Seeing the Invisible

Seeing the Invisible

GUEST POST from Mike Shipulski

It’s relatively straightforward to tell the difference between activities that are done well and those that are done poorly. Usually sub-par activities generate visual signals to warn us of their misbehavior. A bill isn’t paid, a legal document isn’t signed or the wrong parts are put in the box. Though the specifics vary with context, the problem child causes the work product to fall off the plate and make a mess on the floor.

We have tools to diagnose the fundamental behind the symptom. We can get to root cause. We know why the plate was dropped. We know how to define the corrective action and implement the control mechanism so it doesn’t happen again. We patch up the process and we’re up and running in no time. This works well when there’s a well-defined in place, when process is asked to do what it did last time, when the inputs are the same as last time and when the outputs are measured like they were last time.

However, this linear thinking works terribly when the context changes. When the old processes are asked to do new work, the work hits the floor like last time, but the reason it hits the floor is fundamentally different. This time, it’s not that an activity was done poorly. Rather, this time there’s something missing altogether. And this time our linear-thinker toolbox won’t cut it. Sure, we’ll try with all our Six Sigma might, but we won’t get to root cause. Six Sigma, lean and best practices can fix what’s broken, but none of them can see what isn’t there.

When the context changes radically, the work changes radically. New-to-company activities are required to get the new work done. New-to-industry tools are needed to create new value. And, sometimes, new-to-world thinking is the only thing that will do. The trick isn’t to define the new activity, choose the right new tool or come up with the new thinking. The trick is to recognize there’s something missing, to recognize there’s something not there, to recognize there’s a need for something new. Whether it’s an activity, a tool or new thinking, we’ve got to learn to see what’s not there.

Now the difficult part – how to recognize there’s something missing. You may think the challenging part is to figure out what’s needed to fill the void, but it isn’t. You can’t fill a hole until you see it as a hole. And once everyone agrees there’s a hole, it’s pretty easy to buy the shovels, truck in some dirt and get after it. But if don’t expect holes, you won’t see them. Sure, you’ll break your ankle, but you won’t see the hole for what it is.

If the work is new, look for what’s missing. If the problem is new, watch out for holes. If the customer is new, there will be holes. If the solution is new, there will be more holes.

When the work is new, you will twist your ankle. And when you do, grab the shovels and start to put in place what isn’t there.

Image credit: Pixabay

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Bringing a Hospitality Mentality to Customer Experience

Bringing a Hospitality Mentality to Customer Experience

GUEST POST from Shep Hyken

Want to know the secret to creating an amazing customer experience? It’s simpler than you might think. I recently interviewed Michael Cecchi-Azzolina on my podcast, Amazing Business Radio, and his answer was refreshingly straightforward: “Be kind. Just be nice.”

Cecchi is the owner of Cecchi’s restaurant in New York City and author of Your Table is Ready: Tales of a New York City Maître D’. With nearly 40 years in the hospitality industry, he’s learned that kindness trumps everything else.

It’s Called “Hospitality” for a Reason

Cecchi noticed something interesting. Customers weren’t just thanking him for good service—they were specifically thanking him for his “hospitality.” This shift represents something important. People don’t just want service. They want to feel welcomed, valued and cared for.

Cecchi said, “This is new. I’ve been doing this for almost forty years, and I’ve only been hearing this the past year and a half or so.” The trend in what customers want and expect—for all industries, not just hospitality—is an experience that includes employees who are friendly, knowledgeable and helpful. That’s hospitality.

The Food or Service Question

Years ago, Cecchi interviewed for a job with legendary restaurateur Danny Meyer, who asked him a question that would stick with him for decades: “What’s more important, food or service?” After years of working with world-class chefs, Cecchi’s answer is clear: “It always came down to the service.”

His point is, you could have the best product in the world, but if your service is poor, customers won’t come back. As Cecchi put it, “If you have a surly waiter, a maître d’ who’s rude, a bartender who doesn’t acknowledge you … chances are you’re not coming back.”

My annual customer service and experience research backs this up. Every year, my survey finds that rudeness and apathy are the top reasons customers leave businesses. Sure, the product is important, but kindness — the opposite of rudeness and apathy — is what keeps them coming back.

We Don’t Sell Products—We Sell Experiences

One of my favorite quotes from our conversation was when Cecchi said, “We don’t sell food. We sell an experience. The experience begins when our front door opens. If the lights are perfect and the music is right and you’re getting this wonderful smile from the person at the door … you’re winning.” This is true for every business. You aren’t selling insurance, software or consulting services. You’re selling an experience wrapped around those things.

What does this look like in your business? What’s your equivalent of perfect lighting and the right music? It might be as simple as answering the phone with a smile in your voice or remembering a customer’s name.

The Broadway Principle

Cecchi’s first job out of high school was working at Playwrights Horizons. They had no money to pay him, but he wanted the experience. His boss knew Cecchi needed money to live, and it would be a short time before Cecchi would have to move on, so the boss got him a job at the restaurant across the street.

Cecchi compared restaurant service to Broadway theater: “This is a theater. We’ve got a script. We’ve got a set … those actors who were crushing it, they might have had a breakup that day or someone died in the family. You must put that aside.”

I call this the Broadway Principle. Legendary actor Richard Burton used to tell himself before performances (paraphrased): “Tonight, I want to be so good that I cheat the audience that was here last night.”

What if everyone, no matter their business or industry, approached customer interactions with that level of commitment?

Hiring for Heart, Not Just Experience

Cecchi’s hiring philosophy is not focused on the experience that employees have in the restaurant industry. Although that helps, he’s looking for people who genuinely love interacting with others. “I don’t hire people because of their resume,” he explained. “It takes a really special person to understand what real hospitality is.”

In 2011, I interviewed Jim Bush, former SVP of Worldwide Customer Experience at American Express. His hiring philosophy was similar. I’ll never forget his advice about hiring. Bush explained that given the choice between someone with 10 years of experience in a contact center or someone who worked at a restaurant, he’d hire the restaurant worker every time because they understood how to take care of people. In other words, they understand the hospitality mentality.

It’s All About Emotion

At its core, business is emotional. As Cecchi put it, “Restaurants are an emotional experience. People come in because they’re on a date, or celebrating a birthday or an anniversary.” Again, this isn’t just true for restaurants. Whether you’re buying a car, choosing a healthcare provider or selecting a software vendor, emotions drive decisions.

Cecchi shared a story that perfectly captures the power of hospitality: “I had six women at one table who’d been in the restaurant about 12 times. I jokingly said, ‘Thank God there are no other restaurants in New York City.’ And one of them looked at me and said, ‘Michael, there’s no restaurant in New York City that treats us the way you do here.’”

That story summarizes what we should all aim for—to be the one business that treats customers like no one else does. And it starts with something as simple as being kind, the core of the hospitality mentality.

Image Credits: Unsplash, Shep Hyken

This article originally appeared on Forbes.com

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Is Your Innovation Strategy on Track?

Is Your Innovation Strategy on Track?

GUEST POST from Stefan Lindegaard

A solid innovation strategy is key to setting your organization up for long-term success. But how do you know if you’re on the right path? Here are a few signs that your innovation strategy is sound – and some KPI/metrics tips to guide you along the way.

1. Alignment with Corporate Strategy

A strong innovation strategy doesn’t stand alone—it’s integrated with the overall corporate strategy. While innovation teams often lean more visionary, the core business balances daily execution with future growth. Finding the “sweet spot” between these perspectives helps shape an innovation strategy that is bold yet achievable.

KPI/metrics: Strategic alignment score. Are innovation initiatives aligned with overall business goals and timelines? Does the strategy push far enough to create the future, but close enough to today’s realities?

2. Clarity on Innovation Type

It’s critical to know what type of innovation your organization is pursuing. Incremental innovation? Breakthrough or radical? Or perhaps you’re aiming for “in-between” innovation – meaningful advancement without the high stakes of disruptive change.

KPI/metrics: Track innovation project distribution across types (incremental, in-between, breakthrough). Are you focusing on the sweet spot for your capabilities?

3. Understanding of Ecosystem Dynamics

In-between innovation, where companies push beyond small improvements but not into complete market disruption, often benefits from ecosystem collaboration. This means tapping into external assets and building alliances that complement internal capabilities.

KPI/metrics: Number and quality of ecosystem partnerships. How many productive partnerships are helping you access needed assets or knowledge?

Six Innovation Models by BCG

4. Balance Between Vision and Reality

The innovation team may lean toward bold, future-shaping ideas, while the core business focuses on today’s realities. A sound strategy balances both perspectives – pushing boundaries while staying feasible within current business structures.

KPI/metrics: Time-to-market for innovation projects. Are projects moving efficiently from concept to market, indicating a practical balance between vision and execution?

5. Talent and Skills Alignment

A clear innovation strategy should inform talent requirements. Are the right skills and roles in place to support the type of innovation you’re aiming for?

KPI/metrics: Skills gap analysis for innovation-related roles. Does your team have the capabilities needed to bring your strategy to life?

6. Adaptability and Resilience

Innovation doesn’t follow a straight line. A sound strategy allows for flexibility and quick pivots based on market feedback, technology shifts, and emerging opportunities.

KPI/metrics: Percentage of innovation projects adapted or redirected based on feedback. How adaptable is your team in responding to change?

Your innovation strategy should guide you in defining what’s possible, aligning with your corporate strategy, and fostering a collaborative yet grounded approach. The right KPIs help you measure progress and ensure alignment with your strategic vision.

I hope this shorter post can help spur some reflection and raise some guiding questions for your efforts and initiatives.

Image Credit: Pexels

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This AI Creativity Trap is Gutting Your Growth

This AI Creativity Trap is Gutting Your Growth

GUEST POST from Robyn Bolton

“We have to do more with less” has become an inescapable mantra, and goodness, are you trying.  You’ve slashed projects and budgets, “right-sized” teams, and tried any technology that promised efficiency and a free trial.  Now, all that’s left is to replace the people you still have with AI creativity tools.  Welcome to the era of the AI Innovation Team.

It sounds like a great idea.  Now, everyone can be an innovator with access to an LLM.  Heck, even innovation firms are “outsourcing” their traditional work to AI, promising the same radical results with less time and for far less money.

It sounds almost too good to be true.

Because it is too good to be true.

AI is eliminating the very brain processes that produce breakthrough innovations.

This isn’t hyperbole, and it’s not just one study.

MIT researchers split 54 people into three groups (ChatGPT users, search engine users, and no online/AI tools using ChatGPT) and asked them to write a series of essays.  Using EEG brain monitoring, they found that the brain connectivity in networks crucial for creativity and analogous thinking dropped by 55%.

Even worse? When people stopped using AI, their brains stayed stuck in this diminished state.

University of Arkansas researchers tested AI against 3,562 humans on a series of four challenges involving finding new uses for everyday objects, like a brick or paperclip.   While AI scored slightly higher on standard tests, when researchers introduced a new context, constraint, or modification to the object, AI’s performance “collapsed.” Humans stayed strong.

Why? AI relies on pattern matching and is unable to transfer its “creativity” to unexpected scenarios. Humans use analogical reasoning so are able to flex quickly and adapt.

University of Strasbourg researchers analyzed 15,000 studies of COVID-19 infections and found that teams that relied heavily on AI experts produced research that got fewer citations and less media attention. However, papers that drew from diverse knowledge sources across multiple fields became widely cited and influential.

The lesson? Breakthroughs require cross-domain thinking, which is precisely what diverse human teams provide, and, according to the MIT study, AI is unable to produce.

How to optimize for efficiency AND impact (and beat your competition)

While this seems like bad news if you’ve already cut your innovation team, the silver lining is that your competition is probably making the same mistake.

Now that you know better, you can do better, and that creates a massive opportunity.

Use AI for what it does well:

  • Data analysis and synthesis
  • Rapid testing and iteration to refine an advanced prototype
  • Process optimization

Use humans for what we do well:

  • Make meaningful connections across unrelated domains
  • Recognize when discoveries from one field apply to another
  • Generate the “aha moments” that redefine industries

Three Questions to Ask This Week

  1. Where did your most recent breakthroughs come from? How many came from connecting insights across different domains? If most of your innovations require analogical leaps, cutting creative teams could kill your pipeline.
  2. How are teams currently using AI tools? Are they using AI for data synthesis and rapid iteration? Good. Are they replacing human ideation entirely? Problem.
  3. How can you see it to believe it? Run a simple experiment: Give two teams an hour to solve a breakthrough challenge. Have one solve it with AI assistance and one without.  Which solution is more surprising and potentially breakthrough?

The Hidden Competitive Advantage

As AI commoditizes pattern recognition, human analogical thinking and creativity become a competitive advantage.

The companies that figure out the right balance will eat everyone else’s lunch.

Image credit: Gemini

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Three Strategies for Overcoming Change Resistance

Three Strategies for Overcoming Change Resistance

GUEST POST from Greg Satell

Max Planck’s work in physics changed the way we were able to see the universe. Still, even he complained that “A new scientific truth does not triumph by convincing its opponents and making them see the light, but rather because its opponents eventually die, and a new generation grows up that is familiar with it.”

For most transformational efforts we need to pursue, we simply don’t have that kind of time. To drive significant change we have to overcome staunch resistance. Unfortunately, most change management strategies assume that opposition can be overcome through communication efforts that are designed to persuade.

This assumes that resistance always has a rational basis and clearly that’s not true. We all develop emotional attachments to ideas. When we feel those are threatened, it offends our dignity, identity and sense of self. If we are going to overcome our most fervent opponents we don’t need a better argument, we need a strategy. Here are three approaches that work:

Strategy 1: Designate An Internal Red Team

Resistance is never monolithic. While some people have irrational attachments based on their sense of identity and dignity, others are merely skeptical. One key difference between these two groups is that the irrational resistors rarely voice their opposition, but try to quietly sabotage change. The rational skeptics, on the other hand, are much more eager to engage.

While these are different groups, they often interact with each other behind the scenes. In many cases, it is the active, irrational opposition that is fueling the skeptics’ doubts. One useful strategy for dealing with this dynamic is to co-opt the opposition by setting up an internal red team to channel skepticism in a constructive way.

Red-teaming is a process in which an adversarial team is set up to poke holes in an operational or strategic plan. For example, red teams are used in airports and computer systems to see if they can find weaknesses in security. The military uses red teams to test battle plans. Perhaps most famously, a red team was used to help determine whether the conclusions that led to the raid on Osama bin Laden’s hideout were valid or if there was some other explanation.

Recruiting skeptics to be an internal red team provides two benefits. First, they can alert you to actual problems with your ideas, which you can then fix. Second, they not only voice their own objections, but also bring those of the irrational opposition out into the open (remember, irrational resisters rarely speak out.)

What’s key here is to make the distinction between rational skeptics and the irrational saboteurs. Engage with skeptics, leave the saboteurs to themselves.

Strategy 2: Don’t Engage And Quietly Gain Traction

Have you ever had this happen?: You’re in a meeting where things are moving slowly towards a consensus. Issues are discussed, objections raised and solutions devised. Toward the end of the meeting, just as things are shifting gears to next steps, somebody who had hardly said a word the whole time all of a sudden throws a hissy fit in the middle of the conference room and completely discredits themself.

There’s a reason why this happens. Remember saboteurs are not acting rationally. They have emotional attachments that they often can’t articulate, which is why they rarely give voice to their objections, but rather look for more discreet opportunities to derail the process. When they see things moving forward, they panic.

This doesn’t happen just in conference rooms. Those who are trying to sabotage change prefer to lurk in the background and hope they can quietly derail it. But when they see genuine progress being made, they will likely lash out, overreach and inadvertently further your cause.

This behavior is incredibly consistent. In fact, whenever I’m speaking to a group of transformation and change professionals and I describe this phenomenon to them, I always get people coming up to me afterwards. “I didn’t know that was a normal thing, I thought it was just something crazy that happened in our case!”

It’s important to resist the urge to respond to every attack. You don’t need to waste precious time and energy engaging with those who want to derail your initiative, which is more likely to frustrate and exhaust you than anything else. It’s much better to focus on empowering those who support change. Non-engagement can be a viable way to deal with opposition.

Strategy 3: Design A Dilemma Action

I once had a six-month assignment to restructure the sales and marketing operations of a troubled media company and the Sales Director was a real stumbling block. She never overtly objected, but would rather nod her head and then quietly sabotage progress. For example, she promised to hand over the clients she worked directly with to her staff, but never seemed to get around to it.

It was obvious that she intended to slow-walk everything until the six months were over and then return everything back to the way it was. As a longtime senior employee, she had considerable political capital within the organization and, because she was never directly insubordinate, creating a direct confrontation with her would be risky and unwise.

So rather than create a conflict, I designed a dilemma. I arranged with the CEO of a media buying agency for one of the salespeople to meet with a senior buyer and take over the account. The Sales Director had two choices. She could either let the meeting go ahead and lose her grip on the department or try to derail the meeting. She chose the latter and was fired for cause. Once she was gone, her mismanagement became obvious and sales shot up.

Dilemma actions have been around for at least a century. One early example was Alice Paul’s Silent Sentinels who picketed the Wilson White House with his own quotes in 1917. More recently, the tactic has been the subject of increasing academic interest. What’s becoming clear is that these actions share clear design principles that can be replicated in almost any context.

Key to the success of a dilemma action is that it is seen as a constructive act rooted in a shared value. In the case of the Sales Director, she had agreed to give up her accounts and setting up the meeting was aligned with that agreement. That’s what created the dilemma. She had to choose between violating the shared value or giving up her resistance.

How Change Really Happens

One of the biggest misconceptions about change is that it is an exercise in persuasion. Yet anyone who has ever been married or had kids knows how hard it can be to convince even a single person of something they don’t want to be convinced about. Seeking to persuade hundreds or thousands to change what they think or how they act is a tall order indeed.

The truth is that radical, transformational change is achieved when not when those who oppose it are convinced, but when they discredit themselves. It was the brutality of Bull Connor’s tactics in Birmingham that paved the way for the Civil Rights Act in 1964. It was Russia’s poisoning of Viktor Yushchenko in 2004 that set Ukraine on a different path. The passage of Proposition 8 in California created such controversy that it actually furthered the cause of same-sex marriage.

We find the same dynamic in our work with organizational transformations. Whenever you set out to make a significant impact, there will always be people who will hate the idea and seek to undermine it in ways that are dishonest, underhanded and deceptive. Once you are able to internalize that you are ready to move forward.

Through sound strategies, you can learn to leverage opposition to further your change initiative. You can co-opt those who are rationally skeptical to find flaws in your idea that can be fixed. For those who are adamantly and irrationally opposed to an initiative, there are proven strategies that help lead them to discredit themselves.

The status quo always has inertia on its side and never yields its power gracefully. The difference between successful revolutionaries and mere dreamers is that those who succeed anticipate resistance and build a plan to overcome it.

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

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Why Context Engineering is the Next Frontier in AI

Why Context Engineering is the Next Frontier in AI

by Braden Kelley and Art Inteligencia

Observing the rapid evolution of artificial intelligence, one thing has become abundantly clear: while raw processing power and sophisticated algorithms are crucial, the true key to unlocking AI’s transformative potential lies in its ability to understand and leverage context. We’ve seen remarkable advancements in generative AI and machine learning, but these technologies often stumble when faced with the nuances of real-world situations. This is why I believe context engineering – the discipline of explicitly designing and managing the contextual information available to AI systems – is not just an optimization, but the next fundamental frontier in AI innovation.

Think about human intelligence. Our ability to understand language, make decisions, and solve problems is deeply rooted in our understanding of context. A single word can have multiple meanings depending on the sentence it’s used in. A request can be interpreted differently based on the relationship between the people involved or the situation at hand. For AI to truly augment human capabilities and integrate seamlessly into our lives, it needs a similar level of contextual awareness. Current AI models often operate on relatively narrow inputs, lacking the broader understanding of user intent, environmental factors, and historical interactions that humans take for granted. Context engineering aims to bridge this gap, moving AI from being a powerful but often brittle tool to a truly intelligent and adaptable partner.

In the realm of artificial intelligence, context engineering is the strategic and human-centered practice of providing an AI system with the relevant background information it needs to understand a query or situation accurately. It goes beyond simple prompt design by actively building and managing the comprehensive context that surrounds an interaction. This includes integrating historical data, user profiles, real-time environmental factors, and external knowledge sources, allowing the AI to move from a narrow, transactional understanding to a more holistic, human-like awareness. By engineering this context, we enable AI to produce more accurate, personalized, and genuinely useful responses, bridging the gap between a machine’s logic and the nuanced complexity of human communication and problem-solving.

The field of context engineering encompasses a range of techniques and strategies focused on providing AI systems with relevant and actionable context. This includes:

  • Prompt Engineering: Crafting detailed and context-rich prompts that guide AI models towards desired outputs.
  • Memory Management: Implementing mechanisms for AI to remember past interactions and use that history to inform current responses.
  • External Knowledge Integration: Connecting AI systems to external databases, APIs, and real-time data streams to provide up-to-date and relevant information.
  • User Profiling and Personalization: Leveraging data about individual users to tailor AI responses to their specific needs and preferences.
  • Situational Awareness: Incorporating real-world contextual cues, such as location, time of day, and user activity, to make AI more responsive to the current situation.

A Human-Centered Blueprint for Implementation

Implementing context engineering is not a one-time technical fix; it is a continuous, human-centered practice that must be embedded into your innovation lifecycle. To move beyond a static, one-size-fits-all model and create truly intelligent, context-aware AI, consider this blueprint for action:

  • Step 1: Start with the Human Context. Before you even think about data streams or algorithms, you must first deeply understand the human being you are serving. Conduct ethnographic research, user interviews, and journey mapping to identify what context is truly relevant to your users. What are their goals? What unspoken needs do they have? What external factors influence their decisions? The most valuable context often isn’t in a database—it’s in the real-world experiences and emotional states of your users.
  • Step 2: Map the Contextual Landscape. Once you understand the human context, you can begin to identify and integrate the necessary data. This involves creating a “contextual map” that connects the human need to the available data sources. For a customer service AI, this map would link a customer’s inquiry to their purchase history, recent support tickets, and even their browsing behavior on your website. For a medical AI, the map would link a patient’s symptoms to their genetic data, environmental exposure, and family medical history. This mapping process ensures that the AI’s inputs are directly tied to what matters most to the user.
  • Step 3: Build a Dynamic Feedback Loop. The context of a situation is constantly changing. A great context-aware AI is not a static system but a learning one. Implement a continuous feedback loop where human users can correct the AI’s understanding, provide additional information, and refine its responses. This “human-in-the-loop” approach is vital for ethical and accurate AI. It allows the system to learn from its mistakes and adapt to new, unforeseen contexts, ensuring its relevance and reliability over time.
  • Step 4: Prioritize Privacy and Ethical Guardrails. The more context you provide to an AI, the more critical it becomes to manage that information responsibly. From the outset, you must design for privacy, collecting only the data you absolutely need and ensuring it is stored and used in a secure and transparent manner. Establish clear ethical guardrails for how the AI uses and interprets contextual information, particularly for sensitive data. This is not just a regulatory requirement; it is a fundamental aspect of building trust with your users and ensuring that your AI serves humanity, rather than exploiting it.

By following these best practices, you can move beyond simple, reactive AI to a proactive, human-centered intelligence that understands the world not just as a collection of data points, but as a rich tapestry of interconnected context. This is the work that will define the next generation of AI and, in doing so, will fundamentally change how technology serves humanity.

Case Study 1: Improving Customer Service with Context-Aware AI Assistants

The Challenge: Generic and Frustrating Customer Service Chatbots

Many companies have implemented AI-powered chatbots to handle customer inquiries. However, these chatbots often struggle with complex or nuanced issues, leading to frustrating experiences for customers who have to repeat information or are given irrelevant answers. The lack of contextual awareness is a major limitation.

Context Engineering in Action:

A telecommunications company sought to improve its customer service chatbot by implementing robust context engineering. They integrated the chatbot with their CRM system, allowing it to access the customer’s purchase history, past interactions, and current account status. They also implemented memory management so the chatbot could retain information shared earlier in the conversation. Furthermore, they used prompt engineering to guide the chatbot to ask clarifying questions and to tailor its responses based on the specific product or service the customer was inquiring about. For example, if a customer asked about a billing issue, the chatbot could access their latest bill and provide specific details, rather than generic troubleshooting steps. It could also remember if the customer had contacted support recently for a related issue and take that into account.

The Impact:

The context-aware chatbot significantly improved customer satisfaction scores and reduced the number of inquiries that had to be escalated to human agents. Customers felt more understood and received more relevant and efficient support. The company also saw a decrease in customer churn. This case study highlights how context engineering can transform a basic AI tool into a valuable and helpful resource by enabling it to understand the customer’s individual situation and history.

Key Insight: By providing AI customer service assistants with access to relevant customer data and interaction history, companies can significantly enhance the quality and efficiency of support, leading to increased customer satisfaction and loyalty.

Case Study 2: Enhancing Medical Diagnosis with Contextual Patient Information

The Challenge: Over-reliance on Isolated Symptoms in AI Diagnostic Tools

AI is increasingly being used to assist medical professionals in diagnosing diseases. However, early AI diagnostic tools often focused primarily on analyzing individual symptoms in isolation, potentially missing crucial contextual information such as the patient’s medical history, lifestyle, environmental factors, and even subtle cues from their recent health records.

Context Engineering in Action:

A research hospital in the Pacific Northwest developed an AI-powered diagnostic tool for a specific type of rare disease. Recognizing the importance of context, they engineered the AI to integrate a wide range of patient data beyond just the presenting symptoms. This included the patient’s complete medical history (past illnesses, medications, allergies), family medical history, lifestyle information (diet, exercise, smoking habits), recent lab results, and even notes from previous doctor’s visits. The AI was also connected to relevant medical literature to understand the broader context of the disease and potential co-morbidities. By providing the AI with this rich contextual information, the researchers aimed to improve the accuracy and speed of diagnosis, especially in complex cases where isolated symptoms might be misleading.

The Impact:

The context-aware AI diagnostic tool demonstrated a significantly higher accuracy rate in identifying the rare disease compared to traditional methods and earlier AI models that lacked comprehensive contextual input. It was also able to flag potential risks and complications that might have been overlooked otherwise. This case study underscores the critical role of context engineering in high-stakes applications like medical diagnosis, where a holistic understanding of the patient’s situation can lead to more timely and effective treatments.

Key Insight: Context engineering, by enabling a holistic view of a patient’s health and history, is crucial for improving the accuracy and reliability of AI in critical fields like medical diagnosis.

The Future of AI is Contextual

The future of AI is not about building bigger models; it’s about building smarter ones. And a smarter AI is one that can understand and leverage the richness of context, just as humans do. From a human-centered perspective, context engineering is the practice that makes AI more useful, more reliable, and more deeply integrated into our lives in a way that truly helps us. By moving beyond simple prompts and isolated data points, we can create AI systems that are not just powerful tools, but truly intelligent and invaluable partners. The work of bridging the gap between isolated data and meaningful context is where the next great wave of AI innovation will emerge, and it is a task that will demand our full attention.

Image credit: Pexels

Content Authenticity Statement: The topic area and the key elements to focus on were decisions made by Braden Kelley, with help from Google Gemini to shape the article and create the illustrative case studies.

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The Future is Rotary

Human-Centered Innovation in Rotating Detonation Engines

The Future is Rotary - Human-Centered Innovation in Rotating Detonation Engine

GUEST POST from Art Inteligencia

For decades, the pursuit of more efficient and sustainable propulsion systems has driven innovation in aerospace and beyond. Among the most promising advancements on the horizon is the Rotating Detonation Engine (RDE). This technology, which harnesses supersonic combustion waves traveling in a circular channel, offers the potential for significant leaps in fuel efficiency and reduced emissions compared to traditional combustion methods. However, the true impact of RDEs will not solely be defined by their technical prowess, but by a human-centered approach to their development and integration.

A Paradigm Shift for a Better Future

Human-centered change innovation focuses on understanding and addressing the needs and aspirations of people affected by technological advancements. In the context of RDEs, this means considering not only the engineers and scientists developing the technology but also the pilots, passengers, communities living near airports, and the planet as a whole. The potential benefits are immense:

  • Enhanced Fuel Efficiency: RDEs promise a significant reduction in fuel consumption, leading to lower operating costs and a smaller carbon footprint for air travel and other applications.
  • Reduced Emissions: More efficient combustion can translate to lower emissions of harmful pollutants, contributing to cleaner air and a healthier environment.
  • Increased Performance: The unique properties of detonation combustion could lead to more powerful and lighter engines, opening up new possibilities for aircraft design and space travel.
  • Economic Growth: The development and adoption of RDE technology will create new jobs in research, manufacturing, and maintenance, fostering economic growth.

Navigating the Winds of Change: Key Areas for Innovation

Realizing the full potential of RDEs requires a concerted effort across various domains, guided by a human-centered perspective:

  • Materials Science: Developing materials that can withstand the extreme temperatures and pressures of detonation combustion is crucial. This requires innovative research and collaboration between material scientists and engineers.
  • Engine Design and Control Systems: Creating robust and reliable RDE designs, along with sophisticated control systems to manage the complex detonation process, is essential for safe and efficient operation. Human factors engineering will play a vital role in designing intuitive and user-friendly control interfaces.
  • Manufacturing Processes: Scaling up the production of RDE components will require innovative manufacturing techniques that are both cost-effective and environmentally sustainable.
  • Infrastructure Development: The widespread adoption of RDEs may necessitate changes in fuel production, storage, and delivery infrastructure. Planning for these changes with community needs and environmental impact in mind is critical.
  • Education and Training: A new generation of engineers, technicians, and pilots will need to be trained in the principles and operation of RDE technology. Educational programs must adapt to incorporate this emerging field.
  • Regulatory Frameworks: Governments and regulatory bodies will need to develop new standards and certifications to ensure the safe and responsible deployment of RDE-powered systems. Engaging stakeholders in the development of these frameworks is crucial.

Companies and Startups to Watch

The landscape of RDE development is dynamic, with several established aerospace companies and innovative startups making significant strides. Keep an eye on organizations like GE Aerospace and Rolls-Royce which have publicly acknowledged their research into detonation technologies. Emerging startups such as Venus Aerospace are focusing on leveraging RDEs for high-speed flight, while others like Purdue University’s research labs often spin out promising technologies. These entities are pushing the boundaries of RDE technology and demonstrating potential pathways for its future application, always with an eye on the practical and societal implications of their work.

Case Studies in Human-Centered RDE Application

Case Study 1: Sustainable Air Travel

Imagine a future where short-haul flights are powered by RDEs running on sustainable aviation fuels (SAFs). The increased fuel efficiency of RDEs could significantly reduce the amount of SAF required per flight, making sustainable travel more economically viable and environmentally friendly. This benefits passengers through potentially lower ticket prices in the long run and contributes to the well-being of communities near airports by reducing noise and air pollution. Aircraft manufacturers would need to prioritize designs that minimize noise impact and ensure passenger comfort within the new performance parameters of RDE-powered aircraft. This human-centered approach ensures that the technological advancement directly addresses the need for sustainable and accessible air travel.

Case Study 2: Enhanced Emergency Response

Consider the application of compact, high-power RDEs in heavy-lift drones for disaster relief. Their potential for increased payload capacity and range could enable faster and more efficient delivery of critical supplies to disaster-stricken areas. For first responders and affected populations, this translates to quicker access to necessities like medical equipment, food, and shelter. Developing user-friendly drone control systems and ensuring the safe operation of these powerful machines in complex, real-world scenarios are key human-centered considerations. The focus here is on leveraging RDE technology to improve the speed and effectiveness of humanitarian aid, directly impacting the lives and safety of vulnerable individuals.

A Future Forged Together

The future of rotating detonation engines is not just about technological advancement; it’s about creating a future where propulsion is more efficient, sustainable, and ultimately benefits humanity. By embracing a human-centered approach to innovation, we can navigate the challenges and unlock the transformative potential of RDEs, ushering in a new era of cleaner, more powerful, and more responsible propulsion.

Disclaimer: This article speculates on the potential future applications of cutting-edge scientific research. While based on current scientific understanding, the practical realization of these concepts may vary in timeline and feasibility and are subject to ongoing research and development.

Image credit: Gemini

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Prioritization Drives Productivity

Prioritization Drives Productivity

GUEST POST from Mike Shipulski

If you haven’t noticed, the pace and complexity of our work is ever-increasing. There’s more to do and there are more interactions among the players and the tasks. And though there’s more need for thinking and planning, there’s less time to do it. And the answer from company leadership – more productivity.

With the traditional view of productivity, it’s do more with less. That works for a while and then it doesn’t. And when you can no longer do more, the only remaining way to improve productivity is to do less.

If you try to do all five things and get four done poorly, wouldn’t it be more productive if you tried to do only three things and did them well? None of the three would have to touched up or redone. And none of the three would occupy your emotional bandwidth because they were done well and they’re not coming back to bite you. And because you focused on three things, you spent only three things worth of energy. Your life force is conserved and when you get home you still have gas in the tank.

If you get three things done each day, you’ll accomplish more than anyone else in the company. Don’t think so? Three things per day is fifteen things per week. And if you work fifty weeks per year, three things per day is one hundred and fifty things per year. (I hope you don’t work fifty weeks per year, I chose this number because it makes the math cleaner.)

It’s not easy to get three things done per day. With meetings, email, texts and the various collaboration platforms, you have almost zero uninterrupted time. And with zero uninterrupted time, you get about zero things done. And if I have to choose between getting three things done or zero things done, I choose three. It’s difficult to allocate the time to get three things done, but it’s possible.

Three things may not seem like enough things, but three is enough. Here’s why. You don’t do just any three things, you do three important things. You choose what you want to get done and you get them done. The key is to decide which three things you’ll get done and which three hundred you won’t. To do this, take some time at the end of the day to define tomorrow’s three things. That way, first thing, you’ll get after the right three things. It’s productivity through prioritization. You’ve got to do fewer things to get more done.

And you can still deliver on large projects with the three-things-per-day method. For large projects, most, if not all, of the day’s three things should be directly related to the project. Remember the math – you can do fifteen things per week on a large project. And it works for long projects, too. Do one thing per week on the long project and you will accomplish fifty things over the course of the year. When was the last time you completed fifty things on a project?

And if you think three things is too few, that’s fine. If you want to do more than three things, you can. Just make sure you know which three you’ll complete before moving on to the fourth. But, remember, you want to leave work with some gas still in the tank so you can do three things when you get home.

Image credit: Pexels

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When You Don’t Have What the Customer Wants

When You Don't Have What the Customer Wants

GUEST POST from Shep Hyken

I recently responded to a question on LinkedIn: A customer is furious about an out-of-stock item. How do you turn their frustration into satisfaction?

I added a second part to that question. What if what the customer wants is something you’ve never had in stock? Some customers might still be angry that you do not have what they want. And even if they aren’t, whether the item is out of stock or you just don’t carry it, that doesn’t mean you can’t make the customer happy.

Before we go further, let me do a very quick recap of how to deal with any upset or complaining customer. This is my five-step process for handling complaints:

  1. Apologize for the problem.
  2. Acknowledge what the problem is.
  3. Discuss the resolution. (In a moment, I’ll cover this in detail.)
  4. Accept ownership. It may not be your fault, but now you own taking care of the customer.
  5. Act with urgency.

So, back to #3, the resolution. Is the item the customer wants temporarily out of stock? If so, when will it be in, and when can the customer expect to receive it? Giving customers information gives them a sense of control.

Shep Hyken Empty Shelves Cartoon

What if you’re out of the item and won’t get any more back in inventory? This is an opportunity to shine. If you can’t suggest a reasonable alternative, does a competitor have what the customer wants? Yes, I’m suggesting sending the customer to a competitor. Even if the sale goes to a competitor, the customer will realize you’re more interested in getting them what they want and need versus making a sale, which can go a long way in building trust that takes the relationship to a higher level.

One of my favorite examples comes from an Ace Hardware store. It was a very cold winter, and a customer was upset to find out the store was out of space heaters. Rather than say, “Sorry,” and send the customer away, the associate called a competitor, confirmed they had a space heater, and asked them to hold it for his customer. And who do you think the customer loved after that experience? (It’s a rhetorical question, but just in case you can’t figure it out … Ace Hardware!)

Any time a customer is unhappy or has a complaint, it’s an opportunity to resolve the problem and turn a Moment of Misery™ into a Moment of Magic®. For inventory issues, it’s an easy fix. Always think to yourself, even if you have to give up the sale to a competitor, “Is what I’m doing right now going to get the customer to come back?” When you have the customer’s best interest in mind, they will!

Image Credits: Unsplash, Shep Hyken

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Performance Reviews Don’t Have to Suck

Performance Reviews Don't Have to Suck

GUEST POST from David Burkus

Traditional annual performance reviews are confusing, dated, messy, time-consuming, and sometimes just plain inaccurate to what’s really going on in your team. As organizational psychologist Bob Sutton said, “If performance evaluations were a drug, they would not receive FDA approval. They have so many side effects, and so often fail.” According to a survey of 837 companies across the globe only about 1 in 4 companies in North America said their performance management systems were effective. And only-third of companies surveyed said their employees were evaluated fairly.

The employees and the employers have spoken.

The workplace, and work itself, has gone through some radical transformations in the past few years. It’s time performance reviews do the same. Managers don’t like evaluations because they can get confusing. It’s a hassle, and it feels like extra work on top of their existing work

Employees feel the pressure of being graded through a system that is confusing because typically it has the potential to make or break a potential raise for them. The intent of the review process—to fix problem areas, develop skills and set people up for success—breaks down into debates about what rating scales mean and the semantics of every definition.

And then there’s the time involved. On both sides of the review process, it just takes a long, long time. Adobe found that managers spent about 17 hours per employee on their performance reviews. You can interpret that amount of time two ways:

1) either managers are taking their time to thoughtfully reflect and analyze an individual’s performance and contributions over the course of a year, or 2) it’s an audacious amount of time that goes on top of regular meetings and check-ins about performance that happen naturally throughout the year.

But if you’re leaning toward the latter, trust your instincts.

How did performance reviews become so painful?

The Ranking Method, or stack ranking, or “rank and yank” was popularized by Jack Welch, the CEO of General Electric from 1981 to 2001. If you didn’t already know him as a very influential figure in corporate America, then you might recognize him as the mentor of Jack Donaguey on 30 Rock.

GE went through a massive hot streak through most of his tenure as CEO, and a lot of that success was attributed to his popularized ranking method of his employees. It worked like this:

The manager will have a list of all employees and will first choose the most valuable employee and put that name at the top. Then he or she will choose the least valuable employee and put that name at the bottom of the list. With the remaining employees, this process would be repeated.

In addition, there is a bell curve at play here. Not everyone is going to get a top rating or perfect marks, even if theoretically everyone on a team is a superstar and exceeds expectations. Under Jack Welch, in a team of 10, everyone knew only two of them would get a great rating, and at least one would get a negative rating, and possibly be…yanked.

This method or some variation of it became a norm at a lot of companies until about 2012 when more research started to come out and leaders were questioning whether the method was doing more harm than good.

Managers reported that people became obsessed with the rankings, and that it also created unhealthy, siloed competition between everyone, especially top performers. Great employees would distance themselves from other great employees out of fear they might fall in the rankings.

Great employees should be collaborating, not competing

Microsoft recently overhauled their performance review system after realizing how damaging rank-and-yank was to performance and morale. From 2000 to 2012, Microsoft’s market cap had declined from $510 billion to half of that value. Employees pointed their finger at one big reason for the nose-dive: Stack Ranking.

Turns out pitting your individual employees against one another created a culture where innovative ideas were killed, and fast. It was all about the rankings, and not about the actual work. Top performers were even ditching the company where more value was placed on the work and not just a metric.

So, Microsoft ditched the stack rankings. And a handful of other Fortune 500 companies quickly followed suit after finding the same negative effects. Motorola, Expedia, and Adobe were all yanking their rating methods in favor of more frequent, informal, focused conversations with individuals throughout the year.

Performance reviews should be an ongoing conversation

Removing the annual ritual of performance reviews and replacing them with more targeted sessions throughout the year may sound like more work, but it actually saves time. At least it did for Motorola which reported saving 50-70 percent of time spent on review processes after they ditched their once-a-year ranking method.

These check-ins don’t have to be grueling, high stakes sessions—in fact, they should be very informal. Just like the name suggests. A check-in. Schedule it sometime at the end of the month with your direct report and…check-in. The best check-ins hit on three topics: expectations, feedback, and professional growth. Don’t confuse this with just another stand-up, progress check that you usually do with your whole team.

And if you’re reading this as an individual manager, with no authority to ditch annual reviews, remember that nothing is stopping you from doing more frequent check-ins with your team. That will leave you better prepared when the annual performance review season comes up, and it will make them more willing to accept your feedback. The annual review becomes just another check-in.

Use AI, but sparingly

There is a lot of enthusiasm for AI and what it can do to make work easier. But as a leader, you should remain highly skeptical and cautious if you’re considering using AI tools in your performance review process. Pew Research came out with some recent data finding, not surprisingly, people are mixed on AI being used to monitor them in the workplace. Tracking especially.

Have AI help you figure out where to look, where to find problem areas. But AI shouldn’t be making decisions in the evaluations. Great teams are made up of humans, and when we evaluate others, we need to look them in the eye and come prepared to back up whatever we have to say, person to person. It can be an intensely vulnerable process, for both sides of the conversation. If you’re looking to bring in AI to make it easier on yourself as a manager, to take away the awkwardness you might feel when you have these conversations…you might not be cut out for being a manager.

Conclusion

The evolution from the rigid, competitive ranking systems of the past to the more flexible and supportive frameworks of today marks a significant shift in how companies view and value their employees. By focusing on development, continuous feedback, and a collaborative environment, modern businesses are paving the way for a more engaged and innovative workforce. This transformation not only enhances individual performance but also drives collective success, ensuring that the workplace remains becomes one where everyone can do their best work ever.

Image credit: Pexels

Originally published at https://davidburkus.com on August 26, 2024.

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