Latest / The Human Factor: Exploring the Intersection of Humanity, Technology, and Transformation / Episode 010 Measuring the Human Factor - When Surveys Lie and Behavior Reveals the Truth

Transcript

Episode 010 Measuring the Human Factor - When Surveys Lie and Behavior Reveals the Truth · The Human Factor: Exploring the Intersection of Humanity, Technology, and Transformation

• 0:05
  The organization hired us to figure out why their digital
• 0:08
  transformation was stalling. They had run an engagement
• 0:11
  survey three months earlier. Support for the initiative was
• 0:15
  at 82%. Leadership was baffled, and four
• 0:19
  out of five people supported the transformation.
• 0:22
  Why was it anything actually changing?
• 0:25
  So we started measuring something different.
• 0:28
  Not what people said they would do, but what they actually did.
• 0:32
  We tracked systems, logins, feature usage, time spending,
• 0:37
  new work flows versus the old workarounds.
• 0:40
  We even monitored question frequency and training sessions,
• 0:43
  as well as error reporting rates.
• 0:46
  We looked at whether people were helping their colleagues learn
• 0:49
  the new system or quietly reverting the spreadsheets when
• 0:53
  no one was watching. The behavioral data told a
• 0:57
  completely different story than the survey.
• 1:00
  Actual adoption was 31%. Two out of three people who
• 1:05
  claimed to support the transformation were actively
• 1:08
  avoiding it in their daily work. They weren't lying on the
• 1:12
  survey. They genuinely believed they
• 1:15
  supported the initiative. But their behavior revealed what
• 1:19
  their conscious minds couldn't admit.
• 1:22
  They weren't psychologically ready for change.
• 1:26
  This gap between state of support and actual behavior is
• 1:31
  the measurement crisis that it's at the heart of transformation
• 1:35
  failure. And it's why everything that
• 1:37
  we've discussed in the 1st 9 episodes of this series, from
• 1:41
  resistance patterns to transformation fatigue, remains
• 1:45
  invisible to most organizations until it's far too late.
• 1:51
  I'm Kevin Novak, CEO of 2040, Digital Professor at the
• 1:55
  University of Maryland and author of the book The Truth
• 1:58
  about Transformation, Leading in the Age of AI, Uncertainty, and
• 2:03
  Human Complexity, as well as the Ideas and Innovations Weekly
• 2:07
  newsletter. Welcome to the Human Factor
• 2:10
  Podcast, the show that explores the intersection of humanity,
• 2:14
  technology, and transformation, along with the psychology behind
• 2:19
  transformation success. Today we're exploring how to
• 2:23
  measure the human factor, the psychological readiness that
• 2:27
  determines whether your transformation will succeed or
• 2:32
  become another casualty of the 70% failure rate.
• 2:35
  This connects directly to the subtitle of my book, Leading in
• 2:39
  the Age of AI Uncertainty in Human Complexity.
• 2:43
  Because in an era where technology changes faster than
• 2:47
  psychology can adapt, understanding how to measure
• 2:51
  what's actually happening inside your organization, not what
• 2:55
  surveys tell you is happening, becomes the difference between
• 2:59
  transformation success and complete or expensive failure.
• 3:05
  Here's the fundamental problem with how organizations measure
• 3:09
  transformation. We measure what people say
• 3:12
  instead of what they do. We ask people if they support
• 3:16
  the change, and we're surprised when stated support doesn't
• 3:21
  translate to behavioral change. We track training completion
• 3:25
  rates, and we assume that completing a course means
• 3:29
  someone has actually changed how they work.
• 3:32
  We count system logins, and we conclude that access frequency
• 3:37
  equals adoption. These aren't measurements of
• 3:40
  human factors, they're measurements of compliance
• 3:44
  theater and they explain why organizations keep investing in
• 3:49
  transformations that fail at 70% predictable rates despite all
• 3:55
  the dashboards showing them green.
• 3:58
  Today I'm going to share in the measurement framework we
• 4:01
  developed to 2040 digital to make psychological rating is
• 4:05
  visible and actionable for our clients.
• 4:09
  First, I want to share that if I sound a bit different this week,
• 4:12
  I had sinus surgery last week, so an active recovery.
• 4:17
  I wanted to do this episode because this is a topic that I'm
• 4:20
  incredibly passionate about. So let's start by understanding
• 4:24
  why the metrics you're currently using are probably lying to you.
• 4:29
  Research from implementation science reveals A consistent
• 4:33
  pattern across industries and transformation types.
• 4:36
  Self reported support for organizational change typically
• 4:39
  ranges between 70 and 85%. People genuinely believe they
• 4:44
  support the initiative, but actual adoption rates, measured
• 4:48
  by sustained behavioral change rather than survey responses,
• 4:52
  averages between 30 and 45%. That's a gap of 40 to 50% point
• 4:58
  percentage points between what people say and what they do.
• 5:03
  And here's the critical insight This isn't a communication
• 5:07
  problem or a treating gap. It's a measurement problem.
• 5:11
  We're measuring the wrong things, and then we're surprised
• 5:15
  when our Men First surveys measure intention, not behavior.
• 5:20
  When someone says they support a transformation, they're
• 5:23
  reporting their conscious intention.
• 5:25
  They genuinely believe they support it.
• 5:28
  But intention and behavior are governed by different
• 5:31
  psychological systems. Your conscious mind can commit
• 5:35
  to change while your unconscious mind is working overtime to
• 5:38
  protect you from it. This is exactly what we explored
• 5:42
  in Episode 8 on hidden resistance.
• 5:45
  The quality director who sincerely supports digital
• 5:48
  transformation still raises quality concerns that delay
• 5:52
  implementation. She wasn't lying.
• 5:55
  She's protecting herself from competence threat in ways that
• 5:59
  she can't consciously recognize. Surveys also nearly always drive
• 6:05
  the respondents to answers expected by the survey creators.
• 6:09
  Whether an individual or a group of authors create the survey,
• 6:13
  they are developing the questions, then they often to
• 6:17
  gain consistency response, develop the multiple choice
• 6:21
  answers that survey construction leads the respondents to choose
• 6:26
  from what was provided. In my consulting experience all
• 6:31
  these years, it rarely have I see the truth result from
• 6:35
  surveys. Those hidden gems of challenges,
• 6:39
  resistance of important knowledge, only present
• 6:43
  themselves outside of a survey construct, and only then can one
• 6:48
  recognize the very human behaviors that are manifesting
• 6:52
  and causing problems with the project.
• 6:55
  Second, training metrics measure compliance, not capability.
• 7:01
  When organizations track training completion rates or
• 7:04
  training test scores, they're measuring whether people showed
• 7:07
  up, not whether they retained information, and if they will
• 7:11
  put that knowledge into action, and not whether they embrace the
• 7:16
  change. The research on training
• 7:18
  transfer, the extent to which skills learned in training
• 7:22
  actually appear in job performance, is sobering.
• 7:25
  Studies consistently show that only 10 to 20% of training
• 7:29
  content translates to sustained behavior change on the job.
• 7:34
  Yet organizations continue to use training completion as a
• 7:38
  proxy for transformation readiness.
• 7:41
  Third, usage metrics measure frequency of access, not
• 7:46
  adoption. System logins, feature clicks
• 7:49
  and time, and application are all proxies for adoption, not
• 7:54
  evidence of it. Someone can log into a new
• 7:57
  system every day and still be doing their actual work in
• 8:00
  success spreadsheets. They've learned the minimum
• 8:04
  necessary to appear compliant while maintaining their
• 8:07
  comfortable workflows. This is one of the most common
• 8:12
  patterns we see in digital transformation.
• 8:14
  The dashboard shows 90% usage. The reality is maybe 40% of the
• 8:20
  people have genuinely changed how they work. 4th milestone
• 8:26
  metrics measure project progress, not psychological
• 8:30
  readiness. Traditional transformation
• 8:33
  scorecards track implementation milestones, technology deployed,
• 8:38
  training delivered, processes documented.
• 8:42
  These are important operational metrics, of course, but they
• 8:45
  tell you nothing about whether people are psychologically
• 8:49
  prepared to work differently. You can achieve every milestone
• 8:54
  and still fail the transformation because the human
• 8:58
  factors simply weren't ready. The fundamental problem is that
• 9:03
  we're measuring visible activities and assuming they
• 9:06
  reflect invisible psychology. It's like measuring the number
• 9:12
  of gym memberships sold and concluding that everyone in the
• 9:15
  city is fit. The membership is just a leading
• 9:19
  indicator of intention, not a measurement of outcome.
• 9:24
  And there is a lot as humans that we intend, that we aspire
• 9:29
  and even genuinely in the moment believe we will do or complete,
• 9:34
  whereas in reality we simply don't.
• 9:37
  So if traditional metrics measure the wrong things, what
• 9:42
  should we be measuring instead? This brings us to the framework
• 9:46
  we developed for making human factors visible.
• 9:50
  Our framework focuses on 4 domains of human factor
• 9:52
  measurement. Each domain addresses a
• 9:55
  different aspect of psychological readiness, and
• 9:58
  together they predict transformation success with
• 10:02
  significantly greater accuracy than traditional approaches.
• 10:06
  Let me walk you through each one.
• 10:09
  The first domain is behavioral readiness, which measures actual
• 10:12
  behavior patterns rather than stated intentions.
• 10:16
  Instead of asking people if they're ready for change, we
• 10:19
  observe whether their behaviors indicate readiness.
• 10:22
  So here are some specific indicators that we track work
• 10:26
  around frequency, which tells us how often people are creating
• 10:30
  parallel processes that bypass the new systems.
• 10:34
  Workarounds are a reliable indicator of psychological
• 10:37
  resistance. When someone says they support
• 10:40
  the new system but maintains their own spreadsheets just in
• 10:44
  case, they're demonstrating that their behavior hasn't actually
• 10:47
  changed. Feature depth versus feature
• 10:50
  breadth reveals whether people are using the full capabilities
• 10:54
  of new tools or only the minimum features required for
• 10:58
  compliance. The surface level adoption uses
• 11:02
  new tools to do exactly what old tools did.
• 11:05
  It suggests the psychological shift hasn't occurred.
• 11:09
  Proactive engagement versus reactive compliance shows
• 11:13
  whether people seek out information about the
• 11:15
  transformation or only engage when required.
• 11:19
  Someone who attends optional training sessions and ask
• 11:23
  questions in Teams meetings is behaviorally ready.
• 11:27
  Someone who does the minimum required is demonstrating
• 11:31
  resistance to what we call compliance theater.
• 11:35
  Help seeking patterns indicate people who are asking for help
• 11:39
  and how often psychologically ready individuals are asking
• 11:43
  questions early and very publicly.
• 11:46
  Those experiencing resistance either don't ask or they ask
• 11:50
  privately because they don't want to appear incompetent.
• 11:54
  Behavioral readiness tells us what people are doing.
• 11:58
  But behavior doesn't happen in a vacuum.
• 12:00
  It happens within an emotional environment that IR supports or
• 12:04
  undermines the change. Remember back to Elizabeth
• 12:08
  Stewart and I emphasizing the criticality of psychological
• 12:11
  safety in Episode 7. That then now brings us to our
• 12:15
  second domain, psychological safety, which measures the
• 12:20
  emotional environment for change.
• 12:23
  Transformation requires people to acknowledge what they don't
• 12:27
  know. They can make mistakes while
• 12:30
  learning and admit when they're struggling.
• 12:34
  If the environment doesn't feel safe for these behaviors, people
• 12:38
  will hide their difficulties and they'll fake adoption.
• 12:41
  This also connects directly to Episode 7, where Elizabeth and I
• 12:46
  talked about vulnerability being essential for transformation.
• 12:50
  Question frequency in meetings is a powerful indicator In
• 12:55
  psychologically safe environments.
• 12:57
  People ask questions publicly. When question frequency drops,
• 13:02
  it often indicates that people don't feel safe revealing what
• 13:06
  they don't understand. Error reporting rates tell us
• 13:12
  whether mistakes are being reported promptly or whether
• 13:15
  people are hiding errors until they become too big to conceal.
• 13:20
  The decrease in error reporting during transformation often
• 13:24
  means people are afraid of the consequences of admitting
• 13:27
  they're struggling with the new systems.
• 13:30
  Peer support dynamics reveal whether team members are helping
• 13:34
  each other or competing to appear competent.
• 13:39
  Psychologically safe teams share tips.
• 13:42
  They troubleshoot together and openly discuss challenges.
• 13:47
  Unsafe teams keep the struggles very private.
• 13:51
  Feedback quality matters as well.
• 13:54
  When people provide specific, constructive feedback about
• 13:57
  transformation challenges, it indicates psychological safety.
• 14:02
  When feedback becomes vague or disappears entirely, people
• 14:07
  don't feel safe about being honest and talking about the
• 14:11
  problems they're experiencing. Behavioral readiness and
• 14:15
  psychological safety tell us about current state issues.
• 14:20
  But transformation is a process that unfolds over time, so we
• 14:24
  also need to understand the trajectory of change.
• 14:28
  The third domain is adoption velocity.
• 14:31
  Adoption velocity measures the speed and quality of behavioral
• 14:35
  change over time. This domain helps identify
• 14:38
  whether people are genuinely progressing towards new
• 14:41
  behaviors or stuck in patterns of resistance.
• 14:45
  This includes learning curve progression, which determines
• 14:49
  whether people are improving at a normal rate or showing signs
• 14:53
  of stalled development. Where you see stalled learning
• 14:57
  curves, they often indicate psychological barriers that
• 15:01
  training simply can't address. Remember from episode 9 when I
• 15:05
  talked about cognitive resources being depleted?
• 15:09
  Learning capacity diminishes as a result, regardless of training
• 15:14
  quality. Another factor?
• 15:17
  Early adopter identification. It matters because in every
• 15:21
  organization, some people embrace change naturally.
• 15:25
  Identifying these early adopters and understanding their
• 15:28
  characteristics helps predict who else is likely to adopt and
• 15:33
  who will need some additional support.
• 15:35
  Another factor influence network activation, which tracks whether
• 15:40
  the early adopters are influencing each other.
• 15:43
  Transformation spreads through social networks.
• 15:47
  If early adopters aren't bringing their colleagues along,
• 15:50
  something is blocking the natural diffusion of the new
• 15:53
  behaviors. Another factor?
• 15:56
  Regressive patterns. They reveal whether people who
• 15:59
  adopted new behaviors are reverting to old ones under
• 16:03
  stress regression is one of the most reliable indicators of
• 16:07
  insufficient psychological readiness.
• 16:10
  The behavior changed temporarily, but underlying
• 16:14
  psychology didn't shift enough to sustain it.
• 16:18
  This brings us then to the ultimate question.
• 16:21
  Are changes actually sticking? Are they becoming part of how
• 16:25
  your organization operates, or will they fade when attention
• 16:29
  moves elsewhere? Let's talk about domain 4,
• 16:33
  sustainability indicators. Sustainability indicators
• 16:37
  measure whether behavior changes or becoming embedded habits or
• 16:42
  remaining fragile. Conscious efforts that will fade
• 16:44
  when leadership focuses on other priorities.
• 16:47
  Much about what I'm going to share requires active watching
• 16:52
  and listening of individuals across the organization.
• 16:56
  Yeah, system metrics help inform, but real listening
• 17:00
  becomes a superpower in determining if the organization
• 17:03
  and its culture has reached a level of sustainability with the
• 17:07
  transformation effort. Some examples here.
• 17:11
  Habit formation metrics, which determine whether new behaviors
• 17:15
  are becoming automatic. Early in transformation, people
• 17:19
  have to consciously choose new behaviors.
• 17:23
  Successful transformation means those behaviors have become the
• 17:26
  default. Cultural integration measures
• 17:30
  whether new behaviors are becoming part of their team
• 17:33
  identity. When teams start describing
• 17:36
  themselves in terms of the new approach rather than as people
• 17:40
  who used to work differently, culture has shifted.
• 17:44
  Continuous improvement engagement, which looks at
• 17:47
  whether people are suggesting improvements to new processes or
• 17:51
  just complying with what they were told to do.
• 17:55
  Genuine adoption leads to ownership, and ownership leads
• 17:59
  to improvement suggestions. Next, stress test resilience
• 18:04
  examines what happens when the organization raises pressure to
• 18:09
  new behaviors. Persist or do people revert to
• 18:12
  familiar patterns? The real test of transformation
• 18:16
  success isn't whether people can work differently when everything
• 18:20
  is calm, it's whether the new behaviors survive in the time
• 18:24
  crunched adversity. These 4 domains, behavioral
• 18:28
  readiness, psychological safety, adoption velocity, and
• 18:32
  sustainability work together to reveal what traditional metrics
• 18:36
  hide. Let me show you how this looks
• 18:39
  in practice by returning to the organization I mentioned in the
• 18:42
  opening. When we applied the four domains
• 18:45
  of human factor measurement to the organization where 82%
• 18:49
  survey support masked 31% actual adoption, here's what we
• 18:53
  discovered. In Behavioral Readiness, we
• 18:57
  found that 67% of employees had created personal workarounds
• 19:01
  that bypassed the new system. Feature Usage analysis showed
• 19:06
  that 78% of the users were only accessing 3 basic features
• 19:11
  despite the system having extensive capabilities that
• 19:14
  could transform their workflows. Help requests had dropped 40%
• 19:18
  since the transformation began, which initially looked like a
• 19:22
  positive sign until we realized that meant people have stopped
• 19:26
  trying to learn and we're simply doing a minimum to appear
• 19:29
  compliant. In psychological safety.
• 19:33
  We found the question frequency and transformation related
• 19:36
  meetings had dropped from an average of eight questions per
• 19:40
  meeting to two. Error reports had declined 60%,
• 19:45
  which leadership had initially interpreted a successful
• 19:48
  adoption. Now, in reality, people were
• 19:52
  hiding mistakes rather than reporting them.
• 19:55
  In interviews that we did with the teams, we discovered
• 19:58
  widespread fear of appearing incompetent.
• 20:01
  In the new system, people were simply afraid to ask questions
• 20:05
  because they thought everyone else had already figured it out.
• 20:09
  In adoption, velocity learning curve analysis revealed that 45%
• 20:14
  of the employees had plateaued at basic proficiency and it was
• 20:18
  within the first two weeks and they hadn't improved since.
• 20:22
  So earlier adopters existed, but they became isolated.
• 20:26
  They weren't influencing their peers because the brighter
• 20:29
  culture didn't show experimentation.
• 20:32
  The most concerning thing We found a 28% regression rate
• 20:37
  among people who had initially shown strong adoption.
• 20:41
  When quarter end pressures hit, they reverted to familiar
• 20:45
  processes because the new behaviors weren't sufficiently
• 20:48
  embedded. They went right back to what was
• 20:50
  comfortable and sustainability indicators.
• 20:53
  Habit formation metrics show that only 23% of employees were
• 20:58
  using the new system automatically.
• 21:01
  The rest were still consciously choosing between old and new
• 21:04
  approaches and choosing old often than not.
• 21:09
  Cultural integration simply just hadn't occurred.
• 21:12
  Teams still describe themselves by their workflows.
• 21:15
  When asked about their work, they say things like we're the
• 21:18
  team that handles the quarterly reports rather than describing
• 21:22
  their role in the new system. This data told a completely
• 21:26
  different story than the 82% survey support, but more
• 21:29
  importantly, it told us exactly what to address for the
• 21:33
  organization. The data allowed us to design an
• 21:37
  intervention that address the actual barriers, not the
• 21:41
  imagined ones. Instead of more training, which
• 21:44
  leadership that assume was the solution, we focused on
• 21:47
  psychological safety and identity threat.
• 21:50
  We created peer learning poems where small groups could
• 21:53
  struggle together without judgement.
• 21:56
  We redesigned error reporting to celebrate learning rather than
• 22:00
  punish the reported mistakes. We worked with managers to shift
• 22:04
  their language from are you using the new system to what are
• 22:08
  you learning as you work with the new system.
• 22:11
  We helped early adopters become visible mentors rather than
• 22:16
  isolating them as experts. Six months later, behavioral
• 22:21
  adoption had increased from 31% to 71%.
• 22:26
  Not because we train people better, but because we address
• 22:29
  the psychological barriers that need them unable to adopt what
• 22:33
  they already knew how to do. So how do you start measuring
• 22:38
  human factors in your own organization?
• 22:41
  Let me give you a practical approach that you can implement
• 22:44
  immediately. First, audit your current
• 22:48
  metrics. List every transformation metric
• 22:51
  that you're currently tracking. For each one, ask does this
• 22:56
  measure what people say or what they do?
• 23:00
  I can't stress this enough how important that determination is
• 23:03
  to any project success. Do your current metrics measure
• 23:09
  compliance or genuine capability?
• 23:12
  Capability change. You're likely to find that most
• 23:16
  of your metrics fall into the intention and compliance
• 23:19
  categories. That's not wrong, but it's way
• 23:23
  incomplete. Second, identify behavioral
• 23:27
  indicators for each domain. You don't need sophisticated
• 23:32
  measurement systems to start. Look for simple behavioral
• 23:35
  signals and behavioral readiness.
• 23:38
  Count workarounds and survey teams about parallel processes
• 23:43
  and psychological safety. Track question frequency in
• 23:46
  meetings and notice whether errors are being reported or
• 23:50
  hidden and adoption velocity. Identify your early adopters and
• 23:55
  ask whether they're influencing others and sustainability.
• 24:00
  Pay attention to what happens under pressure.
• 24:04
  Third, create baseline measurements before assuming you
• 24:08
  understand the current state. Measure the actual current state
• 24:12
  of human factors before launching any planned
• 24:15
  interventions. Most organizations don't do
• 24:18
  this, which means they can't tell whether their interventions
• 24:21
  are working or whether adoption was going to happen anyway. 4th,
• 24:26
  triangulate data sources. No single metric tells the whole
• 24:31
  story. Use multiple indicators for each
• 24:35
  domain. Look for patterns across those
• 24:38
  particularly chosen domains. When behavioral readiness,
• 24:42
  psychological safety, adoption velocity, and sustainability
• 24:45
  indicators all point in the same direction, you can become pretty
• 24:49
  confident in your assessment. 5th, use measurement as
• 24:54
  intervention. The act of measuring human
• 24:57
  factors can itself change behavior.
• 25:01
  When people know that psychological safety is being
• 25:04
  tracked, managers pay more attention to it.
• 25:07
  When workarounds are being counted, people become more
• 25:10
  conscious of them. Measurement, then, isn't just
• 25:14
  about data, it's about signaling what the organization values.
• 25:19
  Everything I've described so far helps you measure human factors
• 25:23
  during transformation. But what about measuring
• 25:27
  readiness before a transformation begins?
• 25:30
  This is where you can prevent problems rather than just
• 25:34
  diagnosing them. The best time to understand
• 25:37
  psychological readiness is before you launch your
• 25:39
  initiative. Once transformation is under
• 25:42
  way, you're measuring resistance that already has formed.
• 25:45
  But if you can assess readiness in advance, you can address the
• 25:50
  barriers before they become entrenched in the culture.
• 25:53
  The understanding informs the plan, the activities, and yes,
• 25:58
  measures that become your hinge points to achieving your goals.
• 26:02
  At transformationassessment.com, we've built an assessment based
• 26:06
  on years of research and consulting experience.
• 26:09
  It measures the gap between stated intentions and likely
• 26:13
  behaviors. The assessment examines 5
• 26:16
  dimensions of transformation readiness.
• 26:18
  The first, leadership alignment, measures whether your leadership
• 26:23
  team is genuinely unified around the change or fractured in ways
• 26:27
  that will create resistance. Next, capability readiness,
• 26:31
  which assesses whether people have the skills they need and
• 26:34
  feel confident in their ability to develop new ones.
• 26:38
  Next, Cultural preparedness, examines the psychological
• 26:42
  safety and openness to change in your organizational culture.
• 26:46
  Next, communication effectiveness, which determines
• 26:50
  whether your messaging is creating clarity or confusion.
• 26:54
  Next, Engagement Foundation, which measures the quality of
• 26:58
  relationships and trust. The change will be built upon
• 27:01
  across the organization. What makes this assessment
• 27:04
  different from typical engagement surveys is that it's
• 27:07
  designed to reveal the gap between conscious support and
• 27:11
  unconscious readiness. The questions are structured to
• 27:14
  surface the psychological barriers that people can't self
• 27:17
  report directly because they're not consciously aware of them.
• 27:22
  For leaders then planning their next initiative, the assessment
• 27:25
  provides the kind of pre work that separates successful
• 27:28
  transformations from the 70% that fail.
• 27:32
  It helps you know where the psychological landmines are
• 27:37
  before you step on them. Take the assessment at
• 27:40
  transformationassessment.com. The measurement framework we
• 27:45
  discussed today, the four domains, the behavioral
• 27:48
  indicators, and the readiness assessment represents A
• 27:52
  fundamentally different approach to understanding transformation.
• 27:56
  Instead of asking people what they think, we observe what they
• 28:01
  do. Instead of measuring compliance,
• 28:04
  we measure genuine psychological change.
• 28:07
  Let me leave you with this perspective.
• 28:10
  The gap between state and support and actual adoption
• 28:13
  isn't a communication failure or a training problem.
• 28:17
  It's a measurement problem. We've been measuring the wrong
• 28:20
  things, and then we're surprised when our green dashboards don't
• 28:24
  predict green outcomes. We know the traditional
• 28:27
  transformation metrics measure all of the wrong things.
• 28:32
  Surveys measure intention, not behavior.
• 28:35
  Training metrics measure compliance, not capability.
• 28:40
  Usage metrics measure access, not adoption.
• 28:45
  Milestone metrics measure project progress, not
• 28:49
  psychological readiness. We know that there's a gap
• 28:53
  between what people say versus what they do.
• 28:56
  The four domains of human factor measurement provide a more
• 28:59
  accurate picture. Behavioral readiness measures
• 29:02
  what people actually do, not what they say they'll do.
• 29:06
  Psychological safety measures whether the environment supports
• 29:10
  honest struggle in learning adoption velocity measures the
• 29:15
  speed and quality of behavior change over time, and
• 29:18
  sustainability indicators measure weather changes are
• 29:22
  becoming embedded habits. When you measure human factors
• 29:27
  instead of just activities, you can identify barriers before
• 29:31
  they become fatal, you can design interventions that
• 29:35
  address real problems, and you can predict transformation
• 29:40
  success with much greater accuracy.
• 29:44
  In our next episode, I'm exploring a danger that
• 29:47
  threatens every successful organization.
• 29:51
  It's called drift. What happens when the very
• 29:54
  success that built your market position becomes the
• 29:57
  psychological barrier that prevents you from seeing where
• 30:00
  the market is heading? Do iconic companies like
• 30:04
  Blockbuster, Kodak, and BlackBerry fail?
• 30:08
  Not because of one catastrophic decision, but through thousands
• 30:13
  of small, seemingly reasonable choices that gradually pulled
• 30:18
  them away from the relevance. How do you recognize when your
• 30:23
  organization has shifted from actively steering to passively
• 30:27
  floating, becoming a passenger instead of a captain?
• 30:33
  Episode 11 then examines the four stages of organizational
• 30:37
  drift, the six human factors that enable it to take hold, and
• 30:42
  the strategic framework for building the awareness that
• 30:44
  prevents drift before it becomes fatal.
• 30:48
  If you found today's episode valuable, subscribe to the Human
• 30:51
  Factor Podcast. Wherever you listen to the
• 30:54
  podcast, leave a rating and a review and share this episode
• 30:59
  with colleagues who are struggling to understand why the
• 31:02
  transformation metrics aren't predicting the outcomes that
• 31:05
  they expect. To explore these concepts
• 31:08
  further, visit 2040 digital.com for the Change Leadership series
• 31:13
  and subscribe to my Ideas and Innovations newsletter on Sub
• 31:17
  Stack. Until next time, remember, you
• 31:20
  can't transform an organization without transforming the humans
• 31:24
  in it, and you can't transform what you don't measure.
• 31:28
  And finally, transformation isn't about technology, it's
• 31:32
  about people. This has been the Human Factor
• 31:35
  podcast. I'm Kevin Novak, thanks for
• 31:38
  watching or listening.