The Traffic You Depend On Is Being Answered Without You

I’ve been staring at a traffic chart for the last three weeks that I can’t stop thinking about.

It’s Chegg’s chart. The online education platform lost 34% of its organic visitors in a matter of months. That’s a cliff. Their keyword footprint went from 11.1 million to 3.5 million.

And the culprit wasn’t a competitor outranking them or a Google algorithm update penalizing thin content. It was Google answering the questions before anyone ever clicked.

The Machine That Eats Your Top of Funnel

Google’s AI Overviews are the AI-generated summaries that now appear at the top of search results, and they are fundamentally changing what it means to rank on Google. For years, the playbook was clear: create valuable content, optimize it for search, capture intent, convert visitors.

That model assumed one thing: that people would actually click through to your site.

AI Overviews break that assumption.

When someone searches “how to explain forgiveness to a congregation” or “best illustrations for an Easter sermon,” Google can now synthesize an answer from multiple sources and present it directly in the search results. No click required. No visit to your site. No entry into your funnel.

Tomasz Tunguz laid this out clearly in a recent analysis:

“Content dependency on organic search is no longer a sustainable acquisition model.”

That sentence should be pinned to the wall of every SaaS product leader who relies on organic traffic (understanding these shifts is a critical PM skill) to fill the top of their funnel.

Chegg Is the Preview

The pattern is showing up everywhere. Stack Overflow, the platform that essentially taught a generation of developers how to code (including me), is seeing the same erosion. Informational queries that used to drive millions of visits are now being answered inline by AI.

The New York Times is thriving. Why? How? A $100 million content licensing deal with Google. They’re feeding the AI, on their terms, for revenue.

Here’s what I think the data is telling us:

1. Q&A-style content is the most vulnerable. If your value proposition is answering questions that can be summarized in a paragraph, you’re in the blast radius.
2. Branded, premium, behind-the-paywall content is more defensible. AI Overviews can summarize a sermon topic, but they can’t replicate a full manuscript, a downloadable media pack, or an AI-powered sermon builder.
3. The winners will be the ones who stop treating Google as a given and start building direct relationships with their audience.

What This Means for SaaS Product Leaders

I run product and growth for a content platform that serves pastors. We have 245,000+ sermons and 50,000+ text illustrations, exactly the kind of content library that ranks well for long-tail informational queries.

For years, that library has been our primary discovery engine. Pastors search for sermon ideas, find us, browse free content, start a trial, and convert to paid.

That model still works today, but we’re down around that same 34% mark and from what I can tell so is everyone, across all industries. But I’d be naive to assume it’ll work the same way in 18 months.

Here’s the uncomfortable math: if organic traffic drops by even 20-30%, and organic is your dominant acquisition channel, no amount of conversion rate optimization saves you. You can have a best-in-class trial-to-paid flow and still miss your numbers because not enough people are entering the funnel in the first place.

It’s an exposure problem. And it requires a fundamentally different response than what most product teams are used to.

The Diagnostic Before the Panic

Before you restructure your entire growth strategy, there’s a critical diagnostic step that teams often skip. You need to know whether AI Overviews are actually appearing on YOUR highest-value queries.

Here’s the move:

  • Pull your top 50 keywords from Google Search Console. Look at click-through rate trends over the last 90 days, segmented by week.
  • The signature you’re looking for: stable or rising impressions, but declining CTR. That pattern means Google is showing your content in results, but users aren’t clicking because the AI Overview already gave them what they needed.
  • If your impressions are dropping, that’s a competitor or algorithm problem. If impressions are stable but clicks are falling, that’s AI Overview cannibalization. Different diagnosis, different treatment.

Most teams I talk to are just making this distinction. They’re looking at traffic declines and assuming it’s an SEO problem when it might be a platform shift problem. The difference matters.

Three Moves to Make Now

I’m not going to pretend I have the full playbook figured out. But here’s where my thinking is landing:

1. Shift discovery investment toward owned channels.
Email nurture sequences, community platforms, pastoral networks, partnerships with organizations that already have the audience. Organic search should be one of many channels, not the only one. Every dollar of effort I’m putting into SEO-driven top-of-funnel content I’m asking if that same effort in email or community would be more durable.

2. Make your paywall content genuinely irreplaceable.
AI can summarize a sermon outline. It cannot replicate a curated media pack, a professionally produced video series, or a workflow tool that saves someone three hours a week. The content that survives AI summarization is the content that requires depth, production value, or interactivity: things a search snippet can’t deliver.

3. Explore whether the threat is also an opportunity.
The NYT licensing deal tells us something important: Google is willing to pay for premium vertical content. If you’re the dominant content platform in your niche, there may be a deal to be made.

A licensing partnership could convert a traffic threat into a revenue stream while maintaining brand visibility inside AI-generated results. Worth exploring.

The Bigger Lesson

I keep coming back to something I’ve learned over the last few years leading product: the most dangerous risks are the ones that look like stability. Traffic holding steady today doesn’t mean the foundation isn’t shifting underneath.

Chegg’s team didn’t wake up one morning to a 34% traffic drop. It happened gradually, then suddenly. The chart looks normal until it doesn’t.

The product leaders who navigate this well will be the ones who diagnosed early, diversified before they had to, and built value that can’t be summarized in a paragraph. The ones who don’t will be staring at a chart they can’t explain and wondering where all the visitors went.

I’d rather be asking the hard questions now than explaining the traffic decline later.

The Big Five Personality Traits: What Every Change Leader Needs to Know

Most change management initiatives fail. Not because the strategy was wrong or the technology didn’t work but because leaders treated a room full of unique human beings the exact same and expected they would all respond to change the same way.

They won’t. They never do.

After more than a decade leading product and organizational change, running platform modernizations, launching new products, and driving cross-functional alignment at companies serving millions of users, I’ve learned one thing: how people respond to change is largely predictable if you’re paying attention to the right signals.

The Big Five personality model gives you a scientific framework for doing exactly that. It won’t tell you everything about a person. But it will tell you enough to stop being surprised when your most methodical engineer resists a process change that your most curious designer is already championing at lunch.

This article breaks down what the Big Five actually is, what each trait means in practice, and how you can apply it specifically to change management no matter what your title is.


What Is the Big Five Personality Model?

The Big Five — also called the Five-Factor Model (FFM) or referred to by the acronym OCEAN — is the most empirically validated framework in personality psychology. This isn’t Myers-Briggs, which has significant reliability problems. This isn’t an astrology-adjacent personality quiz. The Big Five emerged from decades of peer-reviewed psychometric research and is the standard model used in academic personality research worldwide.

The framework originated from what researchers call the lexical hypothesis: the idea that the most important personality traits in any culture will inevitably be encoded in its language. In the 1930s, psychologists Gordon Allport and Henry Odbert catalogued over 4,500 English adjectives used to describe people (I love this idea and think it would be so interesting to have watched them come up with some of the silly ones). From there, researchers spent decades using factor analysis, a statistical technique for identifying patterns in data, to cluster those descriptors into broader dimensions.

By the 1960s, Warren Norman had consolidated the research into five robust factors. In the 1980s, Paul Costa Jr. and Robert McCrae developed the NEO Personality Inventory, which remains the most widely used Big Five assessment today.

The key distinction from other personality models: the Big Five measures traits on a continuous spectrum, not binary categories. You’re not an “introvert” or an “extravert” but you fall somewhere on a range. That nuance matters enormously when you’re managing real people through real change.

The five traits, spelled out by the OCEAN acronym, are: Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism.

Let’s go through each one in detail.


O — Openness to Experience

What it measures: Creativity, intellectual curiosity, and willingness to engage with new ideas, abstract thinking, and novel experiences.

High scorers tend to be imaginative, intellectually adventurous, and genuinely excited by complexity. Low scorers tend to be practical, conventional, and preference-stable — they want proven methods over experimentation.

Neither end of the spectrum is “better.” High openness without the grounding of conscientiousness can produce someone who loves ideas but ships nothing. Low openness combined with high conscientiousness can produce your most reliable operators.

In change management: High-openness people are your early adopters. They’ll be intrigued by the change, ask the interesting questions, and often become your internal champions. I recently had a large launch and my main champion was so excited that she had been using the prototype before I had even let some of my development team know about the project. The risk with high-openness individuals is that they get excited about the idea of change and then lose interest during the unglamorous implementation phase. I kept my champion excited by only introducing small features to her throughout the build.

Low-openness individuals will resist change more instinctively, not because they’re obstinate, but because they’re wired to value stability and proven approaches. What they need from you is not enthusiasm, it’s evidence. Show them data, precedent, and a clear picture of what stays the same. They’re not your enemy in a change initiative. Ignored, they become your loudest critics. Engaged correctly, they become your quality control. This guy is on my team too. He’s difficult to deal with if I don’t give him the data, but I’ve looked at it as a win because it does force me to slow down and get the data. I know he’s going to be asking me questions and I try to have the answers before he arrives.

The practical play: Segment your communication strategy. Don’t send one change announcement to your entire organization and assume it lands equally. High-openness stakeholders want to be in the room early, contributing to the shape of the change. Low-openness stakeholders want to see the pilot results before they commit. Build your rollout timeline to accommodate both.


C — Conscientiousness

What it measures: Self-discipline, organization, dependability, and goal-directedness. Essentially: how reliably does this person follow through?

High scorers are methodical, thorough, and tend to plan ahead. They show up on time, deliver on commitments, and prefer structured environments. Low scorers are more spontaneous, flexible, and sometimes prone to procrastination — but also often more adaptable in chaotic environments.

In change management: High-conscientiousness people are your implementation backbone. Once they buy into a change, they will execute it more reliably than anyone else in the room. The challenge is that they need the full picture before they commit. Launch an initiative without a detailed plan and they’ll spend the entire kickoff meeting asking questions that feel obstructionist but are actually their brain trying to build the mental model they need to be effective.

Low-conscientiousness people adapt to change more easily in terms of mindset but more erratically in terms of execution. They’re comfortable with ambiguity, which is valuable in early-stage change, but they need more structural accountability to follow through on the consistent behaviors that make change actually stick.

The practical play: During change planning, put your high-conscientiousness people in charge of the process design. Give them the runway to build the playbook. During rollout, give them clear milestones and let them hold the team accountable — they’ll do it naturally. For low-conscientiousness team members, build in more check-in touchpoints and make progress visible publicly. Not as surveillance, but as external structure that replaces the internal structure they don’t naturally have.


E — Extraversion

What it measures: Energy drawn from social interaction, assertiveness, tendency toward positive emotion, and degree of talkativeness and engagement in group settings.

This is the most commonly misunderstood trait. Introversion is not shyness. Extraversion is not confidence. The dimension is about where you draw energy from, social engagement energizes extraverts and drains introverts, not the other way around.

High extraverts are vocal, enthusiastic in group settings, and often the first to speak up. High introverts process internally, may need more time before contributing, and tend to prefer one-on-one conversations over all-hands forums.

In change management: Extraverts will often create the social momentum a change initiative needs. They talk about it at lunch, they advocate in meetings, they make it feel like something real is happening. That’s enormously valuable — but it can also mean they’re generating buzz ahead of the evidence, which creates a credibility gap if the initiative stumbles.

Introverts are processing the change deeply but quietly. The danger is confusing their silence with acceptance or indifference when they might be holding substantive concerns that never surface in a town hall setting. Some of the sharpest change-resistant thinking I’ve encountered came from introverted team members who raised it six weeks later in a one-on-one after everyone thought we were past the debate phase.

The practical play: Don’t let all-hands meetings be your only feedback channel. They structurally favor extraverts. Build in async feedback mechanisms — surveys, Slack threads with explicit prompts, written pre-reads before meetings — that give introverts the processing space they need. And deliberately seek out your quiet team members one-on-one before major decisions close. You’ll learn things you never would have heard in a group setting.


A — Agreeableness

What it measures: Cooperativeness, empathy, trust, and prioritization of social harmony. How inclined is this person to put others’ needs above their own?

High agreeableness correlates with warmth, generosity, and conflict avoidance. Low agreeableness correlates with competitiveness, skepticism, and willingness to challenge or confront. Confronting doesn’t necessarily look like hostility, but there may be a higher tolerance for tension.

In change management: This is the trait that creates the most dangerous blind spots for change leaders. High-agreeableness individuals will often nod along with a change initiative in a group setting even when they have legitimate reservations because disagreeing publicly feels like a social cost they’d rather avoid. When you see heads nodding around the conference table, do not assume buy-in.

Low-agreeableness individuals will push back openly and sometimes aggressively. That can feel uncomfortable and even disrespectful in a change rollout. One thing I’ve learned to appreciate (as alluded to above) is the person who tells you directly that your change plan has a hole in it, they are actually doing you a favor. The person who agrees in the meeting and then quietly undermines the initiative in the hallway is the real risk.

The practical play: Create explicit, structured opportunities for dissent. Not just “does anyone have concerns?” at the end of a packed meeting, but dedicated pre-mortem exercises, anonymous surveys, or devil’s advocate assignments that normalize pushback as part of good process. This gives high-agreeableness people a structured reason to voice concerns (it’s the process, not personal conflict) and channels the energy of low-agreeableness people productively into improving the plan rather than resisting it.


N — Neuroticism

What it measures: Emotional volatility, sensitivity to stress, and tendency toward negative emotional states like anxiety, irritability, and self-doubt.

High scorers experience stronger emotional reactions to uncertainty and stress. Low scorers (sometimes called emotionally stable) tend to remain calm under pressure and recover from setbacks more quickly.

This is the trait that demands the most careful handling in a leadership context. Neuroticism should not be viewed as a weakness or a character flaw. I do think there is a maturity level where it may appear as aspects of Neuroticism, but Neuroticism is a genuine dimension of human experience that shapes how people respond to threat and uncertainty. And organizational change is perceived as a threat by more of your team than you probably realize.

In change management: High-neuroticism team members will likely experience change as significantly more stressful than their low-neuroticism peers, even if the change is objectively positive. They need more frequent reassurance, more visibility into what’s coming, and more explicit communication that their role and contributions are valued. If they’re experiencing change anxiety and you’re not addressing it, it will express itself as resistance, absenteeism, or performance decline.

Low-neuroticism individuals may be so unfazed by change that they underestimate the impact it’s having on their teammates. If you’re a leader who naturally scores low in neuroticism, this is your blind spot. Just because you’re energized by the change doesn’t mean everyone else is. Watch for signals in your team: short tempers, declining work quality, missed deadlines during the transition period. These are symptoms, not character issues.

The practical play: Increase your communication frequency during change and especially about what’s NOT changing. The human brain in stress mode fills uncertainty with worst-case assumptions. Every uncertainty you don’t address explicitly will be addressed implicitly by anxiety. Over-communicate the stable elements: this team stays together, your role isn’t going anywhere, here’s exactly what the next 30 days look like. Predictability is medicine for high-neuroticism team members.


Putting OCEAN to Work: A Change Management Framework

Understanding the five traits individually is useful. Using them together is where the real leverage is.

Here’s how I’ve applied this thinking practically in change initiatives:

Start with team mapping, not org charts. Before you launch a change initiative, spend time mapping your key stakeholders across the OCEAN dimensions based on what you’ve observed. These aren’t formal assessments, but your working knowledge of how these people behave. Who asks the most questions before committing? (High conscientiousness / low openness.) Who nods in meetings but raises concerns later privately? (High agreeableness.) Who goes quiet during stressful periods? (High neuroticism.) This map tells you who needs what from you.

Design your communication strategy around the spectrum, not the average. Most change communications are written for the mythical average employee: moderately open, moderately agreeable, moderately stressed. That person doesn’t actually exist in your organization. Write for the ends of the spectrum. Give your low-openness people evidence and precedent. Give your high-neuroticism people explicit, frequent reassurance. Give your introverted team members async channels to process and respond. One message, multiple formats and frequencies.

Use personality diversity as a feature, not a bug. The knee-jerk response in change management is to minimize resistance. The better instinct is to channel it. High-conscientiousness skeptics will pressure-test your process and find the gaps before they become launch-day disasters. Low-agreeableness team members will surface the honest objections everyone else is thinking but not saying. High-neuroticism individuals will be acutely sensitive to signals that something is off and they’re often right. Build a change governance structure that treats these people as assets, not obstacles.

Match your change champions to the stakeholders they’re influencing. A high-extravert, high-openness champion will be brilliant at building excitement in your early adopters. They’re probably the wrong person to walk your most cautious, routine-oriented team members through the transition. Match your internal advocates to the personality profiles of the people they need to bring along. This is people strategy, not manipulation, it’s meeting people where they actually are.


A Note on Using This Responsibly

The Big Five is a lens, not a label. People are more complex than five dimensions, their trait expressions shift with context, and nobody should be reduced to their personality profile in a change initiative or anywhere else.

What this framework does is expand your range of hypotheses. Instead of concluding that your cautious colleague is “resistant to change”, which puts the problem on them and takes it out of your hands, you have a more useful hypothesis: they may be low-openness and high-conscientiousness. That means they need evidence and a clear plan, not enthusiasm. That’s a solvable problem. “Resistant to change” isn’t.

Used that way, the Big Five doesn’t box people in. It opens up more humane, more effective ways of leading them through the hardest parts of organizational life.


Frequently Asked Questions

What is the Big Five personality model?

The Big Five, also known as the Five-Factor Model (FFM) or OCEAN, is an empirically validated framework that measures human personality across five dimensions: Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism. Unlike personality typing systems that sort people into categories, the Big Five measures each trait on a continuous scale, making it a more accurate representation of the actual range of human personality.

How does personality affect change management?

Personality traits significantly shape how individuals perceive, process, and respond to organizational change. People high in Neuroticism typically experience change as more stressful and need more frequent, explicit communication. People high in Openness tend to embrace change early but may disengage during implementation. People high in Conscientiousness need structured plans before committing. Understanding these tendencies allows change leaders to design communication strategies, rollout timelines, and feedback mechanisms that meet people where they actually are rather than where leaders wish they were.

Should you give your team a Big Five assessment?

Formal assessments can be useful, but they’re not required to apply this framework. Effective leaders can identify rough trait profiles through observation and noticing who asks detailed questions before committing, who speaks up readily in group settings versus one-on-one, who seems energized versus stressed by ambiguity. Formal assessments add precision; behavioral observation gets you most of the way there and doesn’t require an HR initiative to begin.

Is the Big Five better than Myers-Briggs for organizational use?

For research-backed applications, yes. The Big Five has substantially stronger empirical support than Myers-Briggs (MBTI), which has been criticized for low test-retest reliability, meaning people often get different type assignments when they retake it. The Big Five is the standard model in academic personality research precisely because of its consistency and predictive validity. For organizational change management specifically, the Big Five’s continuous scale model is also more practically useful because it captures the nuance that binary type systems miss.

What is the most important Big Five trait for a change leader to understand?

Neuroticism. Not because it’s more common, but because it’s most likely to be invisible until it creates problems. High-neuroticism team members experience genuine distress during organizational change that can express itself as resistance, disengagement, or performance decline if it’s not addressed. And leaders who naturally score low in neuroticism often don’t notice it in their team because they’re not experiencing the same stress response. Understanding and proactively addressing the anxiety dimension of change is one of the highest-leverage moves a change leader can make.

AI Just Walked Into Your Website Without Knocking

Last month I asked ChatGPT a question I’ve asked Google a thousand times: “What’s a good sermon illustration about forgiveness?”

It gave me a solid answer. Three illustrations, structured with context, application points, even a suggested closing line. It was genuinely useful.

And it never sent me to a single website.

That moment hit me differently than it would have two years ago. I run a platform with over 245,000 sermons and 50,000 illustrations. I didn’t just lose a click. I watched an AI system do what our product does, using content that likely came from sites like ours, and deliver it in a way that made visiting the source unnecessary.

That’s a revenue problem. (I wrote about the traffic implications of this shift recently.) (I wrote about the traffic implications of this shift recently.)

The Zero-Click Layer

Most product leaders I know are still thinking about AI as a feature to bolt onto their product: chatbots, smart search, AI-generated recommendations. And that matters. But there’s a bigger shift happening underneath that conversation.

AI answer engines (ChatGPT, Google AI Overviews, Perplexity) are becoming the front door to the internet. They don’t just search. They visit your site, interpret your content, synthesize it, and serve it directly to the user. The user gets the answer. You get nothing.

Google’s featured snippets started this zero-click trend years ago. BUT what’s different now is the depth. A featured snippet pulls a paragraph. An AI answer engine can synthesize an entire page, or multiple pages, into a comprehensive response that genuinely satisfies the user’s intent.

If your business depends on organic traffic as a top-of-funnel engine, this should keep you up at night.

Your Content Library Is Both Your Greatest Asset and Your Biggest Vulnerability

Here’s the paradox I’ve been sitting with.

We spent years building one of the largest structured content libraries in our space. That library is what drives our organic traffic. It’s what Google indexes. It’s what pastors find when they search “sermon on grace” at 11pm on a Saturday night.

That same library is now what AI systems are ingesting to train their models and generate their answers. The very content that built our moat is being used to fill in the moat.

And here’s what makes it worse. The emerging AI-native competitors in our space don’t even need to win Google rankings. They ARE the AI tool. They’re built to live inside AI workflows, not compete for traditional search clicks.

I think this pattern applies to any SaaS company sitting on a large content asset. If you’ve built your growth engine on content that AI can summarize, you’re exposed.

AEO: A Genuinely Different Discipline

There’s a term gaining traction: AEO, or AI Engine Optimization. And I’ll be honest, my first reaction was skepticism. We don’t need another three-letter acronym.

But the more I’ve dug into it, the more I realize it represents a genuinely different discipline.

SEO optimizes for ranking. AEO optimizes for citation. The goal is to be the source that AI systems reference AND link back to. That requires a fundamentally different content strategy.

Here’s what that looks like in practice:

  1. Structured data becomes non-negotiable. Schema markup, clear metadata, explicit problem-solution framing in your content. AI systems parse structure, not vibes. (Schema.org is the starting point.)
  2. Content architecture matters more than keyword density. How your content is organized (headers, relationships between pages, internal linking) determines how AI systems understand your authority on a topic.
  3. Gated content is a double-edged sword. If your best content is behind a login wall, AI crawlers can’t index it. You’re invisible to the answer engine. But if everything is open, you get summarized without a click. The play is in the middle: structured preview content that AI can cite, with depth that requires the visit.
  4. Domain-specific language is your moat. Generic content gets synthesized away. Content that uses the precise language of your audience (the way a pastor describes their Saturday night prep struggle, the specific vocabulary of sermon structure) is harder for AI to replace and more likely to be cited with attribution.

What I’m Doing About It

I’m not going to pretend I have this figured out. But here’s where my head is:

Audit how AI sees us. Before optimizing anything, we need to understand how our top pages render to AI crawlers. What structured data exists? What’s behind login walls that blocks indexing?

Treat AI referral as a distinct channel. We track direct traffic, organic search, paid. AI referral needs its own lane in our analytics. We can’t optimize what we can’t measure.

Build content AI can’t summarize away. The full sermon text? AI can handle that. But a pastor’s framework for adapting a sermon to their specific congregation? A diagnostic tool for matching an illustration to a particular emotional moment in a service? That’s interactive, personalized, and requires being on the platform.

Move faster than the AI-native competitors. They have the structural advantage of being built for AI workflows. We have the structural advantage of 20+ years of trusted content and relationships. The question is whether we can adapt our distribution before they build our depth.

The Strategies That Got You Here Won’t Sustain You

I keep coming back to this. The strategies that built organic growth over the last decade won’t sustain it over the next five years.

That’s a reason to move, not a reason to panic.

The companies that treat AI answer engines as a new channel will capture disproportionate share of the next era of discovery. The ones that keep optimizing for Google page one while AI summarizes their content into zero-click answers will watch their traffic erode and wonder what happened.

I’d rather be early and wrong about the tactics than late and right about the trend.

The AI just walked into your website. The question is whether it’s going to send people your way, or make visiting you unnecessary.

Marketing Dashboards

In my role at FSI.co I deal with an overwhelming amount of data. To make it simpler, I’m going to focus on one segment of the data that I’ve been trying to get a grasp on so that I can help further our mission – to be known as the provider for polyurethane chemical systems.

I’m challenging our Digital Marketing Director to develop dashboards so the executive team can quickly see and digest how effective the marketing campaigns we run are. As I’ve been researching business intelligence further, I am beginning to understand that finding data points is often too easy, and throwing up random data on a dashboard lives in the primary stage of DATA.

Let’s back up here and explain the four stages of DIKW otherwise known as the Wisdom Hierarchy. This is a way of categorizing data into four distinct levels: Data, Information, Knowledge and Wisdom.

  • Data is raw data that has not been organized or interpreted. For example, temperature readings in various regions.
  • Information is data that has been categorized and organized according to certain criteria.
  • Knowledge is “justified true belief”, as defined by Plato. It includes additional relational information such as correlations, causation, logic and conditions for the models to hold. This knowledge can then be put into actionable models which are a form of knowledge in themselves.
  • Wisdom comes from being able to identify and apply this relevant knowledge in meaningful ways.

So how would all of this help us in this example of a dashboard I’m preparing to setup in the Marketing department?

I listened to a podcast recently where Forrester’s VP & Principal Analyst Ross Graber stated: “Our latest buying study showed us that on average buyers are going through 27 different motions before they make a successful purchasing decision.”

That statistic aligns with what I’ve been hearing for the last year or two. That 27 motions are not time boxed either. As an example, one of our chemical systems is such a large scale decision that it takes roughly 5 years to move the purchasing organization along the buyer’s journey from Awareness to Decision.

My goal with setting up the dashboard is to be able to identify these 27 interactions and see where we can help answer questions or minimize risks, fears, anxieties the business may have. How can we turn a 5 year decision into a 2 year decision?

That is where wisdom is in the DIKW hierarchy.

Schneiderman’s Eight Golden Rules

Ben Schneiderman worked in Human-Computer Interaction and his research revealed these eight golden rules for interface design.

  1. Strive for consistency. Use familiar icons, colors, menu styles, calls to action, etc.
  2. Enable users to use shortcuts. Users who use your product often will inevitably understand it and no longer need directions on how to use it. They will start looking for ways to move through the interface quicker, provide them shortcuts.
  3. Offer informative feedback. Breadcrumbs and ripple effects on websites, ATM noises, haptic responses on phones/watches are examples of informative feedback.
  4. Design dialogue to yield closure. Thank you messages after purchase, Congratulations after sign-ups, these messages close the interaction for the user.
  5. Offer simple error handling. This reminds me of back in the day when forms were really hard to develop and if you filled one out incorrectly, you would lose all of your information when the page kicked you back. Simple error handling flags fields that may have been missed or filled out improperly.
  6. Permit easy reversal of actions. If the user feels comfortable that errors are reversible, they will explore more.
  7. Support internal locus of control. If your users explore more, they will feel more in control and ultimately trust your application or company more.
  8. Reduce short-term memory load. Human attention is limited. We are only able to remember five things at a time (give or take 2). Recognition is always easier than recalling something.

Deep Dive Resources:

https://developer.apple.com/design/human-interface-guidelines/

This post is part of a series of quick informative lists I can refer back to when doing research or preparing presentations.

Information Facts of Life

According to an article from HBR (March-April 1994), there are rules governing information sharing behavior. Having run across these rules doing some Change Management research this morning, I find these rules relevant even 26 years later.

  • Most of the information in organizations – and most of the information people really care about – is not on computers.
  • Managers prefer to get information from people rather than computers; people add value to raw information by interpreting it and adding context.
  • The more complex and detailed an information management approach, the less likely it is to change anyone’s behavior.
  • All information does not have to be common; an element of flexibility and disorder is desirable.
  • The more a company knows and cares about its core business area, the less likely employees will be to agree on a common definition of it.
  • If information is power and money, people will not share it easily.
  • The willingness of individuals to use a specified information format is directly proportional to how much they have participated in defining it, or trust other who did.
  • To make the most of electronic communications, employees must first learn to communicate face to face.
  • Since people are important sources and integrators of information, any maps of information should include people.
  • There is no such thing as information overload; if information is really useful our appetite for it is insatiable.

Original Article can be found here.

Four Questions to Ask yourself when developing a Brand

  1. What does our brand stand for?
  2. Based on the product selection and website, what would people think our brand stands for?
  3. Does our brand serve a need?
  4. Could a shift in brand serve this product in a better way?

It may be time to audit your website or communication in general. Often these audits are done by third-party consultants who don’t have the history or office politics and can ask Why? without offending colleagues. If you need help with an audit, contact me today and lets work together.

The full article with background details for each of the questions can be found here

User Experience and the ease of usability

The definition of usability is sometimes reduced to “easy to use,” but this over-simplifies the problem and provides little guidance for the user interface designer. A more precise definition can be used to understand user requirements, formulate usability goals and decide on the best techniques for usability evaluations. An understanding of the five characteristics of usability – effective, efficient, engaging, error tolerant, easy to learn – helps guide the user-centered design tasks to the goal of usable products.

  • Usability means thinking about how and why people use a product. 
    Good technical writing, like good interaction design, focuses on user’s goals. The first step in creating a usable product is understanding those goals in the context of the user’s environment, task or work flow, and letting these needs inform the design.
  • Usability means evaluation.
    Usability relies on user-feedback through evaluation rather than simply trusting the experience and expertise of the designer. Unlike conventional software acceptance testing, usability evaluation involves watching real people use a product (or prototype), and using what is learned to improve the product.
  • Usability means more than just “ease of use”
    The 5 Es – efficient, effective, engaging, error tolerant and easy to learn – describe the multi-faceted characteristics of usability. Interfaces are evaluated against the combination of these characteristics which best describe the user’s requirements for success and satisfaction.
  • Usability means user-centered design
    Users are satisfied when an interface is user-centered – when their goals, mental models, tasks and requirements are all met. The combination of analysis, design and evaluation all approached starting from the user’s point of view creates usable products.

Read the well written, in-depth post by Whitney Quesenbery on her site here: http://www.wqusability.com/articles/more-than-ease-of-use.html

Feeling Machines that Think

Over the past several weeks I’ve been performing my research on developing empathy and humility, the foundation of servant leadership, in Afrillennials. I found in the past session an interesting “aha moment” popped up in our discussion and it brought me back to this quote:

According to neuroscientist Antonio Damasio our emotions are the deciding factor for 95 percent of our decisions. So rather than “thinking and acting,” we generally “feel and act.” Part of Damasio’s research involved brain-damaged people who were unable to experience emotions. Even though they could list the pros and cons of any given choice, they were unable to make decisions.

Damasio’s work led him to believe that human beings aren’t “thinking machines that feel,” but rather “feeling machines that think.”

The 95% of our decisions are based on emotions is a staggering thought. I’ve found in my own life, as the development of this research has been taking place, that I desire to make more decisions based on fact vs. emotions. The self-awareness required for this takes deep effort, introspection, and humility with others to allow them to speak into your life, calling out the areas where your thoughts may not be in alignment with your values.

A Change Management secret to tremendous feedback

As I look deeper into Change Management and Organizational Leadership the topic of feedback increasingly comes to the forefront. In a conversation with a fellow Change Manager here in Cape Town our discussion centered around getting feedback which he said is the biggest hurdle he faces in his projects. His practice has begun focusing on helping the employees elicit open, anonymous feedback from their co-workers. Their tool focuses on two questions: What can employee A do better? and What is employee A doing better than anyone else?

The explanation of their Change Management process made me think of this article explaining how Steve Jobs would elicit the most effective feedback.

Tell me what’s not working.

The questions were not directed only toward the exco team, but various people in the organization: Tell me what’s not working here. Then conversely, he would ask someone else: Tell me what is working here.

Ultimately, great leaders, Level 5 leaders as Jim Collins (Good To Great) calls them, are individuals who trust those they’ve hired. By asking questions in this manner, it allows those individuals to speak up and be heard.

Read the article here

Leader Empathy: The Key to Effective Relationships

Leader Empathy: The Key to Effective Relationships

Empathy is one of the Social Awareness competencies in the twelve-competency Leadership Competency Model developed by Daniel Goleman and Richard Boyatzis. Empirically linked to leadership performance, Empathy is present in leaders with an understanding of the motivations of others, and the ability to relate to differing perspectives.

Strength in this competency is also demonstrated by leaders who:

  • Listen attentively
  • Are able to understand unspoken or confused attempts at communication
  • Engage in actions indicating a sincere interest in others
  • Have an increased capacity to respect diversity

How to communicate with those who disagree with you

Fast Company just posted an interesting article that discusses a study on why communicating in person versus a written text is worth the effort. According to a 2016 survey of more than 2,000 US adults (paywall) where managers were asked what they found most difficult about communicating with employees a full 69% of respondents said they found “communicating in general” to be the hardest part about communicating with employees.

Clearly, there is a breakdown.

In Schroeder’s study of almost 300 people, participants were asked to watch, listen, and read arguments about subjects they agreed or disagreed with, including abortion, music, and war. They were asked to judge the character of the communicator and the quality or veracity of the argument. Schroeder’s team found that the participants who watched or listened to the communicator were less dismissive of their claims than when they read that communicator’s same argument.

Schroeder’s research also found the participants who listened to or watched the communicators talk were also less likely to dehumanize them–a phenomenon where we subconsciously belittle or demonize the cognitive capabilities and moral attributes of people who hold views other than our own.

This article has some great advice and is where the 69% statistic came from.

“Rather than endless lunches or dinners or boondoggles, one of the best ways to build a good relationship with your employees is to make sure they feel heard,” wrote HR guru Kim Scott in Harvard Business Review. Scott suggests regular one-on-one check-ins where the employee sets the agenda, and that managers give regular feedback—both positive and critical.

My take is that business is going so rapidly, individuals don’t stop and have a cup of coffee together often enough. If they do, it’s rushed, not relaxed, and no relationship is actually built.

In Cape Town, I’ve worked with a man who told me of his experiences working in offices downtown before the age of computers. “People had time to think” he said. I’ll never forget that statement, because it doesn’t seem the speed of business allows us that luxury anymore.

In Seoul, while consulting over a two-weeek period, I was privileged to experience a “3 o’clock conversation time” – I don’t know what it was called in Korean and it may have just been this particular organization’s practice. Every day, at three in the afternoon, for thirty minutes the executive leadership would step into the CEO’s office, take off their shoes and have coffee and pastries. The conversation was very open, discussing wives or children, vacations, work issues, jokes, etc. It was a team who enjoyed being around each other and felt like they all had the same goal they were working toward. As the statement above emphasizes: the executive leadership felt heard by their leader. They then turned around and did the same for the staff whom they were responsible for.

Are you having difficulty leading? Try slowing down, being friendly, and listening with no agenda.

What makes employees exceptional?

A recent international study surveyed more than 500 business leaders and asked them what sets great employees apart. The researchers wanted to know why some people are more successful than others at work, and the answers were surprising; leaders chose “personality” as the leading reason.

Notably, 78% of leaders said personality sets great employees apart, more than cultural fit (53%) and even an employee’s skills (39%).

Read the full article by Dr. Travis Bradberry on LinkedIn