Tag Archives: EX

Customer Experience, Governance, Leadership

From Behaviors to Business Value: A Customer Experience Framework for Operationalizing CX

August 2, 2026 Doug Tedder Leave a comment

Customer Experience (CX) is broadly defined as a customer’s overall perception of a company or brand based on all their interactions with it. This spans every step of the journey, such as visiting a website or store, interacting with customer service, using a product or service, or receiving follow-ups, emails, or support.

For example, if you quickly find what you need on a website, get helpful support when you have a problem, or receive your product on time, you’d likely say that the company provides good CX. However, if any of those things go poorly, you’d probably say that you had a bad CX.

This simple example highlights the core challenge of CX. CX – good or bad – is based on the perception of the customer. While companies do not control the customer perception, they can influence it through the experiences they design and deliver.

Business leaders know CX matters. But many businesses struggle to connect CX to employee behaviors, business decisions, budgets, and organizational priorities.

It’s not that these organizations aren’t collecting customer experience metrics. They are measuring customer reactions rather than intentionally designing the experience. More importantly, they are not linking those experiences to business results.

Are you focused on the effect rather than the cause?

Many organizations treat CX as a “soft” discipline and rely heavily on perception-based metrics. For example, surveys and measures like NPS and CSAT focus only the perception of the customer post-interaction. This reactive approach provides limited insight into business results, resulting in CX being viewed separately from business performance. This makes it difficult for business leaders to justify CX investments because they cannot connect investments to business outcomes.

Having said that, CX is a key differentiator as products and services become more similar and commoditized. Poor CX can (and will) drive customers away – even if the product itself is good.

In the face of “doing something rather than nothing”, business leaders often invest in “last mile” customer-facing capabilities in reaction to poor CX scores. Organizations invest in digital capabilities like mobile apps, AI chatbots, and self-service portals as they perceive that customers prefer these channels for interaction. They invest training and coaching programs within the contact centers to teach skills like structured problem-solving or empathy. Or they invest in workforce management tools and flexible staffing models to better forecast and meet anticipated customer demand.

And while these investments may influence the customer perception in the moment, they still do not directly translate to business results. In fact, they often mask the real issues – poor system design, poor understanding of the customer journey, and a poor understanding of the underpinning foundation that enables good CX.

Where good CX actually starts

Good CX does not start at the digital channel or the interaction with a contact center. Not taking these steps in order results in the service and support provided at the last mile appearing to be an afterthought.

Good CX results from the following three steps:

First, understand the real-world issue customers are encountering through journey design. Journey design focuses on the human experience, mapping out the steps a customer takes to achieve a goal, uncovering their emotions, points of friction, and needs along the way.

The next step is to engineer a scalable user-friendly way for the customer to accomplish their goals and eliminate those points of friction. This is done via product and solution design. To be clear, product design focused on building a specific repeatable vehicle isn’t enough; the end-to-end infrastructure, software, and processes needed to deliver a solution must also be developed. (Design thinking is a good approach for product and solution design.)

The last step in enabling good CX is the intentional design of service and support. Intentionally designing the operational workflows, contact center procedures, knowledge bases, and contact channels to help customers before the customer needs help ensures that resolution to issues feel seamless and matches the experience designed during journey mapping.

Following these three steps shifts the focus from reacting to the feedback of the day to proactively developing and delivering the CX the organization wants. Now CX becomes measurable in a way that is relevant and meaningful to the business.

A framework for measuring CX

When it comes to measuring CX, most organizations focus on the effect, rather than the cause. This focus on the effect often results in organizations investing in things that may not move the needle when it comes to realizing business outcomes from CX.

Building on the foundation of journey design, followed by product and solution design, and finally to purposeful design of service and support, organizations can focus on identifying and implementing CX measures that are relevant to organizational strategy and business results. Drawing on established performance management principles, a simple cause-effect-business outcome CX framework (similar to service value streams) can be used to measure and evaluate CX.

Cause – “Cause” represents behaviors that are within the control of the organization. The cause consists of employee behaviors and operational activities that shape the customer experience. Employees that follow through on commitments, demonstrate ownership, and solve issues quickly shape a positive customer experience.
Effect – The effect represents what customers experience and perceive. This is where the traditional measures like NPS, CSAT, and survey responses belong, and reflect if the intended experience is being delivered.
Business Outcome – Business outcomes illustrate whether the customer experience is delivering business value. Business results and value are typically depicted in an organization’s goals and objectives, and represent targets like revenue growth, customer retention, reduced customer churn, and lower service costs. When measures connect cause to effect to business outcomes, CX evolves from being just a customer service initiative to a business discipline.

This is not to say that perception measures like NPS and survey feedback are no longer needed or useful – they are. But too many organizations consider perception metrics to be the goal, which it is not. Perception metrics help the organization understand if the customer is realizing the intended outcomes of product and service design.

Secondly, the strongest causes are both observable and measurable. It’s one thing to say that an organization demonstrates customer focus; it’s another thing to measure that customer focus in terms of response time, resolution quality, and commitment completion rates.

Lastly, keep in mind that not every behavior influences every business outcome. Organizations must first identify the causes that have both the greatest impact on customer experience and on business results.

Making CX Measurable and Meaningful

Making CX measurable and meaningful starts with shifting focus from what customers say to what drives their experience – and how that connects to business outcomes. Ask these three questions:

What customer behaviors or employee actions are we measuring as causes?
What customer perceptions are we measuring as effects?
What business outcomes are we expecting those experiences to produce?

If you can measure the effect but not identify the cause or connect it to a business result, your CX measurement framework is incomplete.

AI and Modernization, Human Centered Design, Leadership

Technology is Easy. Experience is Hard. Here’s How to Get it Right.

March 3, 2026 Doug Tedder

There is a tendency within many organizations to take a “technology first” approach to solve every business challenge. In more cases than not, this approach simply creates more challenges and friction within organizations; it is a very short-sighted view.

Organizations do need technology – without it, organizations cannot compete in the digital economy.

But there is a lot of FOMO in today’s business technology environment, valuing speed over strategy.

The often-ignored aspects of rapid technology implementation

When an organization prioritizes speed of implementing technology, it usually results in some significant issues being ignored. Issues such as:

Changes to the organizational operating model. Technology changes the enterprise operating model by reshaping how the whole business creates, delivers, and captures value across structure, processes, people, and governance—not just how IT runs.
Impact of change on people. Organizations often underestimate, if not ignore, the impact of technology implementation on the people the technology was intended to help.
The weight of technical debt. Unless governance keeps pace with technology introduction, rapid introductions of technology can introduce new technical debt in system architectures, data, and model lifecycle. At the same time, many organizations ignore the impact of existing technical debt from legacy systems, customizations, and integrations.

Experience enablement ensures successful technology implementations

Think about it – in the digital economy, all companies have some level of technology enablement. But this ever-increasing rush to implement technology out of the fear of being left behind will have negative consequences – unless the fundamental challenges noted above are addressed.

But I believe that success with technology implementation depends on a single critical factor – the people that use that technology. This highlights the need for a good human experience, both between organizations and their external stakeholders as well as the stakeholders within those organizations.

I am convinced that the experience – the total end‑to‑end journey and feelings of a person interacting with a company or product – is the differentiating factor for organizations in the digital economy. But if technology implementations do not enable that differentiating experience, those organizations will not realize their full potential in the digital economy.

Can an organization achieve its strategy, the demand for speed and agility in the marketspace, and address the need for a good experience for those that interact with technology? The answer is yes – but organizations first must slow down to go fast.

Four Steps to Slow Down and Accelerate Success

How can an organization meet the demands for speed and agility in the market space, yet ensure that technology implementations enable the right experience? It can be done – if organizations first slow down to go fast. Here are the four steps organizations must take to slow down to accelerate success.

Digital business strategy – A well-defined digital business strategy is a critical first step for organizations wanting to leverage technology to deliver business outcomes and value. A digital business strategy ensures that the appropriate technologies are identified for achieving those business results.
Mapping value streams – A value stream map shows how value flows through an organization – and the systems and technology that enables the flow of value. When organizations understand their value streams, they can identify and address any areas of friction resulting from the use of technology.
Define proto personas – Proto personas help organizations understand the goals, needs, and behaviors of the consumers that will be using their products and services.
Journey mapping – Whether it’s a customer or an employee, it’s critical to understand the experience of people’s interactions with an organization. Use those proto personas to produce journey maps. Journey maps depict the touchpoints and experiences – and the impact of technology (good or bad) – humans have while interacting with an organization.

Technology without delivering the right experience is a recipe for failure

As I’ve written before, if technology implementations do not enable that differentiating experience, those organizations will be left behind in the digital economy. But admittedly, organizations taking a “tools first” approach to business challenges is nothing new.

But, delivering that right experience should not be left to chance. A “tools first” approach may address one area of concern but typically will miss other areas of concerns. Different consumers have different expectations of the experience they have with organizations. Implementation of technology without a well thought and integrated business strategy results in wasted time, money, and resources. Such an approach usually results in needless complexity. The different value streams within an organization have different requirements for velocity. Technology solutions must accommodate those requirements.

These are leadership issues, not technology issues. And it takes courage to stand in the face of well-intentioned but misguided demands for rapid technology implementations.

The best way to ensure success in the digital future is to plan for that future. Defining the digital business strategy, mapping value streams, understanding who will be interacting with your organization using proto personas, and journey mapping provides a clear path to success in the digital age.

AI and Modernization

The more AI we become, the more human we need to be

April 3, 2024 Doug Tedder

Why are AI assistants given human-like names?

Apple provides Siri[i]. Amazon has Alexa[ii]. Samsung features Bixby[iii]. And there are literally dozens of other examples, in use both publicly and privately.

The attribution of human characteristics to non-human entities is known as anthropomorphism. Attributing human intent to non-human entities, such as pets, robots, or other entities, is one way that people make sense of the behaviors and events that they encounter. We as humans are a social species with a brain that evolved to quickly process social information.[iv]

There are numerous examples of anthropomorphism with which we are familiar, and honestly, don’t even think twice about. In Toy Story[v], the toys can talk. In Animal Farm[vi], the animals overthrow their masters and govern themselves. In Winnie-the-Pooh[vii], Christopher Robbin interacts with Winnie, a talking bear.

Is this why AI-enabled chatbots and digital assistants are given human-like names? To make us want to talk to them? To make it easy to interact with them? To influence our thinking and behaviors?

Without over psycho-analyzing the situation (and I am far from qualified to do so), the answer to the above questions is “yes”.

The good – and not so good – of today’s AI capabilities

AI capabilities have been around for quite some time. While philosophers and mathematicians began laying the groundwork for understanding human thought long ago[viii] , the advent of computers in the 1940s provided the technology needed to power AI. The Turing Test, introduced in 1950, provided a method for measuring a machine’s ability to exhibit behavior that is human-like. The term and field of “artificial intelligence”, coined by John McCarthy in 1956, soon followed.

The past few years have seen a dramatic expansion of AI capabilities, from machine learning to natural language processing to generative AI. That expansion has resulted in impactful and valuable capabilities for humans. AI is well-suited for managing tedious and repetitive tasks. AI can be used to initiate automated actions based on the detection of pre-defined conditions. AI can facilitate continual learning across an organization based on the data captured from interactions with and use of technology. And most recently, AI is developing a growing capability to respond to more complex queries and generating responses and prompts to aid humans in decision-making.

But despite all the progress with AI, there are some things that are not so good. Miscommunication can occur due to limitations of a chatbot or an AI assistant in understanding user intent or context. A simple example is the number of ways we as humans describe a “computer”, including “PC”, “laptop”, “monitor”, or “desktop” must be explicitly defined for an AI model to recognize the equivalence. AI is not able to exhibit empathy or the human touch, resulting in frustration, because humans feel that they are not being heard or understood.[ix] AI is not able to handle complex situations or queries that require nuanced understanding; as a result, AI may provide a generic or irrelevant response.[x] The quality of responses from AI is directly dependent upon the quality of the input data being used – and many organizations lack both the quality and quantity of data required by AI to provide the level of functionality expected by humans. Lastly, but perhaps most importantly, the expanding use and adoption of AI within organizations has resulted in fear and anxiety among employees regarding job loss.

Techniques that will help humanize AI

Several techniques can help organizations better design human interactions with AI. Here are a few to consider that can help humanize AI.

Employing design thinking techniques – Design thinking is an approach for designing solutions with the user in mind. A design thinking technique for understanding human experience is the use of prototypes, or early models of solutions, to evaluate a concept or process. Involving the people that will be interacting with AI through prototypes can identify any likes or encountered friction in the use of AI technology.
Mapping the customer journeys that (will) interact with AI – A customer journey map is a visual representation of a customer’s processes, needs, and perceptions throughout their interactions and relationship with an organization. It helps an organization understand the steps that customers take – both seen and unseen – when they interact with a business.[xi] Using customer journey maps helps with developing the needed empathy with the customer’s experience by identify points of frustration and delight.
Thinking in terms of the experience – What is the experience that end-users need to have when interacting with AI? Starting AI adoption from this perspective provides the overarching direction for making the experience of interacting with AI more “human”.

Start here to make AI use more human

AI adoption presents exciting opportunities for increasing productivity and improving decision-making. But with any technology adoptions, there is the risk of providing humans with suboptimal experiences with AI. Here are three suggestions for enabling good human experiences with the use of AI.

Define AI strategy – Success with AI begins with a well-defined strategy that identifies how AI will enable achievement of business goals and objectives. But AI success is not just business success or technical success with AI models, but also whether users are happy with AI and perceive it to be a valid solution. [xii]
Map current customer journeys – Mapping current customer journeys may expose where user interactions are problematic and may benefit from the introduction of AI.
Start and continually monitor the experience – Happy Signals, an experience management platform for IT, states that “humans are the best sensors”. Humans are working in technological environments that are in a constant state of change and evolution. Actively seeking out and acting upon feedback from humans regarding their experiences with technology raises awareness of the user experience and fosters a more human-centric approach to technology use and adoption.

The best way to ensure that AI-enabled technologies are more human is to design them with empathy. Design thinking, customer journey mapping, and experience management will help ensure that AI stays in touch with the “human” side.

Need help with customer journey mapping? Perhaps using design thinking techniques to develop solution-rich, human centered solutions for addressing challenges with customer and employee experience? We can help – contact Tedder Consulting for more information.

[i] “Siri” is a trademark of Apple, Inc.

[ii] “Alexa” is a trademark of Amazon.com, Inc. or its affiliates.

[iii] “Bixby” is a trademark of Samsung Electronics Co., Ltd.

[iv] https://www.psychologytoday.com/us/basics/anthropomorphism , retrieved March 2024.

[v] Lasseter, John. Toy Story. Buena Vista Pictures, 1995.

[vi] Orwell, George. Animal Farm. Collins Classics, 2021.

[vii] Milne, A.A., 1882-1956. Winnie-the-Pooh. E.P. Dutton & Co., 1926.

[viii] Wikipedia. “History of artificial intelligence”. Retrieved March 2024.

[ix] https://www.contactfusion.co.uk/the-challenges-of-using-ai-chatbots-problems-and-solutions-explored , retrieved March 2024.

[x] Ibid.

[xi] https://www.qualtrics.com/experience-management/customer/customer-journey-mapping , retrieved March 2024.

[xii] Ganesan, Kavita. “The Business Case for AI: A Leader’s Guide to AI Strategies, Best Practices, & Real-World Applications”. Opinosis Analytics Publishing, 2022.

Customer Experience, Service Management

Why your SLAs aren’t helping your XLAs

March 5, 2024 Doug Tedder 1 Comment

It may be hard to believe, but the term “experience economy” is nothing new. The term was first mentioned in this 1998 Harvard Business Review article. In the article, the authors posited that an experience occurs when a company intentionally uses services as the stage, and goods as props, to engage individual customers in a way that creates a memorable event. In other words, it’s not enough to have great products and services; it’s the experience of the customer that differentiates companies from their competition.

Fast forward to today, and these “memorable events” have become a significant factor in today’s employee-employer relationship, broadly known as employee experience (EX). Companies providing a good EX can attract and retain top talent, deliver better experiences to their customers, and have employees who are more committed to the company.

What is the experience like when employees are interacting with technologies and services within your company? Is your organization actively measuring and improving those experiences? Is your company committed to a great employee experience?

These are answers that an XLA, or Experience Level Agreement, will reveal.

XLAs provide a different perspective

In IT, there is a tendency to focus on and measure things like technology performance and process execution. Often there is little attention given to how end users perceive the quality and effectiveness of technologies, apart from when an end user reports an incident or makes a service request.

An XLA provides a different perspective. An XLA provides focus to end-users’ experience and needs, by measuring the outcomes and the value of services provided. An XLA seeks to understand how end users feel about their interactions with technology and with those with whom they interact during those interactions.

By understanding the experience, organizations can identify where measures reported by IT do not reflect the end user experience. Understanding the experience also helps identify potential areas for improvement, whether that be with a service, a product, a process, or any other aspect that the end user leverages to get their jobs done.

XLAs are becoming increasingly popular as employers realize that good EX is essential for business success. ” This article from reworked.co discusses the impact of a positive EX:

23% higher profitability
28% reduction in theft
81% reduction in absenteeism
41% reduction in quality defects
64% reduction in safety incidents

Clearly, good EX is good business.

XLA vs. SLA

So, what’s the difference between an XLA and an SLA, or Service Level Agreement?

An XLA focuses on happiness and productivity metrics from the end-user perspective.[i] XLAs focuses on measuring the quality of the user experience, rather than just technical metrics like uptime or response times.

An SLA is an artifact of many ITSM (IT Service Management) adoptions. An SLA, as described by ITIL^®[ii], is a documented agreement between a service provider (typically IT) and a customer that identifies both services required and the expected level of service.[iii] SLAs are intended to manage expectations and ensure both IT and non-IT parts of the organization understand their responsibilities. SLAs should also provide a framework for measuring performance and holding the provider (IT) accountable if they fail to meet their commitments.

SLAs are managed by the service level management practice, which is typically found within IT departments. The purpose of service level management is to set clear, business-based targets for service levels, and ensure that delivery of services is properly assessed, monitored, and managed against these targets. [iv] The SLAs produced should relate to defined business outcomes and not simply operational metrics.

An XLA is not meant to replace an SLA but work alongside SLAs to ensure a holistic view of value and results from the use of IT services.

But wait, isn’t quantifying, reviewing, and discussing business value and results part of SLAs and service level management?

Well, yes. But most organizations that claim to have SLAs, really don’t have SLAs.

The problem with most SLAs

What many companies are calling “SLAs” fall far short of being a service level agreement. Why?

Services are not defined and agreed. What and how IT services enable or facilitate business results and business value have not been defined and agreed between IT and non-IT senior managers. Furthering the confusion, what many IT organizations call a “service catalog” only describes technologies and service actions that consumers can request, not business value and outcomes.
The so-called “SLA” discusses IT, not the organization. SLAs discuss IT operational performance – typically related to only the service desk – and not business performance. Indeed, many of the issues related to SLAs (for example, the Watermelon Effect) are as a direct result of ITSM tools using the term “service level agreement” as a misnomer for business performance target
IT arbitrarily decides its own performance and success metrics. And these metrics are either measures that an ITSM platform administrator used in her last job, or metrics pre-configured within the ITSM platform, or metrics that a senior IT leader picked. Regardless, these performance measures are usually not relevant to anyone in the organization outside of IT.
Organizations (including both IT and non-IT leaders) take the wrong approach to SLA. Neither service providers (IT) nor service customers (non-IT managers) invest the time and effort to define services, the relationship and expectations between IT and the non-IT parts of the organization, and agree on business-relevant terms and performance measures. As a result, there is no shared, mutual understanding established regarding the use and importance of technology within the organization.

Close the gaps between SLA and XLA

Understanding how technologies and processes enable business outcomes, as well as what the organization – and the employee – truly value, is critical for a good EX within today’s organizations.

If XLA adoption reveals EX challenges, closing the gaps between SLAs and XLAs will help. Here are some things to try.

Define services – in business, not IT terms. Clearly defining and agreeing IT services between IT and non-IT leaders, including service-specific performance measures. Mutual understanding of business value and outcomes from the use of services is foundational for good EX.
Apply Design Thinking. Design thinking is a human-focused method of problem-solving that prioritizes the solution instead of the problem. Identify where EX is falling short, then apply design thinking techniques to redesign the experience to meet both the employee’s and employer’s needs.
Are your SLAs really SLAs? If SLAs aren’t documented or agreed with non-IT leaders, or SLAs do not identify clear, business-based measures for quantifying success, then you don’t have SLAs. Treat this as an opportunity to build good business relationships and establish true SLAs, resulting in better business outcomes and EX.

While XLA adoption can be a real revelation for an organization, it is not a magic wand for instantly improving EX. Like SLAs, XLAs can only be effective through collaboration, leadership, and having a continual improvement mindset across the entire organization. Resolving the gaps between SLAs and XLAs will help.

[i] https://www.happysignals.com/the-practical-guide-to-experience-level-agreements-xlas

[ii] ITIL is a registered trademark of AXELOS Limited.

[iii] ITIL Foundation: ITIL 4 Edition. Norwich: TSO (2019)

[iv] Ibid.