What If You Could Prove the Government is Ripping Us Off?

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What If You Could Prove the Government is Ripping Us Off?

by Braden Kelley and Art Inteligencia

We are living through a crisis of civic experience. People can feel that they’re being ripped off by their elected and administrative officials, but yet they lack a fair way to prove it. The future will not be built by louder arguments alone. It will be built by better comparisons: value delivered per dollar, relative to peers who look like us. That is the spark for a human-centered citizen movement. First, let’s look at the scale of the problem already documented in the public record.

The bill without a receipt

Most of us do not experience government as a spreadsheet. We experience it as a journey: the permit that takes months, the school board meeting that buries tradeoffs in jargon, the water bill that climbs while the story never quite lands. That journey is the real product. And if experience design has taught us anything, it is this: when the interface of truth is broken, people do not get smarter by trying harder, they get cynical.

Cynicism is not a character flaw. It is a rational response to incomplete design.

We are asked to fund systems whose performance is rarely presented in the only language that makes human comparison fair: what does a place like mine get for money like mine?

Imagine, just for a moment, learning that a school district with a nearly identical enrollment mix educates children with far less administrative drag and better learning growth per instructional dollar. Or that a peer city issues permits, paves roads, or clears cases at a cost structure that cannot be waved away with “we’re special.” That is not a conspiracy theory. That is a design question. Design questions can be answered, if we stop accepting fog as a management strategy.

Before we build the instruments of peer comparison, we have to stop understating what already leaks, bloats, and under-delivers in plain sight. Innovation begins with facing reality, not romanticizing it.

The scale hiding in plain sight

If this were only a few bad actors and a few delayed audits, a nice annual report and a press release would be enough. The public record says otherwise. What we are looking at is a systems problem: structural error and theft measured in hundreds of billions; spending that sprints past simple population-and-inflation baselines; and institutions whose staffing mix drifts toward administration while the work citizens think they are buying becomes relatively thinner.

Let’s start at the federal level, not because your city council or school board is less important, but because the national numbers are large enough that denial starts looking like a lifestyle choice.

The U.S. Government Accountability Office (GAO) estimated that direct annual financial losses to the federal government from fraud fall between roughly $233 billion and $521 billion a year, based on fiscal years 2018–2022 risk environments (GAO-24-105833 highlights; full report: PDF). That is not a rounding error. That is a second economy of loss living inside the first.

Then there are improper payments – the broader leak that includes overpayments, underpayments, documentation failures, and more. Agencies reported about $236 billion in improper payments in fiscal year 2023 (GAO FY2023 overview) and still about $162 billion in fiscal year 2024 after some pandemic programs wound down (GAO FY2024 press release; GAO-25-107753 PDF). Cumulative improper-payment estimates since fiscal year 2003 approach about $2.8 trillion (see GAO-25-107753). Earlier in the same stretch: roughly $281 billion in FY2021 (GAO) and $247 billion in FY2022 (GAO).

Let’s be clear, as any honest change leader must be: improper payments are not all intentional fraud. But they are the proof that our control experience is broken. If you cannot reliably send the right money to the right place, you do not have a “communications” problem. You have a design problem.

Bar chart of federal improper payment estimates for FY2021 through FY2024, declining from roughly $281 billion to $162 billion but remaining very large.

Federal agency-reported improper payment estimates remain measured in hundreds of billions even after the pandemic peak. Sources:
GAO FY2021 (~$281B);
GAO FY2022 (~$247B);
GAO FY2023 (~$236B);
GAO FY2024 (~$162B).
Scale of loss is one window. Scale of spend is another. Total federal net outlays rose from roughly $3.5 trillion in fiscal year 2014 to roughly $6.7 trillion in fiscal year 2024 – nearly a doubling in a decade in nominal dollars, with the pandemic rewriting the shape of the curve. Those figures come from the U.S. Office of Management and Budget historical outlay series published via the Federal Reserve Bank of St. Louis as FRED series FYONET, with the broader tables at OMB Historical Tables.

More spending can mean more service, more obligations, an older population, emergencies. Futurology without humility is just sci-fi cosplay. But here is the innovation insight most public debates miss: absolute “we spent more” tells citizens almost nothing about unit cost, quality, or leakage. When the size of the system grows, the need for peer-relative instruments grows with it. Otherwise we are asking people to navigate a denser fog with the same broken map.

Bar chart showing U.S. federal net outlays rising from about $3.5 trillion in FY2014 to about $6.7 trillion in FY2024.

U.S. federal net outlays, selected fiscal years (nominal dollars). Source:
OMB Federal Net Outlays (FYONET) via FRED.
See also OMB Historical Tables.
Now bring it closer to home – for many of us, literally. Washington State’s Near General Fund–Outlook (NGF-O) operating budget grew from about $31.2 billion in the 2011–13 biennium to about $80.2 billion for 2025–27, roughly a 157% increase in nominal dollars, as laid out by the Washington Policy Center using the state’s NGF-O series. The 2023–25 NGF-O package, after the 2024 supplemental, was about $71.9 billion (Legislative Budget Notes PDF). The same analysis notes that if spending since the mid-2010s had tracked only population and inflation, today’s scale would be tens of billions lower. Growth is real. “We only kept up with costs” is a different claim. Official statewide spending trails also live at fiscal.wa.gov.

This is not a Washington-only story. It is a pattern story: when the bar chart climbs and the experience of value does not climb with it, citizens notice – even if they cannot yet prove the gap against peers.

Bar chart of Washington state Near General Fund–Outlook biennial operating budgets rising from $31.2 billion in 2011–13 to about $80.2 billion in 2025–27.

Washington NGF-O biennial operating budget scale (nominal). Sources:
Washington Policy Center NGF-O growth summary
(2011–13 ≈ $31.2B; 2025–27 ≈ $80.2B; ~157%);
2023–25 NGF-O ≈ $71.9B (Legislative Budget Notes PDF);
mid-decade ~$38B scale as described in the same WPC overview of the decade-long climb.
Then there is administrative gravity, especially in higher education, where parents still believe they are buying teaching first. The Delta Cost Project at the American Institutes for Research documented something experience designers would call a quiet interface change: as managerial and professional administrative ranks grew, the average number of faculty and staff per administrator fell by roughly 40 percent at many four-year institutions between 1990 and 2012, landing near 2.5 or fewer faculty and staff per administrator (Desrochers & Kirshstein, Labor Intensive or Labor Expensive?, 2014 (PDF); AIR press summary). Professional non-faculty roles often grew faster than full-time instructional capacity, even as campuses leaned harder on part-time instructors. The underlying institutional data ecosystem lives in IPEDS and the Delta Cost Project database.

Is every new position waste? Of course not. Human organizations need coordination. The revolutionary question is not “abolish administration.” It is: do we have a transparent, peer-relative view of what administration costs relative to learning and outcomes — or are we just hoping for the best?

Bar chart showing faculty and staff positions per administrator declining from roughly 3.3 around 1990 to about 2.3 around 2012.

Illustrative faculty-and-staff-per-administrator levels reflecting Delta Cost Project / AIR findings of roughly a 40% decline from 1990 to 2012 at many four-year campuses, averaging about 2.5 or fewer faculty and staff per administrator.
Source: Desrochers & Kirshstein (2014) PDF.
And then there is the softer, stickier problem: corruption perceptions and nonprofit “grift” that thrives in long outcome chains. In occupational-fraud cases studied by the Association of Certified Fraud Examiners (ACFE), government organizations and for-profit firms land around a median loss of about $150,000 per case, while nonprofits still show up in about one in ten cases, with smaller median losses (about $76,000) that can still wreck a thin-margin mission (Occupational Fraud 2024: A Report to the Nations (PDF)).

Here is the human-centered insight: when public dollars pass through contractors and tax-exempt intermediaries, the distance between the taxpayer’s intention and the citizen’s experience often grows. High overhead, related parties, vague deliverables, and glossy stories without unit costs are not always illegal – but they can be a failure of value design. Law can punish fraud. Only better metrics can expose underperformance that still has good branding.

Trust tracks this story. Transparency International’s Corruption Perceptions Index has scored the United States in the mid-60s out of 100 in recent years, with multi-year deterioration flagged by Transparency International U.S. (see their CPI 2025 statement (PDF)). When perceptions fall, governance gets more expensive — because every negotiation becomes theater, and every reform takes more energy to land.

So stack it up without theatrics: hundreds of billions a year in federal fraud-loss risk and improper-payment leakage; state operating budgets that can more than double across a decade and a half; staffing mixes that load coordination relative to the work many people believe they are buying; pass-through chains that hide unit economics. That is enough reason to innovate how citizens see value. It is not a license to smear every public employee. Revolutionary change worth having is precise, not performative.

Sources for the scale claims above

Why shouting about “too much spending” never ends the argument

American public argument too often collapses into two dead ends. One side treats every dollar as proof of compassion. The other treats every dollar as proof of waste. Both can be partially right, and still leave neighbors holding a slogan instead of a shared fact.

Absolute spend is a weak instrument for learning. Larger places spend more. Harder case mixes cost more. Expensive labor markets pay more without automatically proving mismanagement. When numbers ignore context, people fight about identity instead of performance. That is not governance. That is sportswashing for budgets.

Experience design offers a simpler truth: people cannot improve what they cannot sense. If the “interface” of civic truth is either opaque PDFs or cable-news moral theater, the lived journey of taxpayers becomes cynicism – then disengagement – then the quiet permission structure where bloat, under-delivery, and yes, fraud, get more time than they deserve.

The future of healthier institutions will not be won by volume alone. It will be won by better comparisons ordinary people can use without a PhD in public finance. That is human-centered change in one sentence: redesign the sense-making layer, and better action becomes possible.

A better unit of civic truth: value relative to peers

Futurology has a bad habit: it over-promises technology and under-specifies culture. Here is the cultural upgrade that matters first.

Score places the way adults already rank experiences in the rest of life, relative to alternatives that should be similar.

Peer-relative value asks a sharper question than “how much did we spend?” It asks: among entities of roughly the same size and constraints, who delivers more real outcomes per dollar – and who is the best performer we should be learning from?

That shift changes the emotional temperature of accountability. It is harder to dismiss a neighbor when the comparison is another city that looks like yours, another county with a similar mandate set, another school district with a similar student population, another water district with similar infrastructure age. The conversation stops being “are you for or against government?” and starts being “why are we so different from our best peers?”

Relative performance does not erase values. It clarifies delivery. Compassion with weak unit economics is still compassion, and also an unfinished design problem. Efficiency without outcomes is just thrift cosplay. Citizens deserve both: what was intended, and what was delivered, at a cost that survives peer daylight.

This is innovation in the classic sense: not novelty for its own sake, but a better way of creating and measuring value — at the civic layer, where most of life is still lived.

Where fraud, grift, and bloat actually hide

Serious fraud is not always cinematic. More often it is procedural: sole-source patterns that never face real competition; nonprofit pass-throughs that struggle to show outcomes while still collecting public purpose; administrative layers that expand faster than service quality; capital projects whose unit costs and schedule slips never get benchmarked against places that built something comparable; delay as a shield because documents arrive too late to matter.

This is where passion becomes useful, and where discipline becomes non-negotiable. Performance gaps and integrity red flags are not the same thing. Treating every underperforming budget line as a crime story destroys trust the first time a good-faith agency is smeared. Treating every audit as “politics” is how poor design gets tenure.

A mature citizen practice separates the tracks, think of them as three instrument panels on the same dashboard:

  • Performance: outcomes and service quality relative to cost among peers.
  • Structure: administration share, contracting concentration, salary density versus output.
  • Integrity: delayed reporting, audit findings, related-party patterns, outcome-light grantee chains—presented with sources, confidence, and room to reply.

That separation is not gentleness toward corruption. It is how legitimate pressure remains standing when the pushback arrives. Revolutions that last are the ones that can still tell the truth under scrutiny.

The future of accountability is local (and buildable)

National drama can make local work feel small. It is not. Your life is administered by boards, districts, counties, cities, and agencies that set real prices for real services within a few miles of your door. Those are also the levels where a committed group of citizens can still change the information environment in a single budget cycle.

What is newly possible, and this is the innovation hinge, is not “AI as magic.” Magic is for marketing decks. Real innovation is AI as scale applied to the boring, necessary labor of extraction, classification, plain-language briefing, and pattern spotting — always subordinated to transparent methods and primary records. The opportunity is a suite of do-it-yourself tools that a passionate local team can download, stand up, and own: gather public data, process it with clear human oversight, and publish peer benchmarks for the jurisdiction they care about.

Think of it as open experience architecture for citizenship: not a single national score imposed from above, but many local instruments speaking the same comparative language. Cities. Counties. States. School districts. Water boards and special districts. Same idea. Local ownership. Peer daylight.

Movements fail when they ask everyone to wait for a capital-city hero. They gain power when they give capable people a way to begin where they already have skin in the game—and when the path from “I care” to “I can host a public scoreboard” is designed, documented, and downloadable. That is human-centered change: remove friction between intention and action.

From spark to local firepower: what you can actually do

Enthusiasm without a next step is just another scroll. So here is the honest promise of this movement: we are building the instruments — and you choose the jurisdiction, the intensity, and the role that fits your life.

Start with a target you can describe in one sentence. Your school district. Your city budget. Your county contracting. Your state’s administrative stack. Your water or sewer or flood-control district, the special-purpose governments that spend real money while almost nobody is watching. Passion plus a defined entity beats vague anger about “the system” every time.

Then choose a depth of start that matches your week, not your fantasy of free time:

  • Weekend scout: Pull the latest budget, CAFR, or checkbook export. List the top five cost centers. Note what is missing — outcomes, headcount by function, sole-source awards. That alone is civic reconnaissance.
  • Meeting witness: Show up once a month with three peer-comparison questions written in advance. Serious questions change how staff prepare—and how journalists listen.
  • Budget-season cadence: Build a small team and a calendar tied to when appropriations still can move. That is when numbers still have opponents who can feel them.
  • Local scoreboard: When the toolkit ships, stand up a public site — data intake, AI-assisted processing under human guardrails, and peer-relative benchmarks neighbors can share without translating bureaucracy dialect.

You do not need to do everything. You need a first mile. The guidebooks we will publish will walk those miles: how to FOIA without burning out, how to structure a peer cohort fairly, how to avoid turning a performance gap into a defamation trap, how to brief a board in three minutes, how to partner with a local reporter as an ally rather than an ambush.

Lighting a fire does not mean burning institutions down. It means raising the temperature of truth until fog can no longer survive as a management strategy—and giving thousands of local teams the same matchbook.

Pick a role that fits how you show up

From the outside, movements look monolithic. From the inside, they are division of labor — just like every innovation team that ever shipped anything that mattered. You do not have to become a full-stack auditor, web host, and public speaker on the same Tuesday night. Find the work that matches your temperament. Then find one person whose temperament complements yours.

Data gatherers and custodians. You enjoy documents more than microphones. You pull budgets, salary schedules, bid awards, board packets, 990s tied to public grants. You file public-records requests, keep the source folder honest, and leave a trail so nothing depends on a single hero’s laptop. Without clean intake, every downstream score is theater.

Benchmarking intelligence creators. You want the “so what.” You define peer sets carefully, normalize costs, choose outcome metrics that survive scrutiny, and write method notes so a critic can challenge the math without inventing motives. You turn spreadsheets into stories: unit cost of pavement, administrative share of a district, permit latency per FTE, learning growth per instructional dollar — always versus true peers. When the AI processing stack is ready, this role runs it with human judgment still on the wheel.

Website hosts and local product owners. You are willing to stand something up for your community: a place where neighbors can see the score, the sources, the trends, and an invitation to correct errors. You care about reliability and clarity – not turning a civic tool into a partisan meme machine. The downloadable suite is for you: templates, deployment path, content structure—so passion is not blocked by “I don’t know how to ship a site.”

Promoters, translators, and evangelists. You are the bridge. You do not have to invent the model. You make sure it reaches PTAs, rotary clubs, neighborhood groups, faith communities, taxpayer groups, student journalists, and people who will never open a CAFR unprompted. You translate peer-relative value into plain language, share uncomfortable comparisons without contempt, and keep the movement multipartisan enough that the score—not the team jersey—remains the headline.

Meeting advocates and budget-season operators. You take the brief to the microphone. Three questions. One peer chart. A written record. You show up when the appropriation can still move. The action packs we will release are for this role: scripts, FOIA companions, and “why the gap” one-pagers for boards and councils.

Local media partners and explanation designers. You help facts travel. A retired editor, a podcast host, a newsletter writer, a visual explainer—anyone who can turn a transparent ranking into public attention that demands reply rather than rumor. Credible pressure almost always needs a second institution’s megaphone.

Tutors of the top decile. When a peer is crushing your entity on value, someone should study them without ego—procurement habits, staffing ratios, open-data practices, facility utilization, grantee outcomes. Celebrating excellence is not a side quest. It is how reform becomes copyable instead of merely shaming. That is continuous improvement in civic form.

If you have ever left a public meeting thinking, “Someone should document this properly,” there is a role with your name on it. If you can explain a hard idea at a kitchen table, there is a role. If you can keep a folder organized, there is a role. The only non-role is permanent spectator—assuming someone else will finish the counting.

From newsletter spark to the bonfire of tools

The first act of a movement is not a software download. It is a shared refusal: we will no longer treat uncompared spending as a finished explanation of life. We will learn to ask for peer-relative value. We will demand receipts ordinary people can follow. We will treat the best performers as teachers, not enemies.

The second act is capability. That is the work now underway: do-it-yourself tooling for data gathering, careful AI-assisted processing, and public benchmarking intelligence — plus a series of role-based guidebooks so data gatherers, intelligence creators, website hosts, promoters, and budget-season operators are not inventing discipline from scratch in the dark.

Between spark and bonfire, there is a simple way to stay in formation: join the people who want the heads-up when the kits go live, when the next methods article drops, and when the first local teams start publishing peer scores others can fork and improve.

If this article lit something in you, subscribe to Human-Centered Change & Innovation Weekly. Use that signup as your seat on the bus for this movement. When the downloadable tools and guidebooks are ready — beyond the idea, into usable firepower — that is how you will know first, with practical next steps you can take in the jurisdiction you choose.

Prefer the full signup page? Open the newsletter signup page.

Tell a friend who sits through the same meetings and mutters the same unfinished sentence. Forward this to the person who always says, “If someone would just pull the numbers…” Forward it to the person who already pulls numbers but has nowhere trusted to publish them. Movements scale by invitation more than by manifesto.

For now, sit with the question every zip code deserves:

What if your community pays more and gets less than its true peers — and the only reason it continues is that nobody has finished the counting?

If that question lands, you are already part of the movement. Choose a jurisdiction. Choose a role. Get on the list. We will build the matchbooks — toolkits, methods, and guidebooks — so when you are ready to strike, the fire has somewhere local, human, and bright to go.

Frequently Asked Questions

What is “peer-relative value,” and why is it better than arguing about total spending?

Peer-relative value compares what similar governments achieve per dollar — schools with similar student needs, cities of similar size and density, utilities with similar infrastructure ages — rather than treating raw budget size as proof of success or failure. It makes accountability fairer because it adjusts for context, and sharper because it points to real best performers citizens can learn from. In experience-design terms: it gives people a better interface for understanding value.

Does this approach accuse every high-spending community of fraud?

No. Serious, human-centered accountability separates performance gaps (weaker outcomes or higher unit costs than peers) from integrity red flags (audit issues, opaque grantee chains, noncompetitive contracting patterns) that require stronger evidence. Relative benchmarking creates pressure for better results; it is not a substitute for investigation, law, or due process—and it should never be used as a license to smear people who serve in good faith.

How can I get involved before the tools are fully available?

Choose one jurisdiction you care about, start basic public-record reconnaissance, and pick a role that fits how you show up — data gathering, benchmarking intelligence, website hosting, promotion, meeting advocacy, or media partnership. Subscribe to Human-Centered Change & Innovation Weekly at bradenkelley.com/contact-me/newsletter-signup/ so you are first in line when downloadable toolkits and role-based guidebooks are ready to help stand up local peer-benchmarking sites.

Image Credits: Gemini

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Cursor to clean up the article.

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Top 10 Human-Centered Change & Innovation Articles of July 2026

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Top 10 Human-Centered Change & Innovation Articles of July 2026Drum roll please…

At the beginning of each month, we will profile the ten articles from the previous month that generated the most traffic to Human-Centered Change & Innovation. Did your favorite make the cut?

But enough delay, here are July’s ten most popular innovation posts:

  1. What Happens When AI Becomes Your Customer? — by Shep Hyken
  2. The Experience Economy 2.0 — by Braden Kelley
  3. How to Calculate the ROI of Customer Experience — by Braden Kelley
  4. Strategic Foresight: A Practitioner’s Guide to Thinking About the Future — by Braden Kelley
  5. Innovation or Not — InTruth — by Braden Kelley
  6. Innovation Framework Examples: 7 Real-World Cases That Show How They Work — by Braden Kelley
  7. The Personal AI Renaissance — by Braden Kelley
  8. Your 3 Phase AI Journey — by Geoffrey Moore
  9. Why So Much Bullshit? — by Greg Satell
  10. Creating an Innovation Edge — by John Bessant

BONUS – Here are five more strong articles published in June that continue to resonate with people:

If you’re not familiar with Human-Centered Change & Innovation, we publish 4-7 new articles every week built around innovation and transformation insights from our roster of contributing authors and ad hoc submissions from community members. Get the articles right in your Facebook, Twitter or Linkedin feeds too!

Build a Common Language of Innovation on your team

Have something to contribute?

Human-Centered Change & Innovation is open to contributions from any and all innovation and transformation professionals out there (practitioners, professors, researchers, consultants, authors, etc.) who have valuable human-centered change and innovation insights to share with everyone for the greater good. If you’d like to contribute, please contact me.

P.S. Here are our Top 40 Innovation Bloggers lists from the last five years:

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Three Facts That Business Leaders Refuse to Accept

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Three Facts That Business Leaders Refuse to Accept

GUEST POST from Greg Satell

In the late 90s Fortune magazine named Enron the most innovative company for six consecutive years, right up until the company collapsed in scandal. GE’s strategy of stack ranking was seen as a model to be emulated by other firms, even though there was no evidence it worked. McKinsey advised companies to fight a war for talent.

Today, we know better. It’s obvious that Enron was incredibly dysfunctional, that stack ranking undermines a high-performance culture and that talent is something that you build through upskilling, not something you “win” in a metaphorical war. It’s mind boggling to think of all the damage that was done before those ideas were exposed.

Yet if we accept all that we need to ask ourselves which ideas are widely accepted today that don’t hold water. Every era has its own fictions, things that are accepted because they are repeated, but lack any serious foundation. They become memes replicating themselves throughout the zeitgeist, rarely being questioned. Here are three truths that will surprise you.

1. Bigger Organizations Are More Innovative

We tend to think of innovation as something startups do. Big organizations, with their bloated bureaucracies and cumbersome decision making, are less nimble. Yet a recent book, Corporate Explorer, by Stanford professor Charles O’Reilly, Harvard Professor ​​Paul Lawrence and consultant Andrew Binns finds that larger firms have more resources, talent and ideas.

This may seem surprising, but there is ample evidence supporting the principle that larger enterprises innovate more effectively. A 1969 study of local health departments found that the larger ones serving larger communities were more innovative. A 1986 analysis of footwear manufacturers found that the bigger ones had more technical specialists and adopted more radical innovation. Same thing when researchers looked at German banks’ adoption of telecommunication services.

Clearly startups have advantages. They tend to be less bureaucratic and can make decisions faster. They are also less invested in incumbent systems and technologies, which makes change easier. Yet innovation isn’t just about speed, it’s also about commitment to solving important problems and larger enterprises have more resources and scope to do that.

That’s why when you look at the most cutting edge technologies, like quantum computing, artificial intelligence, materials science, synthetic biology and others, you tend to find large organizations at the core. Don’t get me wrong, not every big company can innovate, but the ones that can come up with new ideas and execute them consistently, year after year and decade after decade, are enterprises with scale.

2. Levels Of Bureaucracy And Hierarchy Are Increasing, Not Decreasing

About a decade ago, the management guru Gary Hamel wrote a highly cited article in Harvard Business Review entitled First, Let’s Fire All the Managers. He analyzed the success of Morningstar, a leading manufacturer of tomato products that operates with a flat management structure and called for other corporations to follow its lead.

“A hierarchy of managers exacts a hefty tax on any organization,” he wrote. “This levy comes in several forms. First, managers add overhead, and as an organization grows, the costs of management rise in both absolute and relative terms.” The article was very influential and helped bolster other flat models, such as Holacracy.

For a while now, management gurus have been advocating for flatter organizations, yet there is little evidence that eliminating managers is a viable model. In fact, when Wharton Professor Ronnie Lee took a close look at game software developers, he found that the number of levels of bureaucracy increased significantly, not decreased, over the last 50 years.

Certainly, the “flat organization” idea hasn’t caught on. “Since 1983, the size of the bureaucratic class—the number of managers and administrators in the US workforce—has more than doubled, while employment in other categories has grown by only 40%,” Hamil recently wrote.

The inescapable conclusion is that we’ve failed to do away with bureaucracies and hierarchies because they serve a useful purpose. While flatter structures can inspire creativity, we need hierarchies to execute complex operations well. That might not play well when your trying to sell consulting projects or on the keynote stage, but it’s the truth.

3. Markets Are Becoming Less Competitive, not More (At least in the US)

Today it’s become an article of faith that everything moves faster. Business pundits tell us that we’re living in a VUCA world (Volatile, Uncertain, Complex and Ambiguous). These are taken as basic truths that are beyond questioning or reproach. Yet are things actually moving any faster than in earlier eras? The evidence is surprisingly scarce.

The data, however, tell a very different story. A report from the OECD found that markets, especially in the United States, have become more concentrated and less competitive, with less churn among industry leaders. The number of young firms have decreased markedly as well, falling from roughly half of the total number of companies in 1982 to one third in 2013.

A comprehensive 2019 study from the National Bureau of Economic Research found two correlated, but countervailing trends: the rise of “superstar” firms and the fall of labor’s share of GDP. Essentially, the typical industry has fewer, but larger players. Their increased bargaining power leads to more profits, but lower wages.

The truth is that we don’t really disrupt industries anymore. We disrupt people. Economic data shows that for most Americans, real wages have hardly budged since 1964. Income and wealth inequality remain at historic highs. Anxiety and depression, already at epidemic levels, worsened during the Covid-19 pandemic.

What You See Is How You’ll Act

When ideas are repeated often enough, we begin to take them as self-evident and don’t even question them. People take it for granted that small organizations are more innovative than larger ones, that flatter organizations outperform those with high levels of bureaucracy and that business is more competitive today than in earlier eras.

If you believe all that, then you would avoid getting involved with a large organization if you want to innovate, you would try to eliminate levels of hierarchy and create a high sense of urgency about everything you do. Yet when you examine the evidence it becomes clear that none of these things are factual.

The truth is that size has little to do with innovation. As we saw during Covid, the most pathbreaking advances came from collaborations between organizations, public and private, large and small. The levels of hierarchy in an organization aren’t nearly as important as its networks. Pushing too many initiatives is more likely to result in a high level of change fatigue and diminished mental health than lead to genuine results.

When we look back at earlier eras, it’s easy to see the errors in the zeitgeist. It seems obvious that the robber barons undermined society, that excessive tariffs during the depression would impoverished society and that Enron was a fraud. Yet we need to look with the same skeptical eye at prevalent beliefs today.

As Richard Dawkins has explained, memes are selfish. They propagate themselves for their own benefit, not necessarily for ours. We need to learn to be fiercer advocates for our fates.

— Article courtesy of the Digital Tonto blog
— Image credit: Pexels

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AI Will Create a More Human Future, Not a Less Human One

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An AI Soft Landing Scenario

AI Soft Landing Scenario
by Braden Kelley and Art Inteligencia

What If the Future Gets More Human?

We spend a remarkable amount of time rehearsing the wrong ending.

In one popular story, artificial intelligence hollows out work, flattens craft, and leaves people performing the emotional leftovers of automation. That is a hard landing: humans demoted by systems that do more of everything, including the parts of work that used to make us feel useful.

There is another future available to us, what I call an AI soft landing. In that future, organizations and societies deliberately design AI to absorb fragmentation, acceleration, and low-judgment transaction. What returns to humans is not emptiness. What returns is depth: larger blocks of time for insight, empathy, decision making, direction setting, problem definition, creativity, and collaboration. The future becomes more human, not less, because human attention is finally reserved for human work.

This is not a naive techno-optimism. Soft landings are designed. Hard landings arrive when efficiency is the only value on the dashboard.

The Hidden Enemy Was Never “Work.” It Was Fragmentation.

Most knowledge work did not become less meaningful because people stopped caring. It became less meaningful because attention was diced into tickets, pings, updates, status rituals, and micro-approvals. We mistook motion for progress and responsiveness for value.

Task switching is expensive. Every context shift asks the brain to unload one problem and reload another. Multiply that by a day of chats, forms, triage, and administrative glue work, and you get a workforce that is always “on” and rarely deep. Strategic thinking does not fail only for lack of talent. It fails for lack of contiguous time.

AI’s first gift, if we use it well, is not genius on demand. It is fewer interrupted minutes. When drafting, scheduling, summarizing, searching, classifying, routing, and first-pass analysis get accelerated or handled, the calendar can stop looking like confetti. Bigger time blocks reappear. And bigger blocks are the raw material of original insight.

AI Future of Work

What Humans Should Own in a Soft Landing

A soft landing is not humans “using AI better.” It is a clear division of cognitive labor, one that protects the uniquely human contribution instead of competing with the machine on volume.

In a more human future, people spend more of their capacity on:

  • Insight development — connecting weak signals into meaning, not merely producing more output
  • Empathy — understanding stakes, dignity, and lived context that no dashboard fully captures
  • Decision making — choosing under uncertainty with values, tradeoffs, and accountability
  • Direction setting — naming where we are going and why it is worth the journey
  • Problem definition — asking better questions before rushing to automated answers
  • Creativity — combining perspectives in ways that are novel, useful, and humanly resonant
  • Collaboration — building trust, resolving conflict, and making progress together

Notice what is missing from that list: being the fastest typist in the room. Soft landing excellence is not measured in tokens per minute. It is measured in clarity per hour — and in whether people leave interactions more capable, more trusted, and more oriented than before.

From Transactional Lives to Strategic Ones

When small tasks expand to fill the day, even senior roles become transactional. Leaders spend their best hours approving instead of directing, reacting instead of sensing, facilitating meetings about work rather than doing the work of judgment.

AI can reverse that inversion, but only if organizations stop using every efficiency gain to stuff more micro-tasks into the same damaged attention budget. Saving ten minutes and immediately filling them with ten more interruptions is not transformation. It is denser exhaustion.

The soft landing asks a different operating question: What human capability do we want more of, now that machines can carry more of the glue?

If the answer is “more throughput at any cost,” you will automate people into thinner slices of busyness. If the answer is “more strategic quality, better problem framing, deeper customer and employee understanding,” AI becomes a scaffold for human depth. Less task switching. More deliberate thinking. Fewer performative updates. More real collaboration around decisions that matter.

AI Human Endeavors

How Leaders Design a Soft Landing (Instead of Hoping for One)

Human-centered change makes soft landings practical. A few design moves matter more than tool catalogs:

  1. Automate the glue, not the judgment. Route AI toward fragmentation: search, draft, summarize, schedule, classify, prepare. Keep humans responsible for choices with ethical, relational, or strategic consequence.
  2. Protect deep-work blocks as policy, not privilege. If AI creates capacity, calendar culture must not immediately reclaim it for more meetings.
  3. Redefine roles around human endeavors. Job descriptions should emphasize insight, empathy, problem definition, and direction — not inbox velocity as a proxy for value.
  4. Measure success in human outcomes. Track decision quality, customer trust, employee agency, and innovation usefulness — not only cost per interaction.
  5. Teach the craft of better questions. In an AI-rich world, problem definition becomes a core leadership skill. Bad prompts and bad frames still produce confident nonsense.
  6. Build collaboration for synthesis, not status. Use reclaimed time for cross-functional sense-making, not another dashboard review theater.

This is experience design for the future of work: design the system so people can be fully human on purpose.

The Choice Ahead

Futurology is not prediction cosplay. It is responsibility with a longer horizon.

We can use AI to compress people into ever-faster transaction machines. Or we can use it to return something modern work has been quietly stealing: the ability to think, feel, decide, and create with integrity.

The soft landing is the second path, a future where machines handle more of the small so humans can do more of the meaningful. Where strategy is less of a slide ritual and more of a practiced habit. Where customer and employee experience improve not only because algorithms personalize, but because people finally have the attention required for empathy and judgment.

A more human future will not arrive by accident. It will be designed by leaders who refuse to confuse automation with progress, and who insist that the best use of artificial intelligence is the expansion of human capacity where it still matters most.

Frequently Asked Questions

What is an AI soft landing?

An AI soft landing is a future in which artificial intelligence absorbs fragmented, transactional tasks so humans can spend more time on deeper endeavors — insight, empathy, decision making, direction setting, problem definition, creativity, and collaboration — making work more human rather than less.

How does AI reduce task switching at work?

AI can handle or accelerate small tasks such as drafting, summarizing, searching, scheduling, classifying, and routing. When organizations protect the time this frees, instead of immediately filling it with more interruptions, people gain larger blocks for strategic thinking and higher-quality collaboration.

What should leaders do to make the future more human with AI?

Leaders should automate glue work rather than human judgment, protect deep-work capacity as policy, redesign roles around human endeavors, measure human outcomes as well as efficiency, invest in better problem definition, and use reclaimed time for real collaboration and decision quality — not denser busyness.

Image Credits: Cursor

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Cursor to clean up the article.

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Managing Your Work Friends

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Managing Your Work Friends

GUEST POST from David Burkus

You just got promoted. Congratulations! But now you’re managing your friends. The people you used to grab lunch with, the ones you vented to about the boss, and the folks who knew every inside joke from your team Slack channel — they’re your team. And you’re their boss.

Work friendships are powerful. They boost morale, improve collaboration, and make the workday more enjoyable. I don’t have to convince you that having friends at work is valuable. But when the power dynamic shifts, when you go from being “work friend” to “work boss,” things inevitably change. Suddenly your decisions carry weight — promotions, raises, performance reviews, and tough calls that impact livelihoods. At the same time, your team knows a lot about you. Maybe they’ve seen your Instagram stories or been with you at happy hours. That blurred line between friendship and authority can get messy fast.

And this is the dilemma of managing your friends: how do you maintain meaningful relationships without undermining your credibility as a leader? How do you stay approachable and authentic while also being consistent and fair?

The answer isn’t easy, but it is possible. It starts with understanding what doesn’t work, and then rebuilding those friendships into a new kind of relationship.

Why Most New Managers Struggle

Most new managers stumble into one of two extremes when they start managing their friends. They either pretend nothing has changed, or they change everything.

Some ignore the shift. They keep gossiping, keep oversharing, keep hanging out exactly the same way — hoping the friendship will buffer any awkwardness. But it doesn’t. That kind of behavior undermines authority when it’s time to make a hard call. A joke about a teammate suddenly looks like favoritism. A venting session about a senior leader sounds like open dissent. And the manager’s credibility takes the hit.

Others overcorrect. They pull back completely. They stop socializing. They stop texting. They stop grabbing coffee or lunch. They put up walls and operate only in “professional mode.” That comes across as cold — because it is. And the sudden distance damages trust and morale.

Both extremes backfire. Pretending nothing has changed creates resentment and perceptions of favoritism. Overcorrecting destroys connection and trust. Neither approach works long term. What new managers really need is a third path: redefining the friendship for the new reality.

Why The Old Dynamic Doesn’t Work Anymore

It helps to remember why friendships at work felt easy before. They were built on equality. You were in the trenches together — venting about the same boss, rolling your eyes in the same meetings, maybe even sneaking out early together on a Friday. But the key word there is were. You were equals. Now you’re not.

Power dynamics are like gravity. You don’t always see them, but they’re always pulling. Once you’re in charge, every interaction gets filtered through that shift. You may think you’re just being candid with an old friend, but now it sounds like the boss has picked a side. You may think you’re just cutting them some slack, but others see favoritism. And once your team suspects favoritism, everything else you do gets questioned — your motives, your decisions, even your integrity.

That’s why the old friendship dynamic doesn’t work anymore. It’s not because the friendship isn’t real — it’s because the context has changed. So if you want to keep both your friendships and your credibility, you’ll need to redefine the relationship.

Five Tips For Managing Your Friends

1. Address the Shift Directly

Pretending nothing has changed is like pretending you didn’t just get promoted. Everyone knows. They feel it already. And if you don’t address it, the tension just lingers like an awkward silence no one names.

The fix is surprisingly simple: talk about it. You don’t need to make a big speech or hold a formal meeting. Just have an honest one-on-one conversation with each friend. Something as short as:

“Hey, I know this feels a little different now that I’m in this role. I really value our friendship, and I want to make sure I’m being fair and consistent with the whole team. What boundaries make sense for us?”

That’s it. Short, honest, specific. And it shows you care enough to be proactive. Trust me, your friend is already wondering how things are going to change. By being the first to bring it up, you take away the uncertainty and replace it with clarity.

2. Embrace Your New Role

You can still be friendly, but you can’t be “one of the gang” anymore. Accepting that reality is part of stepping into leadership.

This is where many new managers trip up. They cling to the old dynamic. They keep venting frustrations, gossiping, and oversharing with their closest colleagues. But once you’re the boss, those conversations hit differently. A joke about a coworker is no longer harmless — it’s favoritism. Complaining about company policy isn’t just blowing off steam — it’s sowing dissent.

And those side conversations? They never stay side conversations. They spread. They change perceptions. They chip away at your authority.

That doesn’t mean you need to become robotic. You can still laugh with your team. You can still celebrate wins. You can still be approachable. But you’re “leader first, friend second” now. And when you need to vent, find a new outlet—a mentor, another manager, or someone outside the company. Your team isn’t your sounding board anymore.

3. Stay Consistent to Avoid Favoritism

Fairness isn’t just a leadership principle—it’s a credibility shield. The quickest way to lose trust is to treat your friends differently than the rest of the team.

That doesn’t mean you’ll intend to play favorites. It’s usually subtle. Giving your old buddy more slack on a deadline. Asking them for input first in meetings. Grabbing lunch with them a little more often than with others. None of those things seem like a big deal, but your team notices. They always notice. And once they suspect favoritism, the dynamic of the whole team changes.

So be deliberate about how you lead. Rotate lunch invites. Keep feedback tied to measurable goals so everyone sees the standard is the same. Spread recognition evenly and shine the spotlight on the whole team, not just the familiar faces. Consistency protects your credibility and reinforces trust across the group.

4. Reevaluate Social Media Boundaries

Before you were the boss, your social media interactions were harmless — liking memes, posting weekend selfies, swapping DMs. But now? Those same interactions can be seen as bias or favoritism, and worse, they come with receipts.

A casual photo at a backyard barbecue? Favoritism. Liking a slightly edgy meme your friend shared? Bias. Responding privately to a rant about another teammate? Favoritism again — this time with screenshots. You don’t have to ghost your entire digital life, but you do need to tighten boundaries. Adjust privacy settings. Consider unfollowing or at least limiting interactions. Keep work and social media in separate lanes. And follow this rule of thumb: if you wouldn’t put it in a company email, don’t put it in a DM.

5. Focus on Connection Through the Work

One of the best parts about working with friends is the sense of connection. The risk, when you become their boss, is thinking you need to pull away completely to preserve fairness. But you don’t. You just need to redirect that connection into the work itself.

Research on prosocial motivation—our drive to protect and promote the well-being of others—shows that teams thrive when they’re bonded around shared purpose. That’s your new role: to cultivate connection not through gossip or side chats, but through collaboration, recognition, and shared wins.

Keep the relationships, but root them in the team’s mission. That way you’re not just holding on to friendships—you’re strengthening the team.

The Bottom Line

Managing your friends after a promotion is one of the trickiest leadership challenges you’ll face. If you pretend nothing’s changed, you’ll lose credibility. If you overcorrect, you’ll lose connection. The path forward is acknowledging the shift, embracing your new role, staying consistent, setting boundaries, and channeling friendship into shared purpose.

You don’t have to lose your friends when you become their boss. But you do have to lead them differently. And if you do it well, you won’t just keep your friendships — you’ll earn their respect.

Image credit: Gemini

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Customer Experience Audit vs. Customer Satisfaction Survey

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Why They Measure Different Things

Customer Experience Audit vs. Customer Satisfaction Survey

by Braden Kelley and Art Inteligencia

“We already survey our customers” is the single most common objection I hear when I raise the idea of an experience audit, and it’s a reasonable one on the surface — why pay for a second measurement of the same thing? The honest answer is that a survey and an audit aren’t measuring the same thing at all. They’re not even measuring in the same direction.

A survey measures what customers are willing to tell you

NPS, CSAT, and CES all share a structural feature: they depend entirely on a customer choosing to respond, and then choosing to be candid in that response. That’s not a flaw in the instrument — it’s simply what the instrument is. It tells you the sentiment of your most engaged customers (response rates skew toward people who feel strongly, in either direction) at a single moment, about the parts of the experience they happened to be thinking about when the survey arrived.

What it structurally cannot tell you: what happened to the customer who didn’t respond. What the friction actually looked like, step by step, that produced a “6” instead of a “9.” Whether a “9” from one customer and a “9” from another represent the same underlying experience, or two very different ones that both happened to land on the same number.

An audit measures what’s actually happening in the journey

An audit doesn’t ask customers to self-report — it walks the journey directly, the way a real customer experiences it, and documents what’s actually there. That distinction matters most exactly where surveys go quiet: the steps a customer takes for granted and never thinks to mention, the workaround they built without realizing it was a workaround, the moment where the process technically succeeded but took four times longer than it should have.

You can walk journeys for clients whose NPS had been flat, technically acceptable, for years — and find friction serious enough to explain real revenue loss, sitting in a step that had simply never come up in a survey response because no customer thought to complain about something they’d quietly adapted to.

Where each one actually earns its place

None of this makes the survey obsolete — it makes it a different tool for a different job. A survey is the right instrument for tracking sentiment trend over time, cheaply and continuously, across your whole customer base. It’s the wrong instrument for finding out why the trend is what it is, or for finding the friction nobody thought to mention.

An audit is the right instrument for that “why” — for producing a specific, prioritized map of where the experience actually breaks, ranked by business impact. It’s not something you run monthly; it’s something you run when the survey data has told you that something’s wrong without telling you what.

The tell that you need one, not the other

If your satisfaction scores have been flat — not declining, just plateaued — despite genuine effort to improve them, that’s usually the clearest signal that the problem lives somewhere the survey can’t see, and that more survey data won’t produce a different answer than the data you already have. That’s the specific situation an audit is built for.

If you want a rough sense of what that plateau might be costing before committing to a diagnosis, the CX ROI Calculator is a fast way to put a number on it. When you’re ready to find out exactly where the friction is living, that’s what a Customer Experience Audit is for.

Customer Experience Audit versus Customer Satisfaction Survey Infographic

Want to learn more about the value of having an independent Customer Experience Audit done? Or are you ready to invest in one?

Image Credit: Gemini, ChatGPT

Content Authenticity Statement: The topic area, key elements to focus on, etc. were decisions made by Braden Kelley, with a little help from Claude to clean up the article.

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The Leadership Journey

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The Leadership Journey

GUEST POST from Mike Shipulski

If you know what to do, do it. Don’t ask, just do.

If you’re pretty sure what to do, do it. Don’t ask, just do.

If you think you may know what to do, do it. Don’t ask, just do.

If you don’t know what to do, try something small. Then, do more of what works and less of what doesn’t.

If your team doesn’t know what to do unless they ask you, tell them to do what they think is right. And tell them to stop asking you what to do.

If your team won’t act without your consent, tell them to do what they think is right. Then, next time they seek your consent, be unavailable.

If the team knows what to do and they go around you because they know you don’t, praise them for going around you. Then, set up a session where they educate you on what you should know.

If the team knows what to do and they know you don’t, but they don’t go around you because they are too afraid, apologize to them for creating a fear-based culture and ask them to do what they think is right. Then, look inside to figure out how to let go of your insecurities and control issues.

If your team needs your support, support them.

If your team need you to get out of the way, go home early.

If your team needs you to break trail, break it.

If they need to see how it should go, show them.

If they need the rules broken, break them.

If they need the rules followed, follow them.

If they need to use their judgement, create the causes and conditions for them to use their judgement.

If they try something new and it doesn’t go as anticipated, praise them for trying something new.

If they try the same thing a second time and they get the same results and those results are still unanticipated, set up a meeting to figure out why they thought the same experiment would lead to different results.

Try to create the team that excels when you go on vacation.

Better yet, try to create the team that performs extremely well when you’re involved in the work and performs even better when you’re on vacation. Then, because you know you’ve prepared them for the future, happily move on to your next personal development opportunity.

Image credits: Pixabay

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Case Study – Innovating Around a Disruption

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Škoda built a bike bell that beats noise-cancelling headphones

Case Study - Innovating Around a Disruption

GUEST POST from Jason Hauer

A near-miss on a London street became Škoda’s smartest marketing spend in years. The bigger idea: someone else’s AI has broken something in your category too, and fixing it might be your next growth play.

Ben Fraser was walking to work near Borough Market, headphones on, when a cyclist nearly hit him. The cyclist had been ringing his bell the whole way down the street. Fraser never heard a thing.

Fraser works at PHD Media, and the near-miss became a brief. Transport for London data showed bike-pedestrian collisions rose 24% in 2024, with cyclists set to outnumber car drivers in London for the first time this year. One quiet contributor: active noise cancellation. The bike bell had worked for a century. On a growing share of pedestrians, it simply stopped working, because an algorithm in their headphones was scrubbing it out of the air.

Škoda, the Czech carmaker owned by Volkswagen Group and one of Europe’s biggest auto brands, took the problem to acoustics researchers at the University of Salford. Testing turned up something useful: noise-cancelling algorithms struggle with a narrow band between 750 and 780 hertz. So Škoda built the DuoBell, a second resonator tuned to that gap, plus a hammer that strikes in an irregular rhythm the algorithms can’t predict. Fully mechanical. A piece of metal designed to beat software.

They tested it with a fleet of Deliveroo riders in London, people whose income depends on being heard in traffic. One rider said that with the bell, he finally had a voice in the streets. The riders wanted to keep them.

Pedestrians in noise-cancelling headphones gained up to five extra seconds of reaction time and up to 22 metres of additional distance. Roughly four times the cut-through of a standard bell. Škoda published the underlying research as an open-source white paper, and the work took Silver in Creative Data at Cannes in June. One case-study breakdown projects €79 million in vehicle sales connected to the project, which fits how the company sees it. Škoda started life as a bicycle maker in 1895 and still sponsors the Tour de France. The fix sits inside a hundred-year-old brand truth.

Nobody at the headphone companies set out to make cyclists invisible. Noise cancellation was a good product decision that quietly broke a safety system in a completely different category, and the breakage sat unowned for years while collisions climbed. That pattern is everywhere now. Every AI deployment of the last three years created some downstream effect in somebody else’s business.

Somebody is absorbing that cost right now, and no line item owns it.

Look at your own category through that lens. A century-old bell stopped working because ears started running software. Every signal your company sends was built the same way, for a human on the receiving end, and a machine now sits between you and that person. Your buyer’s first impression of you is written by a model you’ve never briefed. Everything you send after that runs through software tuned by companies with no stake in whether you’re heard. Somewhere in that chain, something that worked in your category for decades is being scrubbed out of the air, and the loss surfaces in a metric you’ve been explaining some other way. The collision numbers sat in Transport for London’s data before anyone thought to blame headphones. Your version of that number already exists. It’s in a dashboard right now, filed under something else.

Škoda’s move was to treat the breakage as a market. Find the gap, spend the budget on fixing it, and let the fix carry the brand. The bell exists because someone measured a frequency nobody had bothered to look for.

Skoda DuoBell statistics

WHAT TO DO THIS WEEK

The first conversation moved. Your customer now asks a model before they ask you, whether that’s a buyer building a shortlist or a client second-guessing your advice. This week, put your customers’ most common questions to the major models, worded the way they’d word them. What comes back is your new first impression.

The unfiltered channels are still open. Every digital signal you send now clears someone else’s software before a human sees it. Nothing stands between a room and the people in it. Škoda answered an algorithm with a piece of metal; your equivalent might be a dinner, or a printed report that lives on a desk for a month. Pick the one message this quarter that can’t survive being flattened and spend real money delivering it by hand.

The next breakage is already in somebody’s data. The collision numbers sat in Transport for London’s files before anyone blamed headphones. Spend an hour with your team on two questions. What have our own AI deployments broken for the people downstream, the customer who needed a person, the partner whose emails our triage now buries? And what’s degrading in our category that nobody has claimed yet? One of those answers is a liability you can still price before a competitor does. The other is a bell nobody has built.

Whatever you find, take it all the way to metal. Škoda could have stopped at the white paper. The bell is the reason you’re reading about them.

A century-old bell needed one new frequency to work again. Your category has a gap like that somewhere.

What’s quietly stopped working in your category?

Image credit: Jason Hauer

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10 Ways to Build Customer Trust in Customer Experience

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10 Ways to Build Customer Trust in Customer Experience

GUEST POST from Shep Hyken

This article answers the question: Are organizations not only paying attention to the feedback customers give but also to the feedback they unintentionally withhold?

In the past few months, I’ve been writing and speaking about how trust fits into the customer experience. Trust is earned, and once earned, it results in a customer who has confidence to keep doing business with you. I created a metric, the Customer Confidence Score (CCS), to measure how much a customer trusts you. So, let’s say the customer gives you a 10 on a scale of 1-10. Why do they give you that perfect score? Here are ten reasons why:

  1. You Keep Your Promise: This is simple. You do what you say you will do, and always when you say you will.
  2. Fixing and Owning Mistakes: You don’t make excuses and blame others. You simply focus on fixing whatever needs fixing.
  3. Transparency: There are no surprises, such as hidden fees or rules hidden in small print.
  4. You Protect Your Customer’s Data: Your customer’s privacy and security aren’t negotiable. How the customer’s information and data are protected and how breaches are handled will add to your customer’s trust. Customers must know you guard their information.
  5. You Show Respect: Treat your customers with dignity, respect, and appreciation. This builds trust.
  6. You Embrace Feedback: Your customers know their voice matters. You listen and act on their feedback, and, just as important, you acknowledge them for sharing it.
  7. You Give Back: A company that has a social cause or gives back to the community enjoys more trust than companies that don’t.
  8. You Don’t Take Advantage of Customers: Your customers never feel manipulated by sales tactics, small print, or anything that makes them feel uncomfortable or taken advantage of.
  9. Consistency: When customers do business with you, they know what to expect.
  10. Ethics: This is non-negotiable. There should never be any question about your ethics.

Customer Trust Formula Cartoon

Bonus: Give the customer a great customer service experience. Our annual customer service and CX research found that 83% of customers said that a good experience increases their trust in the person or company they are doing business with.

Trust is more than a business strategy. It’s a promise you keep every day. It is part of your company’s DNA. When customers trust you, they believe in you. They become your fans, your evangelists, and your best source of growth. Earning trust isn’t about one big moment. It’s built over a period of time when your customers know their experience is consistent, you’ll keep your promise, and you’ll do what’s right. Do that and your customers will say, “I’ll be back!”

Special Bonus: If you want a copy of a short eBook I created on the Customer Confidence Score, go to www.Hyken.com/customer-confidence-score.

Image Credits: Gemini

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Category Creation

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Category Creation

GUEST POST from Geoffrey Moore

Category creation is a critical success factor for start-ups bringing to market a disruptive innovation that calls for a new ecosystem, to support a new class of use cases, funded by a new budget line item. If the category does not form, the start-ups have no place to hang their hat. They can acquire early adopter customers via a bespoke project approach, but they cannot scale any further without help from the rest of the marketplace.

Similarly, established enterprises in mature categories also need to find new venues for growth if they are to break free from their value-investor-set market caps and create net new shareholder value. Whether through acquisition or in-house innovation, they, too, can have the challenge of category creation. So, in both cases, companies need to reengineer the marketplace in order to realize their ambitions. The question is, what would make the marketplace want to lean in?

Marketplaces are made up of ecosystem players, be they partners, competitors, or an installed base of customers. All these constituencies keep their eyes out for disruptive developments that could either benefit or jeopardize their future performance. The early adopters are typically motivated by the benefits, seeking a first mover advantage, while the early majority normally takes a wait-and-see approach, thereby creating a chasm, which in turn can be crossed wherever there is an urgent customer problem that is resisting standard solutions and thus warrants taking a novel approach to solve it. If the category does show it is getting traction, then all those wait-and-see pragmatists will begin to feel threatened by FOMO (Fear of Missing Out), and that is what creates a tornado of demand that puts the category permanently on the map.

Okay, so there is reason to believe that under the right circumstances, markets will support the creation of a new category. That said, we should not underestimate the power of inertia. Markets do not welcome transformational changes with open arms. Indeed, their default move is to deflect most attempts. What we need is a proven playbook. Fortunately, there is one, written some forty years ago, written by an old boss of mine, Regis McKenna.

The Regis Touch

It is hard to overstate the impact that Regis had on high-tech marketing, especially in its early days when it was trying to break free from advertising as its primary medium. At the time, the tech sector was just emerging, the bulk of spending was in B2B markets, the focus was on automating core business processes, and every buying decision entailed considerable risk, not only in terms of the product and vendor’s staying power but also in terms of the impact of the business processes themselves. As a result, advertising per se was not sufficiently informative or credible to drive purchasing. Regis saw this and, with the help of a talented set of consultants and communications professionals, developed a public-relations-led approach that successfully launched hundreds of new products and created dozens of new categories.

The key to his approach was a framework called the infrastructure model that organized the various audiences and constituencies that make up a marketplace in what one might call a ladder of communications:

Relationship Marketing Infrastructure Model Geoffrey Moore

Here’s how it works. The goal is to convert prospects into customers. In B2B markets, those prospects organize around three centers of interest—the technology itself, the impact on productivity, and the financial returns. These prospects get their information most directly from the media, the technologists from the technical press, the end users these days from social media (no such thing, of course, back in the day), and the executives from the business press. The agents of the press, in turn, get a lot of their information from opinion leaders, be they the industry analysts for the technical press, the influencers for social media, or the financial investment analysts for the business press. Those opinion leaders, in turn, get their information from their engagement with the marketplace itself, be they customers, partners, or competitors already involved with the disruptive innovation.

The point is, any claims about the disruptive innovation are verified and validated by working down this model, which means any communications program should organize around working up the same model. Skipping over any one of these audiences and going straight to the prospects directly—the way advertising does—is bound to fail because you have not got your references lined up and sufficiently informed to support and endorse a high-risk buying decision. Product launches and category creation initiatives, therefore, work up this ladder of communications, rung by rung, starting in the executive suite, moving from there to the product organization, and from there to the go-to-market team. That team, in turn, needs to start with educating the ecosystem players, typically with talks and panel sessions at industry conferences, then connecting with the opinion leaders, typically via one-on-one briefings that end up being two-way dialogs, and only then out to the media that will engage with the target prospects.

Category Creation Playbook

A lot of what would go into a complete playbook is product and market-specific, but there are audience-centric principles that remain relatively constant. The key question in each case is, what is it about the emerging category that would be of interest to this particular constituency? With that in mind, here is a brief take:

  1. Executive team. This team will value growth to boost market cap, something that participation in an emerging category can be expected to deliver, but it may well be reluctant to take transformational risk to achieve it. If this team is not 100% behind the effort, don’t start, as every other rung on the latter ultimately calls for investments that this team must endorse.
  2. Product team. This team has to be all in for a wild ride—and usually is. You have to pressure test their claims nonetheless, as they can often get over their skis, promising more than they can deliver within the window that matters.
  3. Go-to-market team. This team requires maturity and patience. The big sales commissions won’t come until the category enters the tornado, so for now, the focus is on creating a market, not harvesting it. That means paying deep attention to developing the ecosystem, including bringing along the installed base, helping to engage and enlist partners, and (oddly enough) encouraging competitors. The last one is important because, ultimately, a category is defined by a set of competitors, not just one company, so for a healthy growing category you need to have peers that are winning too—hopefully in target market segments that are distinct from yours.
  4. Ecosystem. These are the people your go-to-market team is engaging with. The sales team has the installed base, the business development team, the partners, and the marketing team, the competitors. The goal is to get everyone speaking from their own perspective to reinforce your story that something big is underway. One item of note: With respect to competitors, marketing needs to develop a narrative that has room for more than one winner while at the same time staking out turf where your own differentiation makes you the obvious choice. What you do not want to do is bad-mouth the other team’s products—that will create anxiety that will cause everyone to wait and see some more. So, save your sharp tongue for when you get inside the tornado—that’s the no-holds-barred battleground where a well-placed elbow can make a real difference.
  5. Opinion leaders. The goal here is to get conceptual endorsement for the claims you will be making via the media. Opinion leaders need to maintain their independence and do not want to shill for you or anyone else. What they do want to do is look intelligent and have something differentiated to say. What they want from you is enough context to do their job and no interference thereafter. In addition, opinion leaders want to share their opinions with you, in part to influence your future investments, and so it is just as important to listen and ask them questions as it is to present your own story. With respect to your presentation, demos can be useful, but repurposing a customer sales pitch is not, as this audience is not going to buy your product but rather is going to opine on the reasons why other people might.
  6. Media. This is the means by which you will communicate with the three prospect audience types—the technical team, the end users, and the executive sponsors. Each has a preferred media type—industry press, social media, and business press—and each of these types wants to be treated in its own special way. The technical press wants to talk about the product itself. They want facts, love demos, and like to talk to specialists more than generalists. They also are often happy to beta test products or get any other kind of advanced notice as to what’s coming next. Social media wants to talk about the applications of the product, and the ways in which it will impact end users’ lives. So demos can work here only if they are in service to an end-user story as opposed to a run-through of all the features and functions. The business press wants to talk about the “size of the prize,” the impact of the new technology on productivity, how it will reengineer bottlenecking processes, and thus how much trapped value it will be able to release. Demos are wasted here, but PowerPoint can help a lot.
  7. Prospects. When category creation is the focus, it is important to engage the three types of prospects in the right order. If the technology is outrageous, you need to start with the technical audience first just to earn the right to talk to anyone else. If it is not outrageous, then the executive sponsor needs to be your first port of call. The reason is that the other two audiences will actually be willing to meet with you to learn about the latest and greatest thing, but they will have budget, not permission to get new budget, if the executive sponsor is not on board. So a typical path through a major account would start with an executive from your company having a conversation with the prospective executive sponsor at your target customer, which would lead to a referral to the technical team to test your bona fides, and then on to the end-user team, to validate your productivity claims. Proof-of-concept projects are necessary at the very beginning, but one of the major milestones in category creation per se is to generate enough marketplace acceptance that future prospects will forgo these tests.

To sum up, category creation is an outbound communications effort to orchestrate a coalition of the willing across a laddered set of constituencies, each with its own set of interests. The goal is to build an inbound path of verification that reinforces the new category’s right to existence. Trying to shortcut the outbound process by skipping over one or more audiences will defeat the purpose, as any doubts raised this early in the game result in lost momentum that can never be recovered. There is no magic here, but patience and discipline are required.

That’s what I think. What do you think?

— Image credit: Pexels

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