest enemy of knowledge is not ignorance, it is the illusion of knowledge.”

Leaders face a brutal paradox. Boards expect forecasts. Teams want confidence. Investors demand projections. The machinery of leadership demands certainty.

So, we build elaborate forecasts and make decisions based on assumptions we know to be fragile. We treat detailed guesses as facts.

Physicist Richard Feynman once said, “Imagine how much harder physics would be if electrons had feelings.” Electrons follow discrete laws, unlike people. People innovate, resist, panic, and occasionally do something amazing nobody saw coming. Competitors behave differently than our models assume. Markets shift for reasons we never thought possible.

Marks describes forecasting as a chain of predictions. “I predict the economy will do A. If A happens, interest rates should do B. With interest rates of B, the stock market should do C.” Even if you’re right two-thirds of the time at each step, your chance of getting all three predictions correct at once is only about thirty percent.

Leadership forecasts work in a similar way. We predict customer adoption rates. If adoption hits those numbers, we’ll need a certain operational capacity. With that capacity, we can achieve specific margins. Those margins will attract investment.

Each assumption depends on the previous one. The chain is only as strong as its weakest link.

The tools we trust

Walk into any strategic planning session and you’ll likely encounter two frameworks treated as gospel:

-SWOT analysis (strengths, weaknesses, opportunities, and threats)

-SMART goals (specific, measurable, achievable, relevant, and time-bound).

Business schools teach them. Consultants recommend them. Leaders deploy them with confidence. Each relies on assumed knowledge that may not exist.

A SWOT analysis claims to know which possible developments count as opportunities versus threats. It’s a snapshot of assumptions masquerading as strategic insight. An opportunity exists only if you can identify it, execute against it, and do so before circumstances change. The framework provides no way of acknowledging uncertainty.

SMART goals often confuse precision with accuracy. “Increase market share” becomes “increase market share in the Northeast region from 12% to 15% by Q4 2026.” It sounds specific, and therefore rigorous. It’s easy to be precise about something unpredictable.

And how do we know a goal is achievable? We make assumptions about resources, market conditions, and competitor behavior, then write a goal that treats our assumptions as facts.

Both frameworks serve a valuable purpose. They force structured thinking. But they also seduce leaders into believing they know more than they do.

What should we do instead?

To be clear, this isn’t an argument for abandoning planning. Organizations need direction, priorities, and coordinated action. The question is how to plan in ways that acknowledge what we can’t know while still making decisive progress.

A better path involves changing how we plan and how we talk about the future.

Distinguish between direction and destination. Amazon knew it wanted to be “Earth’s most customer-centric company” without knowing exactly what that would look like in year ten. “We’re moving toward increased automation” carries more truth than “we’ll reduce costs by seventeen percent by Q3 2026.” The first creates direction. The second creates false precision.

Separate what you know from what you assume. Customer complaints increased forty percent this quarter. That’s knowledge. Saying the trend will continue is extrapolation. Predicting that fixing the issue will increase retention by five points is speculation. Present plans that show what you know, what you’re inferring, what you’re assuming, and what you’ll do if you’re wrong.

Build optionality into everything. Create strategies that work across multiple futures. Hire people who can do, or think about, more than one thing. Build modular systems with flexibility in mind. Create decision points where you can change course.

Use familiar tools differently. Run a SWOT analysis, then list three ways each opportunity might fail to materialize. Write SMART goals, then document the assumptions those goals depend on and how you’ll adapt if they prove incorrect.

Here’s a concrete example. You’re deciding whether to build a new product line. The traditional approach creates a detailed business case with market projections and revenue forecasts. You present it. People debate assumptions. A decision gets made.

An alternative approach defines what success means, then identifies what must be true to achieve it. You sort those conditions into things you can validate quickly, things you can validate over time, and things you can validate only much later. Stage investments to match the timing of the validations, rather than an arbitrary quarterly schedule.

The difference in these approaches is critical. In the first, the business case pretends to represent knowledge. In the second, it becomes a set of hypotheses to test over time.

The harder path

Amos Tversky observed, “It’s frightening to think that you might lack knowledge about something, but more frightening to think that, by and large, the world is run by people who have faith that they know exactly what’s going on.”

We select leaders for their ability to project confidence about an unknowable future. We reward decisiveness over doubt. Then we wonder why strategies fail when reality diverges from our projections.

Most of us live in this system. We’ve built organizations that demand the illusion of knowledge.

Real leadership creates organizations resilient enough to find answers as circumstances unfold. It builds teams that can adapt rather than simply execute a plan written many months ago.

When did you last change a forecast because reality diverged from your assumptions?

When did you last reward someone for identifying that a plan was failing?

Start small. Pick one decision where you can be explicit about uncertainty. Structure one investment to test assumptions instead of betting on a forecast. Have one conversation where you separate what you know from what you’re guessing.

Plan in ways that acknowledge uncertainty and position your organization to learn. Lead with confidence about principles while staying adaptable around specifics. Build organizations that can adapt when reality diverges from the plan.

Because it will. The measure of leadership lies in how well your culture can face that truth.

The CFO’s spreadsheet was never the problem.

The illusion that it represented knowledge was.

Photo by Michael Shannon on Unsplash

Strategy First. AI Second.

Eighty-eight percent of AI pilots fail to reach production, according to IDC research. Most fail because organizations chase the tool instead of defining the outcome. They ask, “How do we use AI?” rather than “What problem are we solving?”

A little perspective

I’m old enough to remember when VisiCalc and SuperCalc came out. That was before Lotus 1-2-3, and way before Microsoft Excel. VisiCalc and SuperCalc were just ahead of my time, but I was a big user of Lotus 1-2-3 version 1. Back then, everyone focused on how to harness the power of spreadsheets to change the way they did business.

Teams built massive (for that time) databases inside spreadsheets to manage product lines, inventory, billing, and even entire accounting systems. If you didn’t know how to use a spreadsheet, you were last year’s news.

The same shift happened with word processing. Microsoft Word replaced WordPerfect and its maze of Ctrl and Alt key combinations. Then the World Wide Web arrived in the early 1990s and opened a new set of doors.

I could go on with databases, client-server, cloud computing, etc. Each technology wave creates new winners but also leaves some behind.

The lesson is simple each time. New tools expand possibilities. Strategy gives those tools a purpose.

The point today

AI is a modern toolkit that can read, reason (think?), write, summarize, classify, predict, and create. It shines when you give it a clear job. Your strategy defines that job. If your aim is faster cycle times, higher service quality, or new revenue, AI can be the lever that helps you reach those outcomes faster.

Three traps to avoid

Tool chasing. This looks like collecting models and platforms without a target outcome. Teams spin up ChatGPT accounts, experiment with image generators, and build proof-of-concepts that fail to connect to real business value. The result is pilot fatigue. Endless demonstrations with no measurable impact.

Shadow projects. Well-meaning teams launch skunkworks AI experiments without governance or oversight. They use unapproved tools, expose sensitive data, or build solutions that struggle to integrate with existing systems. What starts as innovation becomes a compliance nightmare that stalls broader adoption.

Fear-driven paralysis. Some organizations wait for perfect clarity about AI’s impact, regulations, or competitive implications before acting. This creates missed opportunities and learning delays while competitors gain experience and market advantage.

An AI enablement playbook

Name your outcomes. Pick three measurable goals tied to customers, cost, or growth. Examples: reduce loan processing time by 30 percent, cut customer service response time from 4 hours to 30 minutes, or increase content production by 50 percent without adding headcount.

Map the work. List the steps where people read, write, search, decide, or hand off. These are all in AI’s wheelhouse to help. Look for tasks involving document review, email responses, data analysis, report generation, or quality checks.

Run small experiments. Two to four weeks. One team. One KPI. Ship something tangible and useful. Test AI-powered invoice processing with the accounting team, or AI-assisted internal help desk with support staff.

Measure and compare. Track speed, quality, cost, and satisfaction before and after. Keep what moves the needle. If AI cuts proposal writing time by 60 percent but reduces win rates by 20 percent, you need to adjust the approach.

Harden and scale. Add access controls, audit trails, curated prompt libraries, and playbooks. Move from a cool demo to a dependable tool that works consistently across teams and use cases.

Address the human element. Most resistance comes from fear of displacement, rather than technology aversion. Show people how AI handles routine tasks so they can focus on relationship building, creative problem-solving, and strategic work. Provide concrete examples of career advancement opportunities that AI creates.

Upskill your team. Short trainings with real tasks. Provide templates and examples in their daily tools. Make AI fluency a job requirement for new hires and a development goal for existing staff.

Close the loop with customers. Ask what improved. Watch behavior and survey scores, with extra weight on what people actually do, versus what they say.

Governance that speeds you up. Good guardrails create confidence and help you scale.

Access and roles. Limit sensitive data exposure and log usage by role. Marketing might get broad access to content generation tools while finance operates under stricter controls. The concept of least privilege applies. 

Data handling. Define red, yellow, and green data. Keep red data (customer SSNs, proprietary algorithms, confidential contracts) away from general public-facing tools. Yellow data needs approval and monitoring. Green data can flow freely.

Prompt and output standards. Save proven prompts in shared libraries. Require human review for customer-facing outputs, financial projections, or legal documents. Create templates that teams can adapt rather than starting from scratch.

Audit and monitoring. Capture prompts, outputs, and sources for key use cases. Build processes to detect bias, errors, or inappropriate content before it reaches customers.

Vendor review. Check security, uptime, and exit paths before heavy adoption. Understand data residency, model training practices, and integration capabilities. Consider making Bring-Your-Own-Key (BYOK) encryption the minimum standard for allowing your organization’s data to pass through or be stored on any AI vendor’s environment.

Questions for leaders

Which customer moments would benefit most from faster response or clearer guidance? Think about your highest-value interactions and biggest pain points.

Which workflows have the most repetitive reading or writing? These offer the quickest wins and clearest ROI calculations.

Which decisions would improve with better summaries or predictions? AI excels at processing large amounts of information and identifying patterns humans might miss.

Do we have the data infrastructure to support AI initiatives? Clean, accessible data is essential for most AI applications to work effectively. Solid data governance and curation are critical.

What risks must we manage as usage grows, and who owns that plan? Assign clear accountability for AI governance before problems emerge.

What will we stop doing once AI handles the routine? Define how you’ll reallocate human effort toward higher-value activities.

Who will champion AI adoption when the inevitable setbacks occur? Identify executives who understand both the potential and the challenges.

What to measure

Cycle time. Minutes or days saved per transaction.

Throughput. Work items per person per day.

Quality. Rework rate, error rate, compliance findings.

Experience. Customer effort score, employee satisfaction, NPS.

Unit cost. Cost per ticket, per claim, per application.

AI is the enabler

Strategy sets direction. AI supplies leverage. Give your people clear goals, safe guardrails, and permission to experiment and fail along the way.

Then let the tools do what tools do best. They multiply effort. They shorten the distance between intent and execution. They help you serve today’s customers better and reach customers you couldn’t reach in the past.

The question isn’t whether AI will transform your industry.

The question is whether you’ll lead that transformation or react to it.

Which will you choose?

Photo by Jen Theodore on Unsplash – I love this old school compass, showing the way as it always has. The same way a solid strategy and set of goals should lead our thinking about leveraging the latest AI tools.

The Gift of Grace

There are times when we are firmly in the right. The facts are clear. The other person made a mistake or caused harm. In that moment, we face a choice. We can leverage our position of strength and press our advantage. Or we can give grace.

Grace is the strength to let go of proving a point. The willingness to give someone space to recognize what went wrong and find their way back. Every one of us needs that space, because every one of us makes mistakes.

Grace holds truth in one hand and love in the other. It sees what happened and names it honestly. It also holds out the invitation to begin again. In this way, grace strengthens relationships and helps keep them whole.

Grace looks to the future. A person rarely grows when held down by another’s righteousness. They grow when they feel the freedom to face their mistakes with dignity. Grace creates space for that freedom.

The flow of grace is a gift that we depend on. It honors truth. It protects relationships. When we give grace, we often find that it changes us as well.

We may discover that the person we extend grace to carries burdens we never knew about. When we choose grace over vindication, we become more human, more aware of our own weaknesses, and more capable of genuine compassion.

“Put on then, as God’s chosen ones, holy and beloved, heartfelt compassion, kindness, humility, gentleness, and patience, bearing with one another and forgiving one another, if one has a grievance against another; as the Lord has forgiven you, so must you also do.” – Col 3:12–13

Photo by Mrugesh Shah on Unsplash

Providing Room to Fail

Organizational culture, not technology, is the hardest part of innovation

How many of your projects are truly innovative? If you have any, what’s your success rate? Would you consider your success rate to be all-star caliber?

This baseball analogy is almost a cliché, but it holds up. A professional hitter with a .300 average is considered excellent (all-star?). That means they fail seven times out of ten.

Now imagine applying this to innovation. What if only 30% of your projects succeed? At first glance, that sounds like a losing record. But if the successful projects provide 10x productivity increases, transform your customer’s experience, or massively boost profitability…30% success would yield incredible results for your organization.

This is the kind of opportunity in front of us today with AI. Tools are maturing quickly. The potential is staggering. Every company, large or small, is beginning to experiment.

Some will tiptoe. Others will dive headfirst. All will face a mix of breakthroughs and busts.

There will be tools that don’t deliver on promises, pilots that fizzle, and teams that struggle with adoption. But there will also be amazing homeruns. Projects that reshape the business and redefine what’s possible.

Many leaders today are focusing on which AI tools to purchase and how to train their teams. That’s the easy part.

The harder part is creating space for both the hits and the strikeouts. If people feel they must succeed every time, they probably won’t swing at all. They’ll play it safe and stick with what they know.

Innovation will grind to a halt.

Providing room to fail doesn’t mean celebrating mistakes. It means making sure your team knows that experiments, even the ones that fall short, are part of making progress. Leaders who demand perfection get compliance. Leaders who make room for failure get innovation.

As you lead your organization into AI and beyond, remember that your job isn’t to guarantee every swing is a hit.

Your job is building a culture where people are willing to keep taking swings.

Photo by Chris Chow on Unsplash

Climbing in Times of Change

René Daumal titled his unfinished novel, Mount Analogue. It describes a peak, “whose summit is inaccessible by ordinary means.” The mountain can only be reached through inner transformation, making it both a place and an analogy for our journey of struggle toward resilience and clarity in the fog.

Leadership in upheaval can feel similar. Our map runs out. The ground shifts. We carry only our memories. Some sharp with regret, others shining with joy. Yet even scars can become footholds for our climb.

Daumal wrote, “You cannot stay on the summit forever; you have to come down again. So why bother in the first place? Just this: what is above knows what is below, but what is below does not know what is above.”

The summit gives leaders perspective. From above, we see connections hidden from the valley floor. The shape of the landscape, how the streams converge, where the shadows fall and light breaks through. We descend changed by what we’ve seen, and those who walk beside us are steadied by our vision.

History shows us that change always reshapes our climb. The printing press, the steam engine, electricity, space travel, and global connectivity to name a few. Artificial intelligence is the latest steep slope, bringing fear, excitement, and possibility all at once.

Leaders can steady others by naming the change clearly, framing the opportunities, modeling ways to adapt, and keeping purpose at the center of the change.

Daumal died before finishing his book. It breaks off mid-sentence. A fitting metaphor for leadership. Unfinished, unresolved, always in motion.

Leadership is the willingness to prepare others for the climb, walking faithfully with them, and offering perspective so they can see what’s possible…and dare to tackle the climb themselves.

h/t – James Clear for showing a quote from this book that sent me down the path to learn more about Mount Analogue. 

Photo by Caleb Lumingkit on Unsplash

Who Will Hold the Boulder? (a short parable)

There once was a village named Smithville, tucked neatly beneath a mountain. Life was simple until the mayor spotted a massive boulder teetering on the slope. Experts confirmed the obvious. The massive boulder might fall and crush the town.

In a flash of civic urgency, the mayor declared: “We must secure the boulder!” And so they did. With ropes, pulleys, and sheer determination, ten villagers at a time held the lines to keep the boulder in place. They rotated shifts around the clock. It became routine, then tradition, then law.

Children sang, “Hold the boulder, hold the boulder, we must resolve to hold that boulder!” before school each morning. A cabin was built for the rope holders. A trail crew was hired to keep the path safe for the endless march of workers. Rope suppliers prospered since the intricate rope system required constant maintenance. Soon, nearly half the town’s budget went to “boulder security.”

Still, the village flourished. Visitors came to marvel at the rope-wrapped rock. “Come see our mighty gravity defying boulder!” proclaimed their glossy posters. A bond was passed to fund a visitor center and tour buses. Hotels filled. Restaurants boomed. Property values soared near “Boulder View Estates.”

One day, a newcomer named Brunswick questioned the logic of leaving the boulder where it was. “Why not break the boulder into smaller, harmless pieces?” The council laughed at his question.

The mayor beamed with pride, “Our boulder isn’t a threat. It’s our livelihood! Besides, we have a rope system to protect us.”

The townspeople nodded, waving their SAVE OUR BOULDER signs in support.

Who could argue with prosperity?

Brunswick left shaking his head.

Years later, despite the ropes, despite the cables, despite the slogans, the inevitable happened. That winter, the boulder grew heavier than ever with snow and ice. Villagers had trouble reaching the ropes, as storms blocked the trail. Shifts went unfilled. Fewer villagers meant fewer ropes to hold the boulder.

“The forecasters said it wouldn’t be this bad,” the mayor reassured them, as though the weather itself had broken its promise.

Workers tugged and shouted, trying to keep their grip. Fingers numbed, feet slipped, and a few gave up entirely.  The remaining ropes snapped one by one. The sound echoed through the valley like rifle shots. The mountain itself seemed to groan.

Then came the moment. The final rope gave way with a thunderous crack. The boulder lurched forward, dragging what remained of the cable nets with it.

As it tumbled down the mountain, the ground shook violently. Houses rattled, dishes shattered, and children screamed.

The mighty rock careened toward the valley, smashing trees like twigs and carving deep scars into the earth. Clouds of dust rose as if the mountain were on fire. Each bounce sent shockwaves through Smithville, knocking people off their feet. The villagers ran in terror, listening to the deafening roar as the great stone rolled ever closer.

When it finally came to rest, the devastation was complete. The visitor center lay in ruins. Boulder View Estates was flattened into rubble. Streets were cracked, and smoke rose from shattered chimneys.

Yet by some miracle, no one was hurt. The thunder of the falling boulder gave everyone time to flee. Amid the destruction, whispers of a miracle could be heard all over the battered town. 

As the dust cleared, townsfolk began to consider their plans for rebuilding. Some sketched designs for a grand new visitor center. This one would tell the story of The Great Fall.

A five-year plan was drafted to study rope alternatives, complete with a Rope Oversight Committee and quarterly progress reports.

Bureaucracy bloomed again, strong as ever.

Though no one mentioned the missing boulder.

Story behind the image – I used Google’s new Nano Banana image generator for this image. I asked it to produce a large and evil boulder sitting on top of a mountain, held by ropes, overlooking a nice town that it’s threatening…in a cartoonish style. This is the first image it produced. It missed the part about the ropes, but I like the over-the-top (see what I did there?) theme of this rendering. And that boulder may appear in a few more stories in the future.

© 2025 Bob Dailey. Licensed under Creative Commons BY-NC-ND 4.0.

Optimize Today, Invent Tomorrow

Automation makes the machine run smoother. Innovation changes where the machine is going.

Automation hunts for efficiency. It tries to do what we did yesterday, but faster and cheaper. It targets the transactional and trims overhead. It removes steps and reduces friction. When done well, it buys back time.

Automation is valuable work and the price of admission for any organization.

But efficiency alone won’t differentiate.

Innovation asks different questions. Harder questions. Where are we trying to take our customers next? What experience would make them rethink what’s possible with us?

Innovation seeks to create new value.

Innovation needs space, a space that promotes bold and creative thinking.

It might mean dedicating 20% of a team’s work to exploring customer problems without predetermined solutions.

Or creating quarterly “innovation days” where normal metrics don’t apply.

Or creating time in leadership meetings for “what if” conversations instead of only “what’s broken” discussions.

Leaders set the tone. They can focus solely on efficiency, or they can ask questions that point their organization toward innovation.

If your new system creates fewer clicks, fewer steps, and lower costs, you automated.

If you created a new customer journey or opened a new market category, you innovated.

Do both well and you reshape the game.

Automation keeps us strong today. Innovation makes us irreplaceable tomorrow.

Photo by Ben Soyka on Unsplash