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Transforming Metrics into Action

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Customer Experience (CX) Leaders At Verizon, Autodesk And Prudential Are Going Beyond NPS

Transforming Metrics Into Action

GUEST POST from Shep Hyken

Is Net Promoter Score (NPS) still relevant? How can you transfer insights and data into meaningful actions? And how do you hire the right people to meet your Keep Performance Indicators (KPIs) and success metrics? Those were the questions I asked a panel of esteemed executives at a LinkedIn Live interview.

The guests were Brian Higgins, chief customer experience officer at Verizon Consumer, Elisabeth Zornes, chief customer officer at Autodesk, and Abhii Parakh, head of customer experience at Prudential. Their answers are important to any leader making decisions that impact the customer experience.

NPS Is A Foundational Metric, But Its Role Is Evolving

NPS is a powerful metric when used properly. It’s a simple question that determines whether a customer likes you enough to recommend you. From that single question, a follow-up question could seek further insight or action can be taken to improve what’s not working and elevate what is working. So, the first question I asked was about using NPS as a primary metric.

  • Parakh led off by saying, “No metric is perfect. Whether it’s NPS or something else, it’s always about a combination of tactics and measurements to get the insights on what our customers and advisors want. … We run the numbers on how much more value is being driven by our promoters or passives versus detractors, and we see a very meaningful connection between the two.” He cited three key benefits: effectively tracking long-term relationships, correlation with growth metrics and providing actionable insights.
  • Higgins said that Verizon uses NPS to benchmark in two important places. He said, “I want to look at how we are benchmarking against the competition and then against ourselves.” He looks at three areas: one, is Verizon growing or churning? The second is measuring interaction, both digital and with their reps. The third is taking a look at the overall health of the business. And in addition to measuring customer satisfaction, Verizon also uses NPS for employee satisfaction. If employees aren’t happy, the customer is going to feel it.
  • Zornes uses the measurement to strike a balance between Autodesk’s long-term relationships and direct engagement. She explained, “NPS is a great, long-lasting customer impression measurement for services, solutions and products, but we are in the age of digital first engagements, so we, of course, also measure specific moments in the digital journey along with customer effort scores.” While NPS is a foundational metric at Autodesk, they also use the Deloitte Trust ID to assess transparency, capability, reliability and care.

Bring Numbers To Life Through Employees

Competition turns companies and their products into commodities. All three companies represented on the panel have competition. Assuming the products and services do what they are supposed to do and meet their customers’ needs, what differentiates them from competitors is experience. Often, that experience is driven by employees. The next question focused on the hiring criteria that align with CX KPIs.

  • Zornes said, “The internal team and culture are really what determines the customer experience for our customers. So it’s absolutely critical we bring the right talent on board and foster it accordingly.”
  • Higgins focuses on three big areas for hiring. First, Verizon wants a wide range of experience and knowledge. Second, they want employees to act as “CX detectives,” meaning they never let small details get by. Listen and pay attention to the customer feedback and recognize the power of the details. Third, and what Higgins says is most important, is empathy. “A little voice in the back of your head says, ‘I don’t know if the customer is right, but that doesn’t matter. You’ve got to believe in them and make it right for them.’”
  • Parakh says, “It’s super important for any customer-facing role. But I would also say that in addition to customer experience roles, I think that a customer-obsessed mindset is important for any business role. It’s not just the CX team. I think customer experience is everybody’s job. So, across the company, we need to be looking for folks who have empathy for the customer, a growth mindset and familiarity with CX, as well as business knowledge.”

Rethinking How Technology And People Support CX

As the CX landscape evolves with new technology, so do the roles of employees. How do these three iconic brands rethink talent development to support the team’s ability to deliver an exceptional experience?

  • Higgins kicked off with a call back to Parakh’s comment about CX being everyone’s job. “If everyone owns CX across the company, it also means they have to get comfortable with the new sets of tools we’re putting in place. I think about AI, gen AI and agentic AI. You have to make sure employees are comfortable with these new tools that are engaging directly with customers.”
  • Parakh emphasized the importance of keeping up and changing with the times. “You can’t survive for 150 years by doing what you’ve always done. We’ve been through multiple stock market crashes and multiple pandemics, and we’ve done that by constantly reinventing, so when it comes to talent, we have to have the same mindset. Everybody in the company, starting from the top leadership, has to understand where things are going because everything is changing so fast.”
  • Zornes believes that the future is now. “AI is not coming. AI is here. And with that, there is a huge opportunity to really convert those transactions that we might have done in the past to a more smooth and self-service experience. … Some of the profiles of what jobs looked like in the past, what they look like now and what they will look like in the future continue to evolve.”

The future of customer experience lies at the intersection of meaningful metrics, empathetic teams and evolving technology. As Higgins, Zornes and Parakh shared in their answers, success comes not from any single measurement tool but from creating integrated systems that consistently detect, analyze and improve the interactions customers have with the brand. And when you add the right people who are able to demonstrate empathy, curiosity and adaptability, you have a winning combination of KPIs, technology and people that gets customers to say, “I’ll be back!”

Image Credit: Pexels

This article was originally published on Forbes.com

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When Humans and AI Innovate Together

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The Symbiotic Relationship

When Humans and AI Innovate Together

GUEST POST from Chateau G Pato

The narrative surrounding Artificial Intelligence often veers into two extremes: utopian savior or dystopian overlord. Both miss the profound truth of our current inflection point. As a human-centered change and innovation thought leader, I argue that the most impactful future of AI is not one where machines replace humans, nor one where humans merely manage machines. Instead, it is a symbiotic relationship — a partnership where the unique strengths of human creativity, empathy, and intuition merge with AI’s unparalleled speed, scale, and analytical power. This “Human-AI Teaming” is not just an operational advantage; it is the definitive engine for exponential, human-centered innovation.

The true genius of AI lies not in its ability to replicate human thought, but to augment it. Humans excel at divergent thinking, ethical reasoning, abstract problem framing, and connecting seemingly unrelated concepts. AI excels at convergent thinking, pattern recognition in vast datasets, rapid prototyping, and optimizing complex systems. When these distinct capabilities are deliberately integrated, the result is a cognitive leap forward—a powerful fusion, much like a mythical centaur, that delivers solutions previously unimaginable. This shift demands a radical rethink of organizational structures, skill development, and how we define “innovation” itself, acknowledging potential pitfalls like algorithmic bias and explainability challenges not as roadblocks, but as design challenges for stronger symbiosis.

The Pillars of Human-AI Symbiosis in Innovation

Building a truly symbiotic innovation capability requires focus on three strategic pillars:

  • 1. AI as a Cognitive Multiplier: Treat AI not as an autonomous decision-maker, but as an extension of human intellect. This means AI excels at hypothesis generation, data synthesis, anomaly detection, and providing diverse perspectives based on vast amounts of information, all to supercharge human problem-solving, allowing us to explore far more options than before.
  • 2. Humans as Ethical & Creative Architects: The human role is elevated to architect and guide. We define the problem, set the ethical boundaries, provide the contextual nuance, and apply the “human filter” to AI’s outputs. Our unique capacity for empathy, understanding unspoken needs, and managing the inherent biases of AI remains irreplaceable in truly human-centered design.
  • 3. Iterative Feedback Loops: The symbiotic relationship thrives on constant learning. Humans train AI with nuanced feedback, helping it understand complex, subjective scenarios and correct for biases. AI, in turn, provides data-driven insights and rapid experimentation capabilities that help humans refine their hypotheses and accelerate the innovation cycle. This continuous exchange refines both human understanding and AI performance.

“The future of innovation isn’t about AI or humans. It’s about how elegantly we can weave the unparalleled strengths of both into a singular, accelerated creative force.” — Satya Nadella

Case Study 1: Moderna and AI-Driven Vaccine Development

The Challenge:

Developing a vaccine for a novel pathogen like SARS-CoV-2 traditionally takes years, an impossibly long timeline during a pandemic. The complexity of mRNA sequencing, protein folding, and clinical trial design overwhelmed human capacity alone.

The Symbiotic Innovation:

Moderna leveraged an AI-first approach where human scientists defined the immunological targets and ethical parameters, but AI algorithms rapidly designed, optimized, and tested millions of potential mRNA sequences. AI analyzed vast genomic databases to predict optimal antigen structures and identify potential immune responses. Human scientists then performed the critical biological testing and validation, refined these AI-generated candidates, and managed the ethical and logistical complexities of clinical trials and regulatory approval. The explainability of AI’s outputs was crucial for human trust and regulatory acceptance.

The Exponential Impact:

This human-AI partnership dramatically accelerated the vaccine development timeline, bringing a highly effective mRNA vaccine from concept to clinical trials in a matter of weeks, not years. AI handled the computational heavy lifting of molecular design, freeing human experts to focus on the high-level strategy, rigorous validation, and the profound human impact of global health. It exemplifies AI as a cognitive multiplier in a crisis, under human-led ethical governance.

Case Study 2: Generative Design in Engineering (e.g., Autodesk Fusion 360)

The Challenge:

Traditional engineering design is constrained by human experience and iterative trial-and-error, leading to designs that are often sub-optimal in terms of weight, material usage, or performance. Designing for radical efficiency requires exploring millions of permutations—a task beyond human capacity.

The Symbiotic Innovation:

Platforms like Autodesk Fusion 360 integrate Generative Design AI. Human engineers define the essential design parameters: materials, manufacturing methods, load-bearing requirements, weight constraints, and optimization goals (e.g., minimum weight, maximum stiffness). The AI then autonomously explores hundreds or thousands of design options, often generating organic, complex structures that no human designer would conceive. The human engineer then acts as a discerning curator and refiner, selecting the most promising AI-generated designs, applying aesthetic and practical considerations, and testing them for real-world viability and manufacturability.

The Exponential Impact:

This collaboration has led to breakthroughs in lightweighting and material efficiency across industries, from aerospace to automotive. AI explores an immense solution space, while humans inject creativity, contextual understanding, and final aesthetic and ethical judgment. The result is parts that are significantly lighter, stronger, and more sustainable—innovations that would have been impossible for either human or AI to achieve alone. It’s AI expanding the realm of possibility for human architects, leading to more sustainable and cost-effective products.

The Leadership Mandate: Cultivating the Centaur Organization

Building a truly symbiotic human-AI innovation engine is not merely a technical problem; it is a profound leadership challenge. It demands investing in new skills (prompt engineering, AI ethics, data literacy, and critical thinking to evaluate AI outputs), redesigning workflows to integrate AI at key decision points, and—most crucially—cultivating a culture of psychological safety where employees are encouraged to experiment with AI, understand its limitations, and provide frank feedback without fear.

Leaders must define AI not as a replacement, but as an unparalleled partner, actively addressing challenges like algorithmic bias and the need for explainability through robust human oversight. By strategically integrating AI as a cognitive multiplier, empowering humans as ethical and creative architects, and establishing robust iterative feedback loops, organizations can unlock an era of innovation previously confined to science fiction. The future of human-centered innovation is not human-only, nor AI-only. It is a powerful, elegant dance between both, continuously learning and adapting.

Extra Extra: Because innovation is all about change, Braden Kelley’s human-centered change methodology and tools are the best way to plan and execute the changes necessary to support your innovation and transformation efforts — all while literally getting everyone all on the same page for change. Find out more about the methodology and tools, including the book Charting Change by following the link. Be sure and download the TEN FREE TOOLS while you’re here.

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Designing an Innovation Lab: A Step-by-Step Guide

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Designing an Innovation Lab: A Step-by-Step Guide

GUEST POST from Art Inteligencia

Innovation has become a driving force for organizations looking to adapt and thrive in an ever-changing business landscape. To foster a culture of creativity and problem-solving, many companies are now investing in innovation labs. These dedicated spaces provide employees with the tools, processes, and environment necessary to drive impactful change. This article aims to present a step-by-step guide on designing an innovation lab, exploring key considerations and showcasing two inspiring case studies.

Step 1: Defining the Purpose and Objectives

Before embarking on the design process, it is crucial to define the purpose and objectives of the innovation lab. Is it primarily focused on developing new products, enhancing customer experience, or addressing internal efficiency challenges? Identifying the intended outcomes will help shape the lab’s design, resources, and methodologies.

Step 2: Creating the Right Environment

A successful innovation lab requires a physical and cultural environment that encourages collaboration, risk-taking, and creativity. This includes considerations such as open floor plans, flexible workspaces, comfortable furniture, and access to cutting-edge technology. Attracting natural light and incorporating natural elements can also enhance productivity and well-being.

Case Study 1: Google X Moonshot Factory

One of the most renowned innovation labs is Google X, the parent company of Google. The Moonshot Factory, as they call it, is responsible for developing radical, moonshot ideas that address global issues. The lab’s unique design features open spaces, colorful furniture, brainstorming walls, and prototypes scattered throughout the area. This innovative approach creates an atmosphere that fosters creativity, experimentation, and a sense of purpose, enabling teams to tackle audacious challenges with confidence.

Step 3: Promote Cross-Pollination and Collaboration

To maximize the potential of an innovation lab, it is essential to encourage cross-pollination of ideas and collaboration among employees from various departments. By integrating diverse perspectives and expertise, organizations can foster a more holistic and inclusive approach to problem-solving. Setting up common areas, organizing regular ideation sessions, and facilitating knowledge-sharing opportunities all contribute to a vibrant collaborative culture.

Case Study 2: Autodesk’s Pier 9 Workshop

Autodesk’s Pier 9 Workshop in San Francisco serves as an innovation lab that brings together artists, designers, and engineers to explore the intersection of technology and creativity. The lab provides users with cutting-edge equipment and a platform to experiment and create innovative projects. By fostering collaboration between diverse disciplines and offering access to advanced tools, Autodesk empowers individuals to push their boundaries and unleash their creative potential.

Step 4: Implement Agile Processes and Iterative Techniques

To drive innovation effectively, organizations should embrace agile processes that allow for rapid experimentation, continuous improvement, and quick iteration cycles. Encouraging teams to adopt proven methodologies like Design Thinking or Lean Startup principles helps create a structure that balances creativity with tangible results. Emphasizing the importance of learning from failure and celebrating successes also fosters a growth mindset within the lab.

Conclusion

Designing and implementing an innovation lab requires a strategic approach with careful consideration of the purpose, environment, collaboration, and iterative processes. By following this step-by-step guide, organizations can establish a dedicated space that cultivates creativity, engagement, and breakthrough innovations. The case studies of Google X Moonshot Factory and Autodesk’s Pier 9 Workshop serve as inspiring examples of successful innovation labs that have revolutionized industries by embracing the power of human imagination and collaboration. The future belongs to those who dare to innovate, and an innovation lab is the gateway to unlocking boundless possibilities.

Bottom line: Futurology is not fortune telling. Futurists use a scientific approach to create their deliverables, but a methodology and tools like those in FutureHacking™ can empower anyone to engage in futurology themselves.

Image credit: Unsplash

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