Why Transformations Fail

Most of organizations in order to deliver a great customer experience (CX), they will need to go through some sort of transformation (in here we refer more to Digital Transformation). However, according to Forbes, 84% of companies fail in transformation. There are plenty of good articles out there that addresses the same key pain points. One of the great articles is “Leading Change: Why Transformation Efforts Fail”; in this article addresses key eight points.

In this article, I am sharing reasons of failures from my own experiences of successfully transformed companies or failed (I am being too simplistic about failing definition here) and also my observations.

#1 — Digital Transformation is not just another IT Project

In many organizations, they think to be digitally transformed, you just need to invest on technology solutions. That is a mistake #1. Digital Transformation must include various topics as shows in following figure as a one program of change.

An example of it can be organizations would like to transform and start using cloud technologies but the organization’s compliance and legal teams are not equipped for such change.

#2 — Organization does not Learn

According to Peter Senge, learning organizations encourage a holistic approach called systems thinking. Systems thinking stems from the tenets of system theory where each process integrates with all the others. Basically, it means the ability to see the big picture and to be able to see the interrelationships between what might, at first, seem to be completely unrelated. Systems thinking relies on a collective intelligence, believing that a group of people are smarter than one or two smart people. In systems thinking there’s a commitment within this process to real learning, and an agreement that occasionally, the group may be wrong. This process requires that individuals listen to every idea that’s put forward and that there are no wrong or bad ideas. While one idea may initially seem off the wall, it may result in someone else thinking outside the box and coming up with a really good idea.

There are five characteristics of a learning organization:

• Personal mastery, or how the individual looks at the world
• Mental models, or an individual’s deeply ingrained assumptions
• Shared vision, which encourages experimentation and innovation among multiple members
• Team learning, or more than one person acting together; two heads are better than one
• Systems thinking, looking at the whole picture rather than the individual problem

Within each of these characteristics there are three levels of approaches, including

• Practice, or what the individual does, which is the lowest level
• Principles, or what the individual does in keeping with the guiding ideas of the organization
• Essences, or what the individual automatically thinks in terms of the whole organization, which is the highest level of mastery

#3 — Only Seeing the Tip of the Iceberg

The quality of our thinking is proportional to the models in our head and their usefulness in the situation at hand. The more models you have — the bigger your toolbox — the more likely you are to have the right models to see reality. It turns out that when it comes to improving your ability to make decisions variety matters. We also need to be aware of our cognitive biases as well. Most of us, however, are specialists. Instead of a latticework of mental models, we have a few from our discipline. Each specialist sees something different. By default, a typical Engineer will think in systems. A psychologist will think in terms of incentives. A biologist will think in terms of evolution. By putting these disciplines together in our head, we can walk around a problem in a three dimensional way. If we’re only looking at the problem one way, we’ve got a blind spot. You can read more about how to think better in my last blog where I have put together series of mental models I have been using which is gathered from all over internet.

Systems thinking is a way of approaching problems that asks how various elements within a system — which could be an ecosystem, an organization, or something more dispersed such as a supply chain — influence one another. Rather than reacting to individual problems that arise, a systems thinker will ask about relationships to other activities within the system, look for patterns over time, and seek root causes.

One systems thinking model that is helpful for understanding global issues is the iceberg model. We know that an iceberg has only 10 percent of its total mass above the water while 90 percent is underwater. But that 90 percent is what the ocean currents act on, and what creates the iceberg’s behavior at its tip. Global issues can be viewed in this same way.

The iceberg model allows us to explore a more complete picture of the different factors that may be at play in any given situation of your organization. Think of a problem that you’re currently facing at your company. What you see at the top of the iceberg is the “event” where that problem manifests e.g. “Someone in my team has called in sick every week recently.”

But look below the event level to consider what might be contributing to causing the visible event. Firstly, what are the patterns/trends over time? e.g. “This increased absence rate started at the end of the summer.”

Next, identify what underlying structures may be influencing the trends e.g. “Over the summer senior management announced that funding for two major projects was up for review at the end of Q3.”

Finally, consider what mental models those involved may have about the situation e.g. “Team members think that funding is going to be cut for their projects and feel like they weren’t consulted and may be about to lose their jobs. As a result they have lost motivation.” and “Senior management doesn’t necessarily intend to cut funding but would like to shift to quarterly reviews of specific deliverables but don’t think it’s a priority to communicate this to staff.”

This analysis might suggest some actions to take to address the absence rate — maybe a consultation where staff can ask senior management questions and be reassured about the new process and where management can learn what information staff require to stay engaged.

If an organization wants to offer better customer experience, they need to start having transformation in mental model level (look at the above figure and example). You can also use many of tools provide here: https://toolbox.hyperisland.com/

#4 — Unclear Transformation Goals

Before initiating digital transformation, it is important to identify the exact business goal, a strategic initiative that will help your organization to reach a new level of revenue or saving cost. Do employees have a clear understanding of these goals? Are they aware of the future digital transformation process? Keep it simple.

Any digital transformation may affect the following aspects:

• Process automation;
• Remote working;
• New technologies;
• A new website;
• A new marketing strategy;
• Business model changes;
• Digital-first customer experience.

To avoid mistakes during digital transformation, it is worth considering the business vectors of the company. What are the goals of transformation? What needs to be transformed? For large businesses to understand the goals and stages of digital transformation you have to create a roadmap. It will help you to track every step of the transformation process.

Tool : https://toolbox.hyperisland.com/alignment-autonomy Purpose: A workshop to support your business and teams by minimizing barriers to being agile & flexible and maximizing alignment & autonomy — enabling teams to adapt to change to achieve better results faster. Use this to help yourself and others work in a collaborative, committed culture. Inspired by Peter Smith’s model of Alignment & Autonomy, also called Alignment & Personal Responsibility.

#5 — Business Transformation Expertise are Missing

Lack of experience in business transformation leads to basic mistakes, such as initially incorrectly set goals, lack of a clear strategy, risk management, hiring wrong person for a wrong role and adequate resources. Often, a large number of these mistakes make the whole digitalization strategy fail. Of course, the company that is going through digital transformation does not necessarily have to be experienced. Indeed, there is no need to be a pro in new technologies or strategies. But to make the digital transformation process successful, companies without any expertise have to seek advice from external experts. I am not referring to consulting firms only, it is about outside experts who have done such tasks before.

#6 — Too Many Talkers

Be careful with hiring too many talkers. You need to stop using PowerPoints as much as possible. Instead, increase your PoC (Proof of Concept) and see demos. Regardless how ugly or unsexy the demo is; a unsexy demo is better than 100s of beautiful PowerPoint slides.

When creating the strategy listen to the lab coats not the suits. Get the lab coats to produce prototypes, not slideshows.

Never forget that hiring is the most important thing you do. Lots of people say that, but then they delegate hiring to recruiters. Everyone — EVERYONE! — should invest time in hiring not just recruiters.

#7 — Lack of Mental Models among Employees

Be aware of cognitive biases as well (A cognitive bias is a systematic error in thinking that affects the decisions and judgments that people make). Most of us, however, are specialists. Instead of a latticework of mental models, we have a few from our discipline. Each specialist sees something different. By default, a typical Engineer will think in systems. A psychologist will think in terms of incentives. A biologist will think in terms of evolution. By putting these disciplines together in our head, we can walk around a problem in a three dimensional way. If we’re only looking at the problem one way, we’ve got a blind spot.

Mental models are psychological representations of real, hypothetical, or imaginary situations. According to the model theory, everyday reasoning depends on the simulation of events in mental models (e.g., Johnson-Laird, 2006). The principal assumptions of the theory are:

1. Each model represents a possibility. Its structure corresponds to the structure of the world, but it has symbols for negation, probability, believability, and so on.
2. Models are iconic insofar as possible, that is, their parts and relations correspond to those of the situations that they represent. They underlie visual images, but they also represent abstractions, and so they can represent the extensions of all sorts of relations.
3. Models explain deduction, induction, and explanation. In a valid deduction, the conclusion holds for all models of the premises. In an induction, knowledge eliminates models of possibilities, and so the conclusion goes beyond the information given. In an abduction, knowledge introduces new concepts in order to yield an explanation.
4. The theory gives a ‘dual process’ account of reasoning. System 1 constructs initial models of premises and is restricted in computational power, i.e., it cannot carry out recursive inferences. System 2 can follow up the consequences of consequences recursively, and therefore search for counterexamples, where a counterexample is a model of the premises in which the conclusion does not hold.
5. The greater the number of alternative models needed, the harder it is: we take longer and are more likely to err, especially by overlooking a possibility. In the simulation of a sequence of events, the later in the sequence that a critical event occurs, the longer it will take us to make the inference about it.
6. The principle of truth: mental models represent only what is true, and accordingly they predict the occurrence of systematic and compelling fallacies if inferences depend on what is false. An analogous principle applies to the representation of what is possible rather than impossible, to what is permissible rather than impermissible, and to other similar contrasts.
7. The meanings of terms such as ‘if’ can be modulated by content and knowledge. For example, our geographical knowledge modulates the disjunction: Jay is in Stockholm or he is in Sweden. Unlike most disjunctions, this one yields a definite conclusion: Jay is in Sweden.

The difference between great thinkers and ordinary thinkers is that, for ordinary thinkers, the process of using models is unconscious and reactive. For great thinkers, it is conscious and proactive. Micheal Simmons has plenty of great resources to read about mental model besides Farnam Street has plenty of great resources as well.

#8 — Underestimating Internal Resistance

It requires courage to start a new project and be open to experiments. Creating new products and services takes a lot of additional effort. Besides these difficulties, it is important to be patient and minimize risks. It is natural for an organization to collectively fear going through a large transformation. There will be fear that the risks are too high. Nowadays, the risk of not going digital is much higher than the risks of failure. It is especially true amid current offline market disruption, which you can often encounter. You don’t have to look for an example — the lockdowns caused by the COVID-19 pandemic completely paralyzed many offline processes. In addition to such obvious examples, it is clear that being in digital space is a reasonable requirement for any modern-day organization.

However, internal resistance is real and demotivates good employees who are going to make the transformation success. This resistance is specially stronger on employees who are in the organization for more than 4 or 5 years. The resistance shows itself in various format such as:

• Strongly rejecting the idea of change
• Silently form a team and drag the situation for so long that transformation fails or leadership to give up
• Employees might claim we like to change but … (various reasons without offering any solution)
• Finding irrelevant excuses to shut down the employees who are causing transformation, the usual excuses are mainly HR or core value related because it is not measurable and fosters gossiping easily.

#9 — Underestimating Employee Experience

I’ve written a separate article on this topic and you read it there. ReThinking HR — An article on how HR department can cause employee experience.

#10 — Unspoken disagreement among top managers about goals

I’ve heard many times this sentence when I asked any key executives why you did not voice your opinion in the meeting then I get a response: “You might call me politician or diplomatic, but I wanna ensure I stay long enough here so I can make a change in a right moment”. Well, there is nothing wrong in that response but there many bad leadership there which causes a culture that leads to transformation failure.

If top managers aren’t on the same page, it makes it difficult for their direct reports to agree on what to prioritize and how to measure progress. The remedy: Define and articulate not only the opportunity but also the problem it solves, and how the company will build the organization around the desired solution before investing.

#11 — Too Many Fancy Words

Transformation is not about how many fancy words your organization is going to use to impress. Do not fell into the trap of using all hype words like agile (less, safe, spotify, etc models), customer journey, value proposition, business model canvas, design thinking, card sorting, tree testing and many more. There is nothing wrong with any of these concepts but always remember what your organization need. Build a roadmap. Rome was not built in one day. Hire your senior leadership team according to your needs. Do not hire too early wrong roles, if you need foundation work then ensure you hire foundational leadership first then move into more high-tech stuff like ML.

#12 — Not Changing the Culture

I’ve talked about culture in a great length in this article. In the 3 layers of culture, focus more efforts on “Underlying Beliefs” and be aware of the trap for “Artifacts” layer of culture. Schein gives us four lenses to look at culture:

1. Analyzing the process and content of socialization of new members
2. Analyzing responses to critical incidents in the organizations history
3. Analyzing beliefs values and assumptions of culture creators or carriers
4. Jointly exploring and analyzing with insiders the anomalies or puzzling features observed or uncovered in interviews

How to verify if the team is ready for digital transformation

• Staff feel positive about the changes;
• Teams understand how their work will benefit from the changes;
• Ensuring incentives that promote taking risks;
• People feel that they contribute to future success.

Any company has to make sure the team is on its side when making significant changes. People like to understand what this digital transformation is for. It is necessary to explain how the company is going to reach this goal. Communication inside the team helps people feel like they are a part of the process.

Related Articles

I’ve been very obsessed with “experience” and written series of post which I think might be good to read them (or you can skip them) as listed in below:

• Engineering Culture to deliver great CX — Sharing a culture that helps to deliver great CX
• Empathic Banking — An example of building a great CX in banking
• Driven vs Centric — An article on “Data-Driven and Data-Centric” and “Customer-Driven and Customer-Centric”
• Core Values — An article on why core values boost employee experience
• Agile Organization — An article on how to transform and why needs to be agile
• ReThinking HR — An article on how HR department can cause employee experience
• Culture Framework — A methodology on how to build corporate culture
• Thinking Better — An approach to think and transform systematically
• Experience — A post on what is Experience
• Engineering Experience — A framework on building experience
• Know-* Management Team — An article on how to build a management team
• Core Values are not simply your DNA — Trying to go a bit deeper on what’s core value
• Experience Engineering by Digital Transformation — Building an experience using technology
• Components of Experience, the key components of building an experience
• Organizational Barriers to Delivering Customer Experience, what are the key barriers to build a good experience within each organization
• Brand and Customer Experience, sharing how employee and customer engagement are connected when it comes to building an experience
• Pricing for Better Experience. Finding the right balance between value and revenue — your ability to help customers and be fairly compensated for that help — will make or break a SaaS company
• Employee Stock Options Plans (ESOP). Having ESOP, in short, means employees are directly invested in the company’s future. It’s simple — happier employees make happier customers. Those employees who hold ESOP work on average 8 hours more per week (416 hours a year which is equal to ~35 extra days of 12 hours per day in a year) than those that do not own ESOP (of course quality is more important but quantity of hours matter too).