Customer Experience Audit Checklist

What a Professional Auditor Actually Looks For

Customer Experience Audit Checklist

by Braden Kelley and Art Inteligencia

People often picture a customer experience audit as something closer to inspiration than inspection — a few interviews, some good ideas, a workshop. It isn’t. A real audit runs a specific, repeatable checklist across five activities, and knowing what’s actually on that checklist is useful even if you’re not commissioning a full audit yet — it tells you exactly where your own internal review is likely leaving gaps.

1. Audience research and persona validation

  • Have you named your distinct audience segments explicitly, rather than treating “the customer” as one undifferentiated group?
  • Are your existing personas based on validated research, or on assumptions that were accurate once and never rechecked?
  • Do you know which needs, expectations, and pain points are consistent across segments, and which ones genuinely differ?
  • Has anyone recently asked customers directly what they expect, rather than inferring it from internal debate?

Most organizations have personas. Far fewer have validated them against current reality in the last two years — and a persona built on outdated assumptions can misdirect an entire audit before it starts.

2. Journey mapping and touchpoint analysis

  • Is there a current journey map for each validated persona, or one generic map applied to everyone?
  • Are all relevant channels represented, not just the primary one your team happens to work in?
  • Does the map capture emotional highs and lows at each touchpoint, or only the functional steps?
  • Have improvement opportunities been identified at the touchpoint level, rather than as vague, journey-wide observations?

A journey map that only lists steps, without the emotional experience at each one, tells you what happens without telling you what it’s like — and “what it’s like” is usually where the real problem lives.

3. Existing data evaluation

  • Are your KPIs, NPS, CSAT, and sentiment data being analyzed together, or read in isolation by different teams?
  • Have you looked for patterns across data sources that no single dashboard would surface on its own?
  • Is there a gap between what your data says and what your frontline teams say — and if so, has anyone reconciled it?
  • What insight is your current reporting structurally unable to produce, no matter how closely you look at it?

This step exists because most organizations already have more data than they’ve actually used. The checklist item isn’t “collect more data” — it’s “extract what’s already sitting there unexamined.”

4. Walking the journey firsthand

  • Has anyone on your team experienced the journey as a customer would — not reviewed it on paper, but actually gone through it?
  • Does that include the channels that are hardest to observe from a desk — a retail visit, a live service call, a full sales cycle?
  • For B2B experiences specifically, has the buying-committee journey been walked, not just the end-user journey?
  • What did that firsthand pass turn up that no dashboard or survey had previously flagged?

This is consistently where an audit finds its most valuable insights, and it’s also the step most internal reviews skip entirely, because it requires time in the field rather than time in a meeting.

5. Competitive benchmarking

  • Do you know how your experience compares to your closest competitors at the touchpoints that matter most, not just anecdotally?
  • Have you looked at best-in-class examples outside your own industry, where customer expectations are quietly being reset?
  • Is “good enough” being judged against your own history, or against where your customers’ expectations actually sit today?

Benchmarking is the item most often skipped to save time — understandably, since it’s the one activity that looks outward instead of inward. It’s also the one that answers the question your leadership will eventually ask: not “are we good,” but “are we good enough relative to the alternative.”

Using this checklist honestly

If you walk through these five sections and find real gaps — persona research from three years ago, a journey map from before a major process change, data that’s never been cross-analyzed, no one who’s actually walked the journey firsthand, no benchmarking at all — that’s not a failure. It’s an accurate picture of where a professional audit would start, and it’s useful information either way.

If the gaps are small, a lighter internal review might close them. If the gaps run through several of these five, it’s usually a sign that a proper Customer Experience Audit is worth the investment rather than another attempt to patch it internally — and if you want a sense of what closing those gaps could be worth before you commit, the CX ROI Calculator is the fastest way to find out.

Download the Customer Experience Audit Checklist as a PDF

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 Claude to clean up the article.

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Mapping the Future with Wardley Maps

Mapping the Future with Wardley Maps

GUEST POST from Mike Shipulski

How do you know when it’s time to reinvent your product, service or business model? If you add ten units of energy and you get less in return than last time, it’s time to work in new design space. If improvement in customer goodness (e.g., miles per gallon in a car) has slowed or stopped, it’s time to seek a new fuel source. If recent patent filings are trivial enhancements that can be measured only with a large sample sizes and statistical analysis, the party is over.

When there’s so many new things to work on, how do you choose the next project? When you’re lost, you look at a map. And when there is no map, you make one. The first bit of work is defined by the holes in the first revision of your map. And once the holes are filled and patched, the next work emerges from the map itself. And, in a self-similar way, the next work continually emerges from the previous work until the project finishes.

But with so much new territory, how do you choose the right new territory to map? You don’t. Before there’s a need to map new territory, you must map the current territory. What you’ll learn is there are immature areas that, when made mature, will deliver new value to customers. And you’ll also learn the mature areas that must be blown up and replaced with infant solutions that will ultimately create the next evolution of your business. And as you run thought experiments on your map – projecting advancements on the various elements – the right new territory will emerge. And here’s a hint – the right new solutions will be enabled by the newly matured elements of the map.

But how do you predict where the right new solutions will emerge? I can’t tell you that. You are the experts, not me. All I can say is, make the maps and you’ll know.

And when I say maps, I mean Wardely Maps – here’s a short video (go to 4:13 for the juicy bits).

Image credits: Pixabay

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Dead Actors Society

How AI Synthetic Likenesses, Estate Licensing, and the Experience Economy Are Disrupting the Talent Ecosystem

Dead Actors Society

GUEST POST from Art Inteligencia


I. Executive Summary & Thesis

The Paradigm Shift: Generative AI and real-time neural rendering are fundamentally decoupling an actor’s craft and visual identity from their physical body, availability, and natural lifespan. Cinema is transitioning from a discipline constrained by human logistics to an unconstrained digital canvas.

The Core Thesis: In the emerging era of AI-generated full-length feature films, the estates of deceased cultural icons—unencumbered by living human limitations, scheduling conflicts, or creative resistance—are uniquely positioned to lead the charge in licensing synthetic likenesses for entirely new cinematic roles.

The Macro Impact: This transition extends far beyond Hollywood production budgets. It represents a fundamental restructuring of the creative talent ecosystem:

  • Talent Ecosystem Disruption: Living performers will no longer compete solely against current peers, but against a century of cinematic legends performing at their peak aesthetic and charismatic influence.
  • Strategic Career Pressures: Mid-tier and emerging actors face extreme wage deflation as synthetic legacy assets provide predictable, risk-mitigated alternatives for studios.
  • Likeness Securitization: A high-yield financial marketplace—directly mirroring the multi-billion-dollar music catalog acquisition booms—will emerge to monetize, package, and trade post-mortem digital likeness rights as long-term yield assets.

II. Introduction: The Arrival of the Synthetic Cinema Era

The Friction of Change: For decades, visual effects relied on heavy post-production labor to achieve incremental milestones—de-aging an aging star for a brief flashback or rendering a digital double for high-risk stunt work. Today, generative neural rendering and real-time motion synthesis have crossed a critical threshold. We are shifting rapidly from post-production touch-ups to full-synthesis cinematic creation, where generative models can power entire lead performances across full-length feature films with hyper-realistic emotional fidelity.

The “Dead Actors Society” Phenomenon: As production costs drop and synthetic rendering capability matures, a new content category is taking shape: the deliberate, high-budget revival of iconic performers in entirely original narratives. This is not about re-editing archival footage or stitching together outtakes. This is the era of the Dead Actors Society—a dynamic marketplace where legendary figures from film history return to headline original screenplays, cross-genre experiments, and modern franchises decades after their passing.

The Human-Centered Lens: From an experience design perspective, human beings do not connect merely to high-resolution pixels; we connect to narrative resonance, archetypal familiarity, and shared cultural memory. In an increasingly fragmented media landscape, iconic stars carry immediate emotional context and built-in trust. For studios navigating rising development risks, leveraging synthetic legacy talent offers a powerful mechanism to derisk major film slates while tapping directly into deeply ingrained audience nostalgia.

III. Why Estates Will Lead the Licensing Charge

Incentive Alignment (Frictionless Talent): Unlike living performers who manage complex personal brands, physical constraints, and evolving artistic ambitions, estate management operates primarily as an intellectual property enterprise. For estate trustees, licensing a digital likeness eliminates traditional production friction: there are no onset delays, travel requirements, physical exhaustion, or behavioral liabilities. The actor becomes a predictable, high-performing digital asset capable of infinite deployment.

Algorithmic Consistency & Archetypal Clarity: Iconic stars of cinema’s Golden Age—such as Humphrey Bogart, Marilyn Monroe, or James Dean—possess clearly defined, universally understood cultural archetypes. Because their screen legacies are static, generative models can synthesize their specific charismatic signatures, vocal cadence, and emotional range with remarkable precision. Studios gain access to instant brand recognition and established storytelling shorthand that requires zero audience warm-up.

Economic Incentive for Heirs: For heirs and asset managers, passive ownership of legacy rights often faces diminishing returns over time as catalog titles recede from active streaming discovery. Transitioning static IP into active, synthetic licensing models transforms dormant archives into dynamic, high-margin revenue streams. Through royalty-per-frame or box-office participation models, estates can capture continuous commercial value across future generations of media.

IV. The Squeeze on Living Talent: Pressures and Disruption

The “Infinite Competition” Problem: Throughout cinema history, living actors competed primarily against their contemporary peers for coveted roles. In the synthetic cinema era, that competitive arena expands infinitely backward across time. Emerging and established talent will find themselves auditioning not just against current box-office leads, but against a century of screen legends preserved at their peak aesthetic, physical, and charismatic influence—available to perform on demand without fatigue or scheduling conflicts.

Bifurcation of the Acting Profession: The economic pressures of synthetic competition will restructure the performer labor market into two distinct tiers:

  • The Ultra-Elite Tier: A small upper crust of living megastars whose commercial value relies on genuine human presence, active cultural commentary, live press tours, and authentic real-world fan connections.
  • The Squeezed Middle and Entry Level: Character actors, supporting talent, and working professionals who face severe wage compression and diminishing opportunities as studios opt for cost-effective, risk-mitigated synthetic legacy models for mid-tier roles.

The Experience Value Proposition: As synthetic performances achieve technical parity with human delivery, experience design forces a critical question for creators and audiences alike: What is the intrinsic value of human vulnerability in art? While mass-market entertainment may readily accept polished synthetic performances, a premium live-action market may emerge, marketing the deliberate imperfection, unpredictability, and lived experience of authentic human performers.

V. The Financialization of Likeness: Wall Street Meets Hollywood Catalog Sales

The Music Industry Blueprint: Over the past decade, financial institutions and private equity firms created a multi-billion-dollar asset class by purchasing the publishing rights and master recordings of legendary musicians—from Bob Dylan to Bruce Springsteen. The core thesis was simple: predictable, long-term cash flows from enduring cultural IP. Synthetic cinema opens the exact same financial playbook for screen performance, transforming an actor’s visual and vocal identity into an yield-bearing financial asset.

Likeness Securitization & Valuation Models: As generative models require clean, high-density training data, an actor’s digital archive becomes quantifiable. Wall Street valuation models will price an actor’s “Synthetic Future Cash Flow” based on three core variables:

  • Training Data Quality: The depth, resolution, and emotional range captured in their historic filmography.
  • Archetypal Demand: How universally their persona maps to high-converting narrative genres.
  • Cross-Generational Longevity: The projected retention of their cultural relevance across global markets.

Pre-Mortem Rights Offloading & Likeness Royalties: Living actors will not wait for death to monetize their synthetic value. We will see performers offload their post-mortem rights—or even license mid-career synthetic clones—early in life to private equity funds for immediate lump-sum liquidity. This will give rise to complex likeness royalty structures, fractionalized ownership of synthetic talent libraries, and secondary derivative markets trading on the future performance of digital personas.

VI. Strategic Foresight: Governance, Ethics, and Experience Design Challenges

Human-Centered Change Management for Hollywood: Navigating the synthetic era requires robust governance frameworks that balance creative freedom with ethical stewardship. Labor unions like SAG-AFTRA, estate trustees, and legislative bodies will be forced to continually redefine right-of-publicity laws, digital consent boundaries, and posthumous labor rights to prevent non-consensual exploitation while enabling legitimate commercial innovation.

Audience Fatigue & Experiential Saturation: From an experience design perspective, over-relying on familiar digital ghosts carries significant narrative risk. When iconic faces become ubiquitous across cheap spin-offs, interactive media, and localized ad campaigns, “nostalgia overload” sets in. This erosion of scarcity dilutes the actor’s original cinematic legacy and risks numbing audience emotional engagement through synthetic repetition.

Authenticity vs. Convenience: As synthetic content generation accelerates, experience designers and filmmakers must intentionally craft the boundary between efficiency and artistry. The challenge will not be technical feasibility, but human resonance—ensuring that synthetic revival serves a genuine artistic purpose rather than functioning merely as a frictionless, algorithmically optimized cash grab.

VII. Conclusion: Framing the Future of Talent

Summary of the New Landscape: The arrival of synthetic feature films does not spell the end of human performance, but it marks the definitive end of its monopoly. Cinema is entering a hybrid era where living performers, purely synthetic AI-generated entities, and licensed digital revivals of historic legends co-exist within the same creative ecosystem. Success in this environment will require a fundamental shift in how studios, managers, and audiences conceptualize talent, IP, and performance art.

Call to Action for Leaders and Creators: As leaders in media, technology, and human-centered innovation, our responsibility is to guide this transition with intentionality. We must build business models and governance frameworks that honor human legacy without stifling artistic evolution. By prioritizing authenticity, ethical consent, and meaningful experience design over mere algorithmic convenience, we can ensure that synthetic cinema expands the horizons of human storytelling rather than cheapening it.

Frequently Asked Questions

Why are the estates of dead actors more likely to license AI likenesses than living actors?

Estates operate primarily as intellectual property enterprises focused on asset maximization without the physical, emotional, or ego-driven constraints of living performers. Unlike living actors, deceased legends face zero physical friction—there are no set scheduling limits, press junket obligations, physical aging, or behavioral liabilities, making them predictable, high-performing digital assets for studios seeking to derisk major film investments.

How will the rise of synthetic legacy actors impact living performers?

Living actors will no longer compete solely against current peers, but against a century of film history preserved at peak aesthetic and charismatic performance. This will likely bifurcate the talent market: an ultra-elite tier of living megastars whose value lies in authentic human presence and live connection, and a severely squeezed middle tier of character and entry-level actors facing wage compression as studios adopt cost-effective, risk-mitigated synthetic models.

Will AI actor likenesses generate a financial market similar to music catalog sales?

Yes. Just as financial institutions transformed musician song catalogs into multi-billion-dollar yield-bearing assets, Wall Street will monetize actor likenesses based on training data quality, archetypal demand, and historic box office impact. Living actors and estates will offload post-mortem rights to private equity funds for immediate liquidity, creating a robust secondary market for likeness royalties and fractionalized talent libraries.


Image Credits: Gemini

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Amazon Connect Combines Human Empathy with AI to Redefine Service

Amazon Connect Combines Human Empathy with AI to Redefine Service

GUEST POST from Shep Hyken

Will AI replace people?

This is a question I’m often asked. In the customer service world, there are many who say AI will replace human-to-human support. It’s been predicted by the world’s most reputable consulting firms. However, executives from some of the largest and most recognizable brands on the planet have said that while AI is making for a better customer experience, people are still needed and their companies are continuing to hire.

That sentiment was recently confirmed when I interviewed Pasquale DeMaio, vice president and general manager of Amazon Connect, on Amazing Business Radio. His specific approach to AI and human-to-human customer service is summed up in two words: Better Together.

Human and AI: Better Together

Customer service works best when technology and humans come together. While AI and automation can make things faster and easier, there will be times when customers still want to talk to a live customer support agent.

The point is to automate the simple requests and questions and empower agents to manage more complex issues. DeMaio said (referring to customer service agents), “No one is enjoying a password reset, neither talking to someone about it nor listening to the request.” Let AI take care of the simple questions and requests, and let humans manage the more complex problems and emotional issues.

AI Can’t Do Empathy — That’s What People Do

DeMaio said, “People aren’t really looking for technology to form that emotional connection when they’re trying to achieve an outcome.” While AI can talk to a customer and sound like a human, the customer knows it’s just a machine. It can say, “I’m sorry,” and sound empathetic, but it’s not, and the customer knows it. Authentic empathy is a human-to-human experience.

DeMaio shares his philosophy of friendly, empathetic service. He says, “At Amazon, we actually tell people to treat the customer on the phone like they’re your friend. But what we don’t say is the person on the phone is your friend. … What’s natural is to treat them the way you would treat a friend.” And that is how empathy begins.

Customer Support Doesn’t Cost — It Pays

Traditional contact centers have focused on quick, efficient resolutions. Metrics like AHT (Average Handle Time) are efficiency measurements. The goal of handling as many calls as quickly as possible is not as effective as using customer support to not only solve customer issues but also enhance customer relationships. Once again, let AI-fueled self-service tools handle simple problems and have people (customer support agents) spend a little more time with customers to drive repeat business and loyalty. In addition, DeMaio points out that businesses should aim to understand why a customer might want to leave and proactively create positive experiences well before they escalate, to get customers to want to come back. For example, Amazon Connect’s real-time analytics empower agents to detect customer sentiment, identify at-risk relationships and take the necessary steps to save the customer.

Finding the Balance Between Technology and Human-to-Human Conversations

The balance between technology and human support will vary. However, the future of customer service is not about choosing between AI and humans. It’s about using the strengths of both to create a convenient, efficient and seamless experience. Customer service is not just about fixing. It’s about caring and building long-term, loyal relationships. DeMaio summed it up by saying, “Think about the long-term value of the customer. And then think about how you would want to be treated as a human being. And then think about how AI can help you do that better.”

This article was originally published on Forbes.com.

Image Credits: Shep Hyken

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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.

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

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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Focus on Delivering Your Customers’ Desired Outcomes, Not Delighting Them

Focus on Delivering Your Customers' Desired Outcomes, Not Delighting Them

GUEST POST from Geoffrey Moore

Now, let me be clear. I have nothing against delight. But the notion that it should be the goal of a business to delight its customers is folly. Delight, after all, is an evanescent experience that comes and goes pretty much as it pleases. It cannot be reliably evoked. More importantly, your customers, and particularly your B2B customers, are not paying you in order to be delighted. Indeed, while ostensibly they are purchasing your products and services, what they really want to buy is outcomes.

As Ted Levitt taught many years ago, while a customer may need to buy a quarter-inch drill, what they really want to buy is a quarter-inch hole. A successful sales campaign, therefore, starts with getting clarity on what outcomes constitute success. This is harder than it sounds. Success is seen very differently from the perspectives of the executive sponsor, the department manager, the end user, the technical specialist, the CIO, and the CFO. All six of these have a stake in the game, and you will need their support to establish an enduring relationship.

Now, to be fair, a lot of business as usual doesn’t call for executive attention because inertial momentum is already on the side of the desired outcomes. It’s when the customer needs to change the status quo that we need to develop a multi-stakeholder current-state/future-state roadmap for success. So, let’s imagine you are in the IT industry and you are looking to land a major new account. What kind of a journey would that entail?

  • The Executive Sponsor. The process starts with engaging the executive sponsor in a discussion of the current state of their business, what potential future state they may have in mind, and what “value traps” are impeding their progress. In this discussion you have the opportunity to demonstrate genuine intellectual curiosity about the dynamics of their company and industry and to propose connections between your offerings and their aims. The deeper this conversation goes, the bigger the opportunity space becomes. This, in other words, is where five-figure deals can become six-figure, and six-figure deals become seven-figure, for the outcome the executive sponsor really wants is to move the big rocks, not just to smooth out the gravel.
  • The Department Manager. Department managers, on the other hand, are up to their ankles in gravel and they need your help to deal with it. Once again, engaging them in an intellectually curious conversation about their value traps allows you to identify the outcomes that will make a real difference and to make sure you highlight them in your proposal and prioritize them in your implementation. The outcome department managers want is productivity improvement for their team, as measured by faster response times, better quality, and greater throughput. The executive sponsor supports this sort of thing, but they have delegated it to the department manager, and so do not need to be directly involved.
  • The End Users. The end users who work for the department manager are the ones whose behavior you will directly impact and whose buy-in you must secure. The outcomes they seek are improvements in their personal effectiveness and efficiency. Most frequently they are looking for relief from mundane repetitive tasks that a smarter system would just do for them in the background. “Free me from the stupid stuff!” might be their battle cry. With the rise of RPA (Robotic Process Automation), complemented now with GenAI (Generative AI), this is becoming increasingly feasible to deliver. One thing to remember with end-user communities, however, is that they mirror the Technology Adoption Life Cycle in miniature, meaning they are comprised of enthusiasts, visionaries, pragmatists, conservatives, and skeptics. Each profile defines successful outcomes in very different terms, so the Customer Success team needs to identify the adoption profile of the individual they are working with before they go about prescribing tactics for meeting their needs.
  • The Technical Specialist. It is not until you get to the technical specialist that you find anyone who is really interested in your product. This, in other words, is the first person who actually wants to see your demo. Demoing to any of the prior three stakeholders is typically a waste of time, at least until you can tune the demo to highlight the outcome they seek. But with technical specialists, it is critical to your success. They are often the ones who get to make the call between competing products that have roughly the same functionality, and you need expertise in both yours and the competitors’ offers so you can answer their questions with authority. A successful outcome for this stakeholder is to have a high-performing product to support.
  • The CIO. The CIO has bigger fish to fry, and once again, you need to be sensitive to where they sit in the Technology Adoption Life Cycle. Visionaries who drive digital transformation will care a ton about platforms to support the future and be desperate to free themselves from the technical debt of legacy systems. Success for them is a next-generation infrastructure that can help modernize their company’s operating model, and they will move heaven and earth to get it. Pragmatists can have similar goals but will want to proceed more methodically, looking for predictable outcomes that come in on spec, on time, and on budget, as confirmed by customer references that are in production. Meanwhile, conservatives are secretly hoping they can just pass this baton to their successor, and skeptics will simply dig in their heels.
  • The CFO. The CFO is likely to view success in terms of verifiable ROI, yet again with a Technology Adoption Life Cycle wrinkle. Conservative CFOs will be looking for “hard dollar” savings—direct reductions in out-of-pocket costs. Pragmatic CFOs will look beyond these to include “soft dollar” savings from productivity gains in throughput, cycle time, and quality. Visionary CFOs (and, yes, there are such folk) look beyond this for step-function changes in competitive advantage that would change the multiple of their stock price. What unites all of the above is that all these success outcomes have some flavor of “Show me the money!”
  • The Account Plan. As sales teams well know, every account plays out in its own unique ways, but we can do our best to nudge it toward our goals. This starts with prioritizing the importance of our six stakeholders with respect to the buying decision on the table. If we have to create or redirect budget, then we need to call high, but if we are simply looking to consume budget, then we need to focus on the middle management instead. So, as an account manager, get your team to rank order the six stakeholders and then focus your efforts on the top two or three.

With respect to those top targets, the next step is to get the team to agree on their Technology Adoption profile. This is super important because you only get a limited amount of attention from any of these folks, and you don’t want to waste cycles on messages that won’t land.

Third, once you get a realistic sense of the outcome that are driving the sales cycle from the customer’s point of view, you need to differentiate your proposal both by calling them out as key goals and then customizing your offer to ensure they will get achieved.

All in all, it’s not rocket science, but it does require patience, and most of all, it calls for you to genuinely engage with the target personas to develop a differentiating understanding of what they are really after.

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

— Image credit: Pexels

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What Does a Customer Experience Audit Cost?

What Does a Customer Experience Audit Cost?

by Braden Kelley and Art Inteligencia

This is usually the last question someone asks before they’re ready to move forward, which means it deserves a direct answer rather than the consultant’s reflex of “it depends.” It does depend — but on a small, specific set of factors, and I’d rather walk you through exactly what they are than make you guess.

The honest answer: it scales with scope, not with company size

The biggest misconception I run into is that audit cost tracks with company revenue or headcount. It doesn’t, directly. It tracks with the shape of the journey being audited: how many distinct touchpoints are in scope, how many channels the experience spans (in-person, phone, web, app, in some combination), and how many stakeholder groups need to be interviewed to understand the journey from more than one angle. A single-channel, single-audience journey for a mid-size company can cost less than a sprawling omnichannel journey for a smaller one, if the omnichannel journey is genuinely more complex to walk.

The five activities that drive cost

  1. Audience research and persona validation. Every audit starts by identifying your distinct audience segments and validating their journeys against current reality — surfacing the needs, expectations, and pain points that internal assumptions have obscured. One clearly-defined audience is a much faster starting point than four segments that each need their own research and validation pass, and this is usually the first scope decision worth making deliberately.
  2. Journey mapping and touchpoint analysis. From there, we create or update persona-based journey maps — identifying key touchpoints, pain points, emotional highs and lows, and improvement opportunities across every relevant channel. A journey with four or five touchpoints in a single channel maps far faster than one spanning fifteen touchpoints across phone, web, app, and in-person combined.
  3. Existing data evaluation. Your current KPIs, NPS scores, CSAT data, and sentiment analysis get analyzed for the patterns, gaps, and untapped insights that current reporting isn’t surfacing. How much historical data you already have — and how much of it is usable versus scattered across disconnected systems — changes how much work this step takes before it produces anything actionable.
  4. Walking the journey. This is where key touchpoints get evaluated firsthand — retail locations, digital channels, service calls, sales cycles, in B2B and B2C contexts alike — and it’s typically where an audit finds its most surprising and valuable insights. It’s also usually the most time-intensive of the five activities, because it’s genuine fieldwork rather than analysis of what already exists, and cost scales directly with how many touchpoints and channels get walked in person versus reviewed through documentation alone.
  5. Competitive benchmarking. Benchmarking your experience performance against select competitors and best-in-class examples shows not just where you stand, but how far you are from where you need to be. This one is genuinely optional depending on your goals — skipping it keeps the engagement focused purely on your own gaps, while including it adds real value when you specifically need to know how you compare to the alternatives your customers are weighing.

Timeline compresses or expands the cost of all five at once: doing them in two weeks instead of six doesn’t reduce the work, it concentrates it, usually by putting more people on it in parallel. If you have flexibility on timeline, it’s often the easiest lever to pull to manage overall cost.

The number that actually matters more than the price

Cost in isolation is the wrong comparison. The comparison that matters is cost against what the friction is currently costing you in retained revenue, referral loss, and cost to serve — because that’s the number an audit is designed to protect. If you haven’t run that comparison yet, the CX ROI Calculator will give you a real figure in a few minutes, and it’s the right first step before a cost conversation, not after it. A number that’s larger than the audit’s cost is the fastest way to know the conversation is worth having at all.

Getting an actual number

Because cost depends on the scope decisions above, and those decisions are specific to your journey and your goals, the accurate way to get a real figure is a short scoping conversation rather than a published price list that would be wrong for most people who read it. If you’re at the point of wanting that conversation, the audit page has the details on how an engagement runs, and I’m glad to talk through scope and a realistic estimate directly.

Customer Experience Audit Learn More

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

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!

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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

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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