Tag Archives: politics

How to Build a Local Value Score Without Starting a Partisan Firefight

How to Build a Local Value Score Without Starting a Partisan Firefight

by Braden Kelley and Art Inteligencia

In the first piece in this series, we lit the spark: absolute spending debates rarely move the needle, while peer-relative value, what similar communities achieve per dollar, can. This article opens the instrument. Not the full DIY toolkit yet. The method. The experience architecture. The discipline that turns civic anger into civic learning.

From spark to instrument

Innovation without an instrument is just a mood. Human-centered change without a shared unit of sense-making becomes another round of tribal theater. If you felt the first article land – What If You Could Prove the Government is Ripping Us Off? – the next question is practical:

How do we score a place fairly enough that good-faith people on the left, right, and exhausted middle can argue about the same dashboard?

That is an experience-design problem before it is a political problem. People cannot improve what they cannot sense. So we need an interface for civic value that ordinary neighbors can understand in under two minutes, and that a finance director can challenge without inventing motives.

Call the instrument a Relative Value Score (RVS): a transparent, peer-normalized view of outcomes per cost-adjusted dollar, with a clear path to “why the gap.” The revolutionary move is not inventing a grade that flatters your side. It is building a comparison citizens trust enough to use in budget season.

What a Relative Value Score actually measures

A Relative Value Score is not “how big is the budget?” Bigger places spend more. Harder case mixes cost more. Expensive labor markets pay more. Treating raw spend as proof of compassion, or of waste, is how we keep fighting about identity instead of delivery.

Conceptually:

RVS ≈ how close you are to the best peer in your cohort on value delivered per dollar—across a small set of outcome domains, cost-adjusted, with published weights and sources.

Think of it like comparing restaurants of the same type and price band on food quality per dollar, not comparing a food truck to a banquet hall and declaring a winner by total receipts. Futurology loves flashy national indexes. Experience design prefers local instruments that feel fair in the neighborhood where life is actually lived.

Three design rules keep the score human-centered:

  • Outcomes over optics. Prefer measurable delivery (response times, learning growth, pavement condition, permit latency, unit cost of capital) over press-release volume.
  • Cost-adjusted dollars. Adjust for regional price and wage differences so “expensive place” is not automatically “bad place.”
  • Relative, not absolute holiness. Normalize within the peer cohort. The best peer becomes the teacher. Everyone else gets a gap to close—or explain.

Improper payments, fraud risk, and opaque grantee chains still matter. They belong on a related but separate track (more below). Mixing “inefficient” with “corrupt” in one opaque number is how movements lose the room on the first contested claim.

Peers first: the fairness engine

Most “benchmarking” fails before the math starts—because the peer set is a vibes playlist. Comparing a dense coastal city to a rural county, or a high-poverty district to an affluent one using unadjusted test levels, is not accountability. It is ammunition.

Peer cohorts are the fairness engine. Build them first. Argue about them in public. Version them. That is change leadership: put the contested assumptions where people can see them.

Practical cohort dimensions by layer:

  • Cities: population band, density, metro/rural context, regional price/wage index.
  • Counties: population, urban share, mandate set (courts, jails, public health, roads, elections).
  • States: population scale, economic mix, federal transfer share—used carefully; states are multi-product machines.
  • School districts: enrollment, % students in special education / English learners / free-or-reduced lunch (or equivalent need measures), urbanicity, regional educator wages. Prefer learning growth / value-add over raw proficiency levels whenever possible.
  • Water and special districts: service population, infrastructure age/type, treatment complexity, geography—unit cost of delivered service beats “total budget” every time.

A good peer set is small enough to be intelligible and large enough that one outlier cannot redefine “normal.” Publish who is in the cohort and why. Invite the entity to propose alternate peers with evidence. Right-to-reply is not weakness. It is how trust compounds.

Domains, weights, and the “why the gap” story

Do not boil the ocean. Innovation teams ship thin slices. For a first local scorecard, pick 8–12 metrics max across a few domains—not 200 indicators nobody reads.

Example domain shapes (customize by entity type):

  • Service delivery: outcomes or service quality per dollar or per FTE (clearance, response, throughput, condition).
  • Administrative load: central office / admin share versus program or instructional spend.
  • Labor intensity: compensation density (payroll, overtime, benefits where available) versus outputs.
  • Contracting & capital: competitive bid share, concentration, unit cost and schedule slippage on comparable projects.
  • Transparency: timely CAFRs/budgets, machine-readable checkbooks, FOIA latency—inputs to trust, not vanity.

Weights should be public, few, and revisable. Publish a default weighting, and let citizens toggle sensitivity modes (“weight learning growth higher,” “weight admin share higher”) so critics can fork the story without assassinating the messenger. That is open innovation applied to civic sense-making.

The score is the headline. The product is the “why the gap” decomposition: which 2–3 drivers explain most of the distance from the best peer, each with sources and confidence. Without that story, a score is just a ranking for dunking. With it, a score becomes a change agenda.

Two tracks: performance vs. integrity

Human-centered accountability refuses false equivalence. A district can be expensive relative to peers and still honest. An agency can look “lean” on paper and still run integrity red flags. Smash those into one “corruption score” and you have built a weapon, not an instrument.

Keep two panels on the same dashboard:

  • Performance track (RVS): peer-relative outcomes per cost-adjusted dollar. This is the main civic interface.
  • Integrity overlay: audit findings, delayed reporting, sole-source patterns, related-party flags, outcome-light grantee chains—shown with higher evidentiary bars, source documents, and room to reply. Treat AI here as a highlighter for human review, never as a judge pronouncing guilt.

This separation is how a multipartisan movement survives contact with reality. Precision is the revolutionary ethic. Smear is the cheap substitute.

A weekend walkthrough for one jurisdiction

You do not need the full toolkit to practice the method. You need a first mile. Here is a human-sized walkthrough you can start this weekend—before the downloadable suite and guidebooks ship.

  • 1. Name the entity in one sentence. “Our K–12 district,” “our city general fund,” “our water district”—passion plus a border beats rage at “the system.”
  • 2. Pull Tier-A documents. Latest adopted budget, CAFR or annual financial report, salary schedule or checkbook export, and any published outcomes dashboards. Note what is missing.
  • 3. Draft a peer shortlist. Five to fifteen similars using the cohort dimensions above. Write one paragraph defending the set.
  • 4. Choose eight metrics you can source. Prefer unit costs and outcomes over vibes. If a metric cannot be sourced, park it—do not invent it.
  • 5. Build a crude gap view. For each metric, who is best in your peer set? Where are you? What is the story in two drivers?
  • 6. Separate integrity notes. If you see red flags, log them with links and confidence—not as the score itself.
  • 7. Write three budget-season questions. Short enough for a three-minute public comment. Specific enough that staff must answer on the record.

That walkthrough is reconnaissance, not a finished product. Finished products need versioned methods, entity right-to-reply, and consistent cohort rules. That is exactly what the forthcoming DIY tools and role-based guidebooks are for—so local teams are not reinventing discipline in the dark.

What comes next—and how to stay in formation

Method without movement is a PDF nobody uses. Movement without method is a mob with a megaphone. We are building both: open instruments for peer-relative value, and a network of roles—data gatherers, benchmarking intelligence creators, website hosts, promoters, meeting advocates, media partners—who can stand up local scoreboards when the kits are ready.

In the next pieces in this series, we will walk a single jurisdiction end-to-end as a chapter-lead story, then open the downloadable suite: data gathering, careful AI-assisted processing under human guardrails, and public benchmarking sites neighbors can actually use.

Between method and toolkit, stay on the bus.

If this article sharpened your sense of how fair comparison should work, subscribe to Human-Centered Change & Innovation Weekly. That list is how you get first notice when the guidebooks and DIY tools move from spark to usable firepower—practical next steps for the jurisdiction and role you choose.

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Forward this to the person who already knows the peer set in their head—and to the person who keeps saying the comparison “isn’t fair” without ever defining fair. Fairness is designable. That is the work.

Absolute spend is a slogan. Peer-relative value is an instrument. Instruments are how human-centered futures get built.

Frequently Asked Questions

What is a Relative Value Score (RVS)?

A Relative Value Score is a peer-normalized measure of outcomes per cost-adjusted dollar for a city, county, state, school district, or special district. It shows how close an entity is to the best performer among similar peers across a small set of transparent metrics—not whether its total budget is large or small in absolute terms.

How do you choose fair peers for comparison?

Fair peers share similar constraints: size and density for cities; mandate mix for counties; enrollment and student-need mix plus regional wages for school districts; service population and infrastructure profile for water and special districts. Publish the cohort rules, keep the set large enough to be meaningful, and allow entities to propose alternate peers with evidence. Unadjusted “leaderboards” that ignore poverty or cost of living are not fair benchmarks.

Should fraud and performance be one score?

No. Keep a performance track (peer-relative value) separate from an integrity overlay (audits, delayed reporting, sole-source patterns, opaque grantee chains) that requires stronger evidence and human review. Combining them into one “corruption score” destroys credibility and unfairly smears underperforming but honest agencies.

Image Credits: Pexels

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

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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Business Leaders Must Learn About Political and Social Movements

Business Leaders Must Learn About Political and Social Movements

GUEST POST from Greg Satell

Business leaders have long been fascinated by the military. When Alfred Sloan created the modern corporation at General Motors, he based it on the army. In Wall Street, the antihero Gordon Gecko habitually quoted Sun Tzu. Retired generals like Stanley McChrystal earn huge fees advising CEOs and speaking to corporate conferences.

But what about nonviolent conflict? Research has shown non-violent movements are far more successful than violent uprisings, prevailing against powerful regimes against seemingly insurmountable odds. Yet, apart from a stray Gandhi quote here or Martin Luther King Jr. slide there, these go largely unexamined in the business world.

That’s a mistake. As I explained in Cascades, business leaders can learn a lot from the principles of social and political movements. There is abundant scholarship, going back decades, about why efforts succeed and fail. We know what works and what doesn’t. If you’re serious about being a transformational leader, you need to understand these strategies.

We Need To Learn About Not Only Successes—But Failures Too

Organizations are often inscrutable and hard to research. That’s why the preferred mode of analysis is case studies in which insiders are interviewed and a particular situation is interpreted by investigators. These can be helpful, but they also have severe limitations.

First, with shareholders and customers to please, managers are rarely eager to talk about failures. So we usually only hear about successes. Those, of course, are important but also subject to survivorship bias. For example, if a risky strategy results in 1% of the firms being wildly successful and 99% going out of business, then we’ll tend to hear glowing accounts of that lucky 1% and we’ll miss the vast majority that flamed out.

Social and political movements, on the other hand, are largely public events. Gandhi’s Himalayan miscalculation is just as well documented as his triumphant Salt March. We know as much about the failures of #Occupy as we do the ultimate success of the LGBTQ movement. We can look at similar strategies in different contexts and different strategies in similar contexts.

That’s extremely important. We need to learn from failures. It’s one thing to look at a strategy that succeeded, but can it prevail consistently or was that a one-off? Is it a universally successful strategy or highly dependent on context? We need to ask these questions relentlessly and it’s very hard to do that if we only look at the winners.

Change Is Always Multifaceted, We Need to Understand Multiple Perspectives

Another issue with the case study method is that it is necessarily limited. When researchers did a case study on company I used to run, to take just one example, they interviewed insiders (including me) and did their best to interpret what they heard and what they could glean from background information regarding the market.

Yet while I don’t think anything was inaccurate, it wasn’t exactly the truth either. Only a handful of people were interviewed, almost all of them were concentrated in a single part of the business and none of them, besides me, were involved in making decisions. The issues presented in the case study simply weren’t the ones we were actually wrestling with.

Now consider the prominent sociologist Doug McAdam’s paper on recruiting for Freedom Summer during the civil rights movement. He was able to analyze the applications of not only 720 volunteers, but 239 others that withdrew and 55 that were rejected. He conducted 80 in-depth personal interviews and, because the applications asked for social contacts, McAdam was able to document social ties.

That type of documentation simply doesn’t exist in case studies of firms’ internal deliberations and decision making. We rarely get access to internal data, much less insights from partners, customers, competitors and regulators. With social and political movements, on the other hand, we can examine thousands of first-hand accounts from every perspective.

That’s important, because the world is a messy place with a lot going on. Outcomes rarely boil down to a single decision and even key players disagree on which factors were determinant.

We Need To Overcome Resistance

Look at most change management models and what you see is mostly advice that is focused on persuasion. They suggest that the way to drive a transformation is to tell people about it. By creating a sense of urgency and need, you can build a coalition that will implement the change and shift practices for the long term.

Unfortunately, decades of serious research shows that the world doesn’t work that way. Researchers have long been aware of a so-called KAP-gap in which shifts in “knowledge” and “attitudes” don’t necessarily lead to a change in “practices.” For any given change there will also be people who will vehemently resist it, not for any rational logic, necessarily, but for reasons related to identity, dignity and sense of self.

On the other hand, in social and political movements the need to overcome robust—and even violent—resistance is front and center. Practitioners have developed tools such as the Spectrum of Allies and the Pillars of Support as well as innovative strategies like Dilemma Actions. We have decades of documentation on how these worked in a variety of contexts.

Make no mistake. We can’t simply cheerlead change. No one is going to embrace transformation simply because you came up with a fancy slogan. The truth is that whenever you ask people to change what they think or what they do, there will always be some who won’t like it and they will work to undermine what you’re trying to achieve in ways that are dishonest, underhanded and deceptive.

You need to prepare for that and you will learn far more from social and political movements than consultants interpreting case studies.

Change Is Too Important Not To Take Seriously

The most important challenge leaders face is to navigate change. We can optimize operations, streamline our organizations and motivate our people, but eventually our square-peg business will meet its round-hole world and we will need to adapt, build new skills and shift our strategies. Unfortunately, the overwhelming evidence suggests that we will fail.

Consider that, after decades of trying, skills like lean manufacturing, agile development and overcoming unconscious bias are woefully under-adopted in most organizations. Study after study shows that the vast majority of transformational efforts fail. We can’t continue to do the same thing and expect different results.

One reason for this dismal performance is how we research and learn about change. Today’s change management models simply aren’t based on facts or evidence, but rather the interpretation of case studies. Those can help us understand nuance and give us greater depth, but they are no substitute for rigorous research.

The truth is that we know a lot about change. Decades of studies have shown us that new ideas tend to come from outside the community and incur resistance. Research has shown there is a persistent gap between what people know and what they actually put into practice. We also know that transformation follows an s-shaped curve and that ideas are transmitted socially.

Unfortunately, current organizational change practices address none of these challenges. However, social and political movements do and through the work of scholars like Gene Sharp and practitioners Srdja Popović we know what works and what doesn’t. My own work has shown that these principles can be put to use in organizations.

The future is simply too important to be left to superstition and fantasy.

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

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When Survival Crowds Out Creativity: How Affordability Crises Undermine Innovation

An exploration of how rising costs of living reduce cognitive surplus, suppress innovation, and limit organizational and societal progress.

LAST UPDATED: January 19, 2026 at 4:43 PM

When Survival Crowds Out Creativity: How Affordability Crises Undermine Innovation

GUEST POST from Art Inteligencia

I am frequently asked about the ingredients of a successful innovation ecosystem. We talk about venture capital, high-speed internet, patent laws, and university partnerships. But we rarely talk about the most fundamental requirement of all: human physiological and psychological security.

Innovation is not a purely intellectual exercise; it is an emotional and biological one. It requires a specific state of mind — one that is open, curious, and willing to embrace the possibility of failure. However, when a society faces systemic affordability challenges — skyrocketing rents, food insecurity, and the crushing weight of debt — we are effectively taxing the cognitive bandwidth of our greatest resource: people.

“Innovation is not a luxury of the elite, but a byproduct of a society that provides its citizens enough stability to dream. When we price people out of their basic needs, we price ourselves out of our future.” — Braden Kelley


The Cognitive Tax of Scarcity

To understand why affordability kills innovation, we must look at how the human brain functions under stress. Human-centered innovation is rooted in the idea that people solve problems when they have the mental “slack” to do so. When an individual is constantly calculating how to cover a 30% increase in rent or skipping meals to pay for childcare, they are operating in survival mode.

In survival mode, the brain’s prefrontal cortex — the center for higher-order thinking, long-term planning, and creative synthesis — takes a backseat to the amygdala. We become more reactive, more short-term focused, and significantly more risk-averse. You cannot disrupt an industry when you are terrified of an eviction notice.

This “scarcity mindset” creates a hidden drain on productivity and creativity. It is a form of Innovation Debt that we are accruing as a society, where the interest is paid in ideas that were never born because the potential innovators were too exhausted to think of them.

In organizations, this manifests as:

  • Employees avoiding bold ideas for fear of failure
  • Reduced participation in innovation programs
  • Higher burnout and turnover among creative talent
  • A preference for incrementalism over experimentation

“Innovation requires slack — slack in time, money, attention, and emotional safety. When survival becomes the primary occupation, imagination is the first casualty.” — Braden Kelley


Case Study 1: The Silicon Valley “Talent Flight”

The Situation

For decades, Silicon Valley was the undisputed epicenter of global innovation. However, by the early 2020s, the median home price in the region exceeded $1.5 million. While established tech giants could afford to pay engineers high salaries, the support ecosystem — the teachers, the artists, the junior researchers, and the “garage tinkerers” — could not.

The Innovation Impact

Innovation thrives on cross-pollination. When only the wealthy can afford to live in a hub, the diversity of thought collapses. We began to see a “homogenization of innovation,” where new startups focused almost exclusively on problems faced by high-income individuals (e.g., luxury delivery apps) rather than solving systemic human challenges. The high cost of living created a barrier to entry that effectively barred the next generation of “scrappy” innovators who didn’t have a safety net or venture backing.

The Result

Data showed a significant migration of talent to “secondary” hubs like Austin, Denver, and Lisbon. While this decentralization has benefits, the initial friction and lost momentum in the primary hub represented a massive opportunity cost for breakthrough research that requires physical proximity and intense collaboration.


The Death of the “Garage Startup”

The “garage startup” is a cherished myth in innovation circles, but it relies on a very real economic reality: the availability of low-cost, low-risk space. Hewlett-Packard, Apple, and Google all started in spaces that were relatively cheap to rent or own.

In today’s urban environments, that “low-risk space” has vanished. When every square foot of a city is optimized for maximum real estate yield, there is no room for the inefficient, messy work of early-stage experimentation. We are replacing “maker spaces” with luxury condos, and in doing so, we are dismantling the physical infrastructure of the Fail Fast philosophy. If the cost of your “lab” (your garage or basement) is $3,000 a month, you cannot afford to fail. And if you cannot afford to fail, you will never truly innovate.


Case Study 2: Food Insecurity in the Academic Pipeline

The Situation

A 2023 study of graduate students in North America revealed that nearly 30% experienced some form of food insecurity. These are the individuals tasked with the most rigorous scientific and social research — the literal “R” in R&D.

The Innovation Impact

Graduate students are the primary engine of university-led innovation. When these researchers spend their nights worrying about calorie counts instead of quantum counts, the quality of research suffers. The persistence required to push through a failed experiment is diminished when physical health is compromised.

The Result

Universities noted a decline in “high-risk, high-reward” thesis topics. Students began gravitating toward “safe” research areas with guaranteed funding or clear paths to corporate employment to pay off student loans and eat. The “Failure Budget” for these young innovators was effectively zero, leading to a stifling of the very exploratory research that historically leads to major scientific breakthroughs.


Case Study 3: A Manufacturing Firm’s Productivity Paradox

A mid-sized manufacturing company invested heavily in digital transformation and innovation training, yet saw minimal improvement in idea generation or experimentation. Leadership initially blamed culture and skills.

A deeper assessment revealed a different root cause: nearly 40 percent of the workforce was experiencing food or housing insecurity. Employees were working second jobs, skipping medical care, and managing chronic stress.

The company shifted strategy. It introduced wage stabilization, subsidized meals, and emergency financial support. Within twelve months, participation in continuous improvement programs doubled, and frontline innovation proposals increased by over 60 percent.

Innovation did not fail due to lack of tools. It failed due to lack of breathing room.


Why Affordability Shapes Risk Appetite

Innovation requires people to take risks that may not pay off immediately. But when the margin for error is razor-thin, risk becomes reckless rather than courageous.

Employees who fear eviction or medical debt are far less likely to:

  • Challenge entrenched assumptions
  • Experiment with unproven ideas
  • Advocate for long-term investments
  • Speak candidly about systemic flaws

Affordability challenges quietly turn organizations into compliance machines rather than learning systems.


Conclusion: A Call for Human-Centered Policy

If we want to maintain a competitive edge in a rapidly changing world, we must view affordability as an innovation policy. Rent control, affordable housing, student debt relief, and food security are not just “social issues”; they are the foundational layers of a healthy innovation funnel.

We need to create “slack” in our systems. We need to ensure that the next great thinker is not working three gig-economy jobs just to keep the lights on. As leaders, we must advocate for a world where people are free to use their entire brain for the work of change, rather than wasting half of it on the math of survival.

True innovation starts with a simple human truth: A mind preoccupied with where to sleep cannot dream of how to fly.


Frequently Asked Questions

Q: How do high housing costs impact an organization’s innovation potential?

A: High housing costs force talent to relocate or spend a disproportionate amount of cognitive energy on survival. This reduces “cognitive bandwidth,” making employees more risk-averse and less likely to engage in the creative problem-solving or “intrapreneurship” required for organizational growth.

Q: What is the “Cognitive Tax” of affordability challenges?

A: The cognitive tax is the mental drain caused by financial stress. When individuals are worried about basic needs like food and rent, their prefrontal cortex — the area responsible for complex decision-making and creativity — is overwhelmed by the stress of survival, effectively lowering their functional IQ and creative output.

Q: Can innovation survive in an environment of economic scarcity?

A: While scarcity can occasionally breed “frugal innovation,” systemic affordability challenges generally stifle breakthrough innovation. Breakthroughs require “slack” — time, resources, and mental space — to experiment and fail. Without basic economic security, individuals cannot afford the risk of failure.

Disclaimer: This article speculates on the potential future direction of society based on current factors. It is hard to predict whether commercial, political and charitable organizations will respond in ways sufficient to alter the course of history or not.

Image credits: ChatGPT

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We Must Hold AI Accountable

We Must Hold AI Accountable

GUEST POST from Greg Satell

About ten years ago, IBM invited me to talk with some key members on the Watson team, when the triumph of creating a machine that could beat the best human players at the game show Jeopardy! was still fresh. I wrote in Forbes at the time that we were entering a new era of cognitive collaboration between humans, computers and other humans.

One thing that struck me was how similar the moment seemed to how aviation legend Chuck Yeager described the advent of flying-by-wire, four decades earlier, in which pilots no longer would operate aircraft, but interface with a computer that flew the plane. Many of the macho “flyboys” weren’t able to trust the machines and couldn’t adapt.

Now, with the launch of ChatGPT, Bill Gates has announced that the age of AI has begun and, much like those old flyboys, we’re all going to struggle to adapt. Our success will not only rely on our ability to learn new skills and work in new ways, but the extent to which we are able to trust our machine collaborators. To reach its potential, AI will need to become accountable.

Recognizing Data Bias

With humans, we work diligently to construct safe and constructive learning environments. We design curriculums, carefully selecting materials, instructors and students to try and get the right mix of information and social dynamics. We go to all this trouble because we understand that the environment we create greatly influences the learning experience.

Machines also have a learning environment called a “corpus.” If, for example, you want to teach an algorithm to recognize cats, you expose it to thousands of pictures of cats. In time, it figures out how to tell the difference between, say, a cat and a dog. Much like with human beings, it is through learning from these experiences that algorithms become useful.

However, the process can go horribly awry. A famous case is Microsoft’s Tay, a Twitter bot that the company unleashed on the microblogging platform in 2016. In under a day, Tay went from being friendly and casual (“humans are super cool”) to downright scary, (“Hitler was right and I hate Jews”). It was profoundly disturbing.

Bias in the learning corpus is far more common than we often realize. Do an image search for the word “professional haircut” and you will get almost exclusively pictures of white men. Do the same for “unprofessional haircut” and you will see much more racial and gender diversity.

It’s not hard to figure out why this happens. Editors writing articles about haircuts portray white men in one way and other genders and races in another. When we query machines, we inevitably find our own biases baked in.

Accounting For Algorithmic Bias

A second major source of bias results from how decision-making models are designed. Consider the case of Sarah Wysocki, a fifth grade teacher who — despite being lauded by parents, students, and administrators alike — was fired from the D.C. school district because an algorithm judged her performance to be sub-par. Why? It’s not exactly clear, because the system was too complex to be understood by those who fired her.

Yet it’s not hard to imagine how it could happen. If a teacher’s ability is evaluated based on test scores, then other aspects of performance, such as taking on children with learning differences or emotional problems, would fail to register, or even unfairly penalize them. Good human managers recognize outliers, algorithms generally aren’t designed that way.

In other cases, models are constructed according to what data is easiest to acquire or the model is overfit to a specific set of cases and is then applied too broadly. In 2013, Google Flu Trends predicted almost double as many cases there actually were. What appears to have happened is that increased media coverage about Google Flu Trends led to more searches by people who weren’t sick. The algorithm was never designed to take itself into account.

The simple fact is that an algorithm must be designed in one way or another. Every possible contingency cannot be pursued. Choices have to be made and bias will inevitably creep in. Mistakes happen. The key is not to eliminate error, but to make our systems accountable through, explainability, auditability and transparency.

To Build An Era Of Cognitive Collaboration We First Need To Build Trust

In 2020, Ofqual, the authority that administers A-Level college entrance exams in the UK, found itself mired in scandal. Unable to hold live exams because of Covid-19, it designed and employed an algorithm that based scores partly on the historical performance of the schools students attended with the unintended consequence that already disadvantaged students found themselves further penalized by artificially deflated scores.

The outcry was immediate, but in a sense the Ofqual case is a happy story. Because the agency was transparent about how the algorithm was constructed, the source of the bias was quickly revealed, corrective action was taken in a timely manner, and much of the damage was likely mitigated. As Linus’s Law advises, “given enough eyeballs, all bugs are shallow.”

The age of artificial intelligence requires us to collaborate with machines, leveraging their capabilities to better serve other humans. To make that collaboration successful, however, it needs to take place in an atmosphere of trust. Machines, just like humans, need to be held accountable, their decisions and insights can’t be a “black box.” We need to be able to understand where their judgments come from and how they’re decisions are being made.

Senator Schumer worked on legislation to promote more transparency in 2024, but that is only a start and the new administration has pushed the pause button on AI regulation. The real change has to come from within ourselves and how we see our relationships with the machines we create. Marshall McLuhan wrote that media are extensions of man and the same can be said for technology. Our machines inherit our human weaknesses and frailties. We need to make allowances for that.

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

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Stealing From the Garden of Eden

Stealing From the Garden of Eden

GUEST POST from Greg Satell

The story of the Garden of Eden is one of the oldest in recorded history, belonging not only to the world’s three major Abrahamic faiths of Judaism, Christianity and Islam, but also having roots in Greek and Sumerian mythology. It’s the ultimate origin archetype: We were once pure, innocent and good, but then were corrupted in some way and cast out.

As Timothy Snyder points out in his excellent course on The Making of Modern Ukraine, this template of innocence, corruption and expulsion often leads us to a bad place, because it implies that anything we do to remove that corrupting influence would be good and just. When you’re fighting a holy war, the ends justify the means.

The Eden myth is a favorite of demagogues, hucksters and con artists because it is so powerful. We’re constantly inundated with scapegoats— the government, big business, tech giants, the “billionaire” class, immigrants, “woke” society — to blame for our fall from grace. We need to learn to recognize the telltale signs that someone is trying to manipulate us.

The Assertion Of Victimhood

In 1987, a rather drab and dull Yugoslavian apparatchik named Slobodan Milošević was visiting Kosovo field, the site of the Serbs humiliating defeat at the hands of the Ottoman empire in 1389. While meeting with local leaders, he heard a commotion outside and found police beating back a huge crowd of Serbs and Montenegrins.

“No one should dare to beat you again!” Milošević is reported to have said and, in that moment, that drab apparatchik was transformed into a political juggernaut who left death and destruction in his path. For the first time since World War II, a genocide was perpetrated in Europe and the term ethnic cleansing entered the lexicon.

In Snyder’s book, Bloodlands, which chronicled the twin horrors of Hitler and Stalin, he points out that if we are to understand how humans can do such atrocious things to other humans, we first need to understand that they saw themselves as the true victims. When people believe that their survival is at stake, there is very little they won’t assent to.

The assertion of victimhood doesn’t need to involve life and death. Consider the recent Twitter Files “scandal,” in which the social media giant’s new owner leaked internal discussions about content moderation. The journalists who were given access asserted that those discussions amounted to an FBI-Big Tech conspiracy to censor important information. They paint sinister pictures of dark forces working to undermine our access to information.

When you read the actual discussions, however, what you see is a nuanced discussion about how to balance a number of competing values. How do we balance national security and public safety with liberty and free speech? At what point does speech become inciteful and problematic? Where should lines be drawn?

The Dehumanization Of An Out-group

Demagogues, hucksters and con men abhor nuance because victimhood requires absolutes. The victim must be completely innocent and the perpetrator must be purely evil for the Eden myth sleight of hand to work. There are no innocent mistakes, only cruelty and greed will serve to build the narrative.

Two years after Milošević political transformation at Kosooe field he returned there to commemorate the 600 anniversary of the Battle of Kosovo, where he claimed that “​​the Serbs have never in the whole of their history conquered and exploited others.” Having established that predicate, the stage was set for the war in Bosnia and the atrocities that came with it.

Once you establish complete innocence, the next step is to dehumanize the out-group. The media aren’t professionals who make mistakes, they are “scum who spread lies.” Tech giants aren’t flawed organizations, but ones who deliberately harm the public. Public servants like Anthony Fauci and philanthropists like Bill Gates are purported to engage in nefarious conspiracies that undermine the public well-being.

The truth is, of course, that nothing is monolithic. People have multiple motivations, some noble, others less so. Government agencies tend to attract mission-driven public servants, but can also be prone to overreach and abuse of power. Entrepreneurs like Elon Musk can have both benevolent aspirations to serve mankind and problematic character flaws.

It is no accident that the states in the US with the fewest immigrants tend to have the most anti-immigrant sentiment. The world is a messy place, which is why real-world experience undermines the Manichean worldview that demagogues, hucksters and con artists need to prepare the ground for what comes next.

The Vow For Retribution

It is now a matter of historical record what came of Milošević. After the horrors of the genocides his government perpetrated, his regime was brought down in the Bulldozer Revolution, the first of a string of Color Revolutions that spread across Eastern Europe. He was then sent to The Hague to stand trial, where would die in his prison cell.

Milošević made a common mistake (and one Vladimir Putin is repeating today). Successful demagogues, hucksters and con artists know to never make good on their vows for retribution. In order to serve its purpose, the return to Eden must remain aspirational, a fabulous yonder that will never be truly attained. Once you actually try to get there, it will be exposed as a mirage.

Yet politicians who vow to bring down evil corporations can depend on a steady stream of campaign contributions. In much the same way, entrepreneurs and entrepreneurs who rail against government bureaucrats can be enthusiastically invited to speak to the media and at investor conferences.

It is a ploy that has continued to be effective from antiquity to the present-day because it strikes at our primordial tendencies toward tribalism and justice, which is why we can expect it to continue. It’s a pattern that recurs with such metronomic regularity precisely because we are so vulnerable to it.

Being Aware Is Half The Battle

In my friend Bob Burg’s wonderful book, Adversaries into Allies, he makes the distinction between persuasion and manipulation. Bob says that persuasion involves helping someone to make a decision by explaining the benefits of a particular course of action, while manipulation takes advantage of negative emotions, such as anger, fear and greed.

So it shouldn’t be surprising that those who want to manipulate us tell origin stories in which we were once innocent and good until a corrupting force diminished us. It is that narrative that allows them to assert victimhood, dehumanize an out-group and promise, if given the means, that they will deliver retribution and a return to our rightful place.

These are the tell-tale signs that reveal demagogues, hucksters and con artists. It doesn’t matter if they are seeking backing for a new technology, belief in a new business model or public office, there will always be an “us” and a “them” and there can never be a “we together,” because “they,” are trying to deceive us, take what is rightfully ours and rob us of our dignity.

Yet once we begin to recognize those signs, we can use those emotional pangs as markers that alert us to the need to scrutinize claims more closely, seek out a greater diversity of perspectives and examine alternative narratives. We can’t just believe everything we think. It is the people who are telling us things that we want to be true that are best able to deceive us.

Those who pursue evil and greed always claim that they are on the side of everything righteous and pure. That’s what we need to watch out for most.

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

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Top 10 Human-Centered Change & Innovation Articles of April 2025

Top 10 Human-Centered Change & Innovation Articles of April 2025Drum 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 April’s ten most popular innovation posts:

  1. Innovation or Not? – Kawasaki Corleo — by Braden Kelley
  2. From Resistance to Reinvention — by Noel Sobelman
  3. How Innovation Tools Help You Stay Safe — by Robyn Bolton
  4. Should My Brand Take a Political Stand? — by Pete Foley
  5. Innovation Truths — by Mike Shipulski
  6. Good Management is Not Good Strategy — by Greg Satell
  7. ChatGPT Blew My Mind with its Strategy Development — by Robyn Bolton
  8. Five Questions Great Leaders Always Ask — by David Burkus
  9. Why So Many Smart People Are Foolish — by Greg Satell
  10. Beyond Continuous Improvement Culture — by Mike Shipulski

BONUS – Here are five more strong articles published in March 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 four years:

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We Need to Solve the Productivity Crisis

We Need to Solve the Productivity Crisis

GUEST POST from Greg Satell

When politicians and pundits talk about the economy, they usually do so in terms of numbers. Unemployment is too high or GDP is too low. Inflation should be at this level or at that. You get the feeling that somebody somewhere is turning knobs and flicking levers in order to get the machine humming at just the right speed.

Yet the economy is really about our well being. It is, at its core, our capacity to produce goods and services that we want and need, such as the food that sustains us, the homes that shelter us and the medicines that cure us, not to mention all of the little niceties and guilty pleasures that we love to enjoy.

Our capacity to generate these things is determined by our productive capacity. Despite all the hype about digital technology creating a “new economy,” productivity growth for the past 50 years has been tremendously sluggish. If we are going to revive it and improve our lives we need to renew our commitment to scientific capital, human capital and free markets.

Restoring Scientific Capital

In 1945, Vannevar Bush, delivered a report, Science, The Endless Frontier, that argued that the US government needed to invest in “scientific capital” and through basic research and scientific education. It would set in motion a number of programs that would set the stage for America’s technological dominance during the second half of the century.

Bush’s report led to the development of America’s scientific infrastructure, including agencies such as the National Science Foundation (NSF), National Institutes of Health (NIH) and DARPA. Others, such as the National Labs and science programs at the Department of Agriculture, also contribute significantly to our scientific capital.

The results speak for themselves and returns on public research investment have been shown to surpass those in private industry. To take just one example, it has been estimated that the $3.8 billion invested in the Human Genome Project resulted in nearly $800 billion in economic impact and created over 300,000 jobs in just the first decade.

Unfortunately, we forgot those lessons. Government investment in research as a percentage of GDP has been declining for decades, limiting our ability to produce the kinds of breakthrough discoveries that lead to exciting new industries. What passes for innovation these days displaces workers, but does not lead to significant productivity gains.

So the first step to solving the productivity puzzle would be to renew our commitment to investing in the type of scientific knowledge that, as Bush put it, can “turn the wheels of private and public enterprise.” There was a bill before congress to do exactly that, but unfortunately it got bogged down in the Senate due to infighting.

Investing In Human Capital

Innovation, at its core, is something that people do, which is why education was every bit as important to Bush’s vision as investment was. “If ability, and not the circumstance of family fortune, is made to determine who shall receive higher education in science, then we shall be assured of constantly improving quality at every level of scientific activity,” he wrote.

Programs like the GI Bill delivered on that promise. We made what is perhaps the biggest investment ever in human capital, sending millions to college and creating a new middle class. American universities, considered far behind their European counterparts earlier in the century, especially in the sciences, came to be seen as the best in the world by far.

Today, however, things have gone horribly wrong. A recent study found that about half of all college students struggle with food insecurity, which is probably why only 60% of students at 4-year institutions and even less at community colleges ever earn a degree. The ones that do graduate are saddled with decades of debt

So the bright young people who we don’t starve we are condemning to decades of what is essentially indentured servitude. That’s no way to run an entrepreneurial economy. In fact, a study done by the Federal Reserve Bank of Philadelphia found that student debt has a measurable negative impact on new business creation.

Recommitting Ourselves To Free and Competitive Markets

There is no principle more basic to capitalism than that of free markets, which provide the “invisible hand” to efficiently allocate resources. When market signals get corrupted, we get less of what we need and more of what we don’t. Without vigorous competition, firms feel less of a need to invest and innovate, and become less productive.

There is abundant evidence that is exactly what has happened. Since the late 1970s antitrust enforcement has become lax, ushering in a new gilded age. While digital technology was hyped as a democratizing force, over 75% of industries have seen a rise in concentration levels since the late 1990s, which has led to a decline in business dynamism.

The problem isn’t just monopoly power dominating consumers, either, but also monopsony, or domination of suppliers by buyers, especially in labor markets. There is increasing evidence of collusion among employers designed to keep wages low, while an astonishing abuse of non-compete agreements that have affected more than a third of the workforce.

In a sense, this is nothing new. Adam Smith himself observed in The Wealth of Nations that “Our merchants and master-manufacturers complain much of the bad effects of high wages in raising the price, and thereby lessening the sale of their goods both at home and abroad. They say nothing concerning the bad effects of high profits. They are silent with regard to the pernicious effects of their own gains. They complain only of those of other people.”

Getting Back On Track

In the final analysis, solving the productivity puzzle shouldn’t be that complicated. It seems that everything we need to do we’ve done before. We built a scientific architecture that remains unparalleled even today. We led the world in educating our people. American markets were the most competitive on the planet.

Yet somewhere we lost our way. Beginning in the early 1970s, we started reducing our investment in scientific research and public education. In the early 1980s, the Chicago school of competition law started to gain traction and antitrust enforcement began to wane. Since 2000, competitive markets in the United States have been in serious decline.

None of this was inevitable. We made choices and those choices had consequences. We can make other ones. We can choose to invest in discovering new knowledge, educate our children without impoverishing them, to demand our industries compete and hold our institutions to account. We’ve done these things before and can do so again.

All that’s left is the will and the understanding that the economy doesn’t exist in the financial press, on the floor of the stock markets or in the boardrooms of large corporations, but in our own welfare as well as in our ability to actualize our potential and realize our dreams. Our economy should be there to serve our needs, not the other way around.

— Article courtesy of the Digital Tonto blog
— Image credits: Unsplash

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Top 10 Human-Centered Change & Innovation Articles of August 2023

Top 10 Human-Centered Change & Innovation Articles of August 2023Drum 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 August’s ten most popular innovation posts:

  1. The Paradox of Innovation Leadership — by Janet Sernack
  2. Why Most Corporate Innovation Programs Fail — by Greg Satell
  3. A Top-Down Open Innovation Approach — by Geoffrey A. Moore
  4. Innovation Management ISO 56000 Series Explained — by Diana Porumboiu
  5. Scale Your Innovation by Mapping Your Value Network — by John Bessant
  6. The Impact of Artificial Intelligence on Future Employment — by Chateau G Pato
  7. Leaders Avoid Doing This One Thing — by Robyn Bolton
  8. Navigating the Unpredictable Terrain of Modern Business — by Teresa Spangler
  9. Imagination versus Knowledge — by Janet Sernack
  10. Productive Disagreement Requires Trust — by Mike Shipulski

BONUS – Here are five more strong articles published in July 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!

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 three years:

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Four Transformation Secrets Business Leaders Can Learn from Social and Political Movements

Four Transformation Secrets Business Leaders Can Learn from Social and Political Movements

GUEST POST from Greg Satell

In 2004, I was managing a major news organization during the Orange Revolution in Ukraine. One of the things I noticed was that thousands of people, who would normally be doing thousands of different things, would stop what they were doing and start doing the same things all at once, in nearly complete unison, with no clear authority guiding them.

What struck me was how difficult it was for me to coordinate action among the people in my company. I thought if I could harness the forces I saw at work in the Orange Revolution, it could be a powerful model for business transformation. That’s what started me out on the 15-year journey that led to my book, Cascades.

What I found was that many of the principles of successful movements can be applied to business transformation. Also, because social and political movements so well documented—there are often thousands of contemporary accounts from every conceivable perspective—we can gain insights that a traditional case studies miss. Here are four principles you can apply.

1. Failure Doesn’t Have To Be Fatal

One of the things that amazed me while researching revolutionary movements was how consistently failure played a part in their journey. Mahatma Gandhi’s early efforts to bring independence to India led to the massacre at Amritsar in 1919. Our own efforts in Ukraine in 2004 ultimately led to Viktor Yanukovych’s rise to power in 2010.

In the corporate context, it is often a crisis that leads to transformational change. In the early 90s, IBM was nearly bankrupt and many thought the company should be broken up. That’s what led to the Gerstner revolution that put the company back on track and a similar crisis at Alcoa presaged record profits under Paul O’Neil.

In fact, Lou Gertner would later say that failure and transformation are inextricably linked. “Transformation of an enterprise begins with a sense of crisis or urgency,” he told a groups of Harvard Business School students. “No institution will go through fundamental change unless it believes it is in deep trouble and needs to do something different to survive.”

What’s important about early failures is what you learn from them. In every successful transformation I researched, what turned the tide was when the insights gained from early failures were applied to create a keystone change that set out a clear and concrete initiative, involved multiple stakeholders and paved the way for a greater transformation down the road.

2. Don’t Bet Your Transformation On Persuasion

Any truly transformational change is going to encounter significant resistance. Those who fear change and support the status quo can be expected to work to undermine your efforts. That’s fairly obvious in social and political movements like the civil rights movements or the struggle against Apartheid, but often gets overlooked in the corporate context.

All too often change management efforts seek to convince opponents through persuasion. That’s unlikely to succeed. Betting your transformation on the idea that, given the right set of arguments or snappy slogans, those who oppose the change that you seek will immediately see the light is unrealistic. What you can do, however, is set out to influence stakeholders who can wield influence.

For example, in the 1980s, anti-Aparthied activists activists led a campaign against Barclays Bank in British university towns. That probably did little to persuade white nationalists in South Africa, but it severely affected Barclays’ business, which pulled its investments from South Africa. That and similar efforts made Apartheid economically untenable and helped lead to its downfall.

In a corporate transformation, there are many institutions, such as business units, customer groups, industry associations, and others that can wield significant influence. By looking at stakeholder groups more broadly, you can win important allies that can help you drive transformation forward.

3. Be Explicit About Your Values

Today, we regard Nelson Mandela as an almost saintly figure, but it wasn’t always that way. Throughout his career as an activist, he was accused of being a communist, an anarchist and worse. When confronted with these accusations, however, he always pointed out that no one had to guess what he believed in, because it was written down in the Freedom Charter in 1955.

Being explicit about values helped to signal to external stakeholders, such as international institutions, that the anti-Aparthied activists shared common values. In fact, although the Freedom Charter was a truly revolutionary document, its call for things like equal rights and equal protection would be considered utterly unremarkable in most countries.

After Apartheid fell and Mandela rose to power, the values spelled out in the Freedom Charter became important constraints. If, for example, a core value is that all national groups should be treated equal, then Mandela’s government clearly couldn’t oppress whites. His reconciliation efforts are a big part of the reason he is so revered today.

Irving Wladawsky-Berger, one of Gerster’s key lieutenants, told me how values played a similar role during IBM’s turnaround years. “The Gerstner revolution wasn’t about technology or strategy, it was about transforming our values and our culture to be in greater harmony with the market… Because the transformation was about values first and technology second, we were able to continue to embrace those values as the technology and marketplace continued to evolve.”

4. Every Revolution Inspires A Counter-Revolution

After the Orange Revolution ended in 2005, we felt triumphant. We overcame enormous odds and had won. Little did we know that there would be much darker days ahead. In 2010, Viktor Yanukovych, the man we took to the streets to keep out of power, was elected president in an election that international observers judged to be free and fair.

While surprising, this is hardly uncommon. Similar events took place during the Arab Spring. The government of Hosni Mubarrak was overthrown only to be replaced by that of Abdel Fattah el-Sisi, who is possibly even more oppressive. Harvard professor Rita Gunther McGrath points out that in today’s business environment, competitive advantage tends to be transient.

The truth is that every revolution inspires a counter-revolution. That’s why the early days of victory are often the most fragile. That’s when you tend to take your foot off the gas and relax, while at the same time those who oppose the change you worked to build are just beginning to plan to redouble their efforts.

That’s why you need a plan to survive victory from the start rooted in shared values. In the final analysis, driving change is less about a series of objectives than it is about forming a common cause. That’s just as true in a corporate transformation as it is in a social or political revolution.

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

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