The Complete Guide to Digital Transformation (+12 Examples)

Christian Berg
January 27, 2023
30 min read

Learn why digital transformation is crucial for business leaders and how to succeed. Includes over 12 examples you can learn from.

Industrial digital transformation


Chances are you’re already tired from hearing and reading about the digital transformation in the media and from tech businesses of all kinds. It’s been one of the most frequently mentioned technological trends of the last decade or so. Despite such wide and long-lasting publicity, today digital transformation is still very much relevant, as businesses in the post-COVID era need to meet even tougher market demands and customer expectations than ever before.

The ability to collect, store, organize and use data plays a fundamentally important role in enabling the success of digital transformation. Which is why we at Clarify decided it’s a good time to talk about digital transformation in more detail, covering the aspects of it that are the most crucial for business leaders and company managers to know about today.

What is digital transformation?

Digital transformation is an umbrella term that describes various processes and initiatives directed towards integrating new digital technologies into business operations as well as modernizing existing IT/OT systems, workflows, approaches and business strategies.

We should note that digital transformation is a cultural change as well as technological. It encompasses all sides of business operations: from management, sales and marketing to customer experience.

But it is safe to say that technological modernizations still play a leading role in this process. The ability to connect various machines and other industrial equipment into a network, allowing them to exchange information and transmit data to a centralized system for real-time tracking and analysis, is a key component of the digital transformation.

We've seen the COVID crisis rapidly re-shape both the "what" and the "how" of companies' digital transformation agendas.
Melissa Swift
, U.S. Transformation Leader at Mercer

Why is digital transformation important?

In the modern-day world, businesses and non-commercial organizations simply cannot afford to ignore the need for digital transformation. In fact, for many companies, it’s a matter of staying in business and keeping up with the competition. As the penetration of innovative technologies across industries and market segments continues to unfold, the market demands and customer expectations are also on the rise. And digital transformation is the only way for companies to evolve and stay in the game when the standards of productivity and efficiency are rising, fueled by new technologies.

Already moving full speed ahead, the digital transformation was further fueled by the COVID-19 pandemic and economic turbulence that was caused by it. The pandemic resulted in a significant change in consumer behaviors, disrupted supply chains, increased the demands for operational flexibility, and altered innovation priorities of businesses towards rapid integration of technologies that enable remote work.

“We've seen the COVID crisis rapidly re-shape both the "what" and the "how" of companies' digital transformation agendas. Take employee experience for example. Even as employee experience has become a key theme in the HR community, in IT circles this notion had been getting a mixed reception – sometimes stereotyped as "spoiled employees expecting best-in-class consumer-grade tech on shoestring budgets,” said Melissa Swift, U.S. Transformation Leader at Mercer, an American business consulting company. “Today, with a vast portion of the workforce now remote, employee experience of digital technology has gone from "nice to have" to "the only way work gets done. Consequently, it's getting the problem-solving focus it likely long deserved."

Key benefits of digital transformation in the post-COVID economy

Here are a few most key and relevant reasons why you can’t avoid the need to implement a digital transformation project in the modern post-COVID economy.

Ddigital transformation and adoption of new technologies survey
How COVID-19 pandemic accelerated digital transformation and adoption of new technologies. Accenture Research

Digital transformation vs. digitization vs. digitalization

If you thought that digital transformation, digitization and digitalization are the interchangeable terms that all basically mean the same, you are not alone. It’s common for people to use them interchangeably even though these three terms do refer to different processes (or different stages of the same process, depending on how you look at it). A few words about each.

What is digitization?

In simple words, digitization defines the very first stage of this process, which begins with moving all business records and documents from analog physical formats and data carriers (paper). The process of converting all business data and the modes of exchanging it from paper to digital formats is digitization. As part of digitization, organizations give up the old-fashioned devices designed with paper-based information exchange in mind, such as faxes, printers and Xerox copier machines, and move to computers and digital files.

What is digitalization?

Now, digitalization is the second stage of this process. This term describes the utilization of the digitized data to improve business processes, optimize workflows and simplify the information exchange. What’s important to note is that digitalization doesn’t involve the transformation of business approaches or creating new types of business models per se. It is limited to leveraging the data in digital format and integrating it into existing business processes to simplify them as much as possible for everyone involved, from company employees to end-customers.

What is digital transformation?

Finally, there’s digital transformation as the final third stage of this process. Digital transformation does involve changing the way organizations operate, moving to new business models, approaches and workflows. It also drives the emergence of totally new business fields and market niches. Digital transformation requires organizations to revise their business operations across every layer, from the management approach, employee training and customer relations to IT systems and hardware solutions.

In other words, digital transformation is taking the full advantage of new technologies to completely transform the way work is done and achieve a significant leap forward in overall efficiency, productivity and business performance.

Digital transformation should begin with a problem statement, a clear opportunity, or an aspirational goal. The "why" of your organization's digital transformation might be around improving customer experience, reducing friction, increasing productivity, or elevating profitability.
Jay Ferro
, chief information & technology officer at Clario

History of digital transformation

Naturally, digital transformation is quite a new concept, but its history goes far back. Even further than many of us may expect. In fact, its origins are traced back to the 1940s.

In 1948, Dr. Claude Shannon published his paper titled “A Mathematical Theory of Communication,” which is considered to be the very first scientific document detailing the future of digitizing business data and interactions between enterprise systems.

The theoretical concept of digitizing data was first enabled in the 1950s with the invention of semiconductor transistors and microchips. This followed by the establishment of ARPANET (the Advanced Research Projects Agency Network), the first wide-area packet-switched network with distributed control and the predecessor of the Internet, in the late 1960s.

Starting from the 1970s, first businesses began to integrate computer-aided design and manufacturing solutions, and the conversion of analog paper-based data into digital form became a reality.

This process was further extended in the 1980s with the invention of the TCP/IP-based Internet and the penetration of industrial automation solutions across different industrial and business fields. Various specialized business software systems, such as ERPs (enterprise resource planning systems), CRM (customer relationships management), eCommerce and online banking solutions, and other tools, were introduced in the late 1980s and early 1990s, permanently marking the era of digitalization.

Another notable milestone is the introduction of 2G cellular networks in the 1990s with the spread of digital mobile phones and connections around the globe.

Modern-day digital transformation

We can say that the process of digital transformation fully took off in the 2000s when Internet access, connected personal computers and mobile devices became truly widespread, having a dramatic effect on the way people and organizations around the globe communicate and exchange data.

First reports documenting the benefits and success of digital transformation projects started to emerge in the early 2010s.

In 2015, MIT Sloan Management Review and Deloitte published a report titled “Strategy, Not Technology, Drives Digital Transformation,” detailing the main drivers of digital transformation projects and identifying key elements of success in this field.

A study titled "The case for digital reinvention," which was published in 2017, has found out that on average, industries were less than 40% digitized at that point in time despite the relatively deep penetration of digital technologies in media, retail, and high tech.

Today, the process of digital transformation is still far from being over. According to the EIB Investment Report 2020-2021, 27% of companies in the United States and 37% of European companies, at the time when the survey was conducted, still hadn’t embraced digital technology. A more recent study by the European Investment Bank, EIB Investment Survey 2022, has shown that 55% of European companies decided to increase their digital transformation efforts in response to the COVID pandemic and economic turbulence caused by it.

Digital transformation market growth

According to Worldwide Digital Transformation Spending Guide, a recently published report by International Data Corporation (IDC), global digital transformation spending should reach $3.4 trillion by 2026 with a five-year compound annual growth rate (CAGR) of 16.3%.

"Despite strong headwinds from global supply chain constraints, soaring inflation, political uncertainty, and an impending recession, investment in digital transformation is expected to remain robust," said Craig Simpson, IDC's senior research manager. "The benefits of investing in digital transformation technology, including automation, data intelligence, operational transparency, and direct support around customer experience, all support targeted areas of business focus to weather the current environment of uncertainty and to make the most of any opportunities in the recovery."

The largest geographic market for digital transformation spending throughout the forecast time interval will be the United States, accounting for nearly 35% of total spending worldwide and surpassing the $1 trillion mark in 2025. Western Europe, with 25% share, will be the second largest region for digital transformation spending. China will see the strongest growth in spending with a five-year CAGR of 18.6%, followed closely by Latin America with a CAGR of 18.2%.

When it comes to digital transformation spending across various industries, discrete and process manufacturing will account for the biggest share, nearly 30% worldwide. The most popular applications for digital transformation technologies throughout these industries will be robotic manufacturing, augmented equipment maintenance and automatization of manufacturing operations.

Businesses in the professional services and retail industries will be the second largest spenders on digital transformation, with back-office support and infrastructure as the most popular applications for digitization projects.

The securities and investment services industry will experience the fastest growth in digital transformation spending with a five-year CAGR of 20.6%, followed closely by banking and healthcare providers with CAGRs of 19.4% and 19.3% respectively.

Latest trends in digital transformation

Digital transformation has been a major business and technology trend for a number of years now. But the world doesn’t stand still and the perception of digital transformation, as well as technologies and solutions that are part of it, continue to evolve and transform.

Here are some of the latest digital transformation trends that are the most relevant today, in the post-COVID era, when the business more than ever before is focused on automating industrial processes, achieving maximum productivity and optimizing the consumption of energy and other resources. According to the Investment Report 2021/2022 done by European Investment Bank, 55% of European companies said that COVID-19 pandemic has increased the demand for digitalization in business circles, and 46% of companies reported that they have grown more digital.

Remote access to enterprise tools and real-time collaboration.

The COVID pandemic has significantly intensified the shift to remote work for businesses in almost every industry and economy sector. Even though enabling the effective remote access to enterprise tools for employees across all teams and business departments has been at the top of the agenda of the majority of organizations in the last couple years as a result of COVID-related lockdowns that restricted the access to workspaces for employees, the transaction to the so-called hybrid work style (when people are able to switch to remote work when needed) is still far from over.

So implementing cloud-based enterprise tools with remote access and real-time collaboration capabilities will continue to be a trend, remaining an important part of digital transformation strategies. That’s one of the reasons why ease of remote access, data sharing and real-time collaboration capabilities are among the top priorities for us at Clarify. Clarify makes it easy to visualize industrial data and access it remotely on web and mobile devices, allowing multiple team members to work on this data simultaneously. Learn more and schedule a live demo with one of Clarify’s experts right now.  

Accelerated growth of direct digital transformation investments.

The volume of direct investments in digital transformation will keep growing in the next couple years. According to the Worldwide Digital Transformation 2022 Predictions study by IDC, digital transformation investment growth rates will accelerate up to 16.5% CAGR for 2022-2024 period. This is an increase of 1% from the 15.5% CAGR for the 2020-2023 time frame. The total amount of investments for 2022-2024 are expected to be $6.3 trillion, which is a $0.9 trillion increase from the 2020-2023 time frame. Digital transformation investments will account for 55% of all ICT investments by the end of 2024.

“For the first time ever, we see that the majority of enterprise organizations (53%) have an enterprise-wide digital transformation strategy, a 42% increase from just two years ago," said Shawn Fitzgerald, research director at IDC.

AI-based automation systems, processes and tools.

Even though AI, ML (machine learning) and AI/ML-powered solutions have been one of the hottest, if not the hottest technological innovation integrated as part of the digital transformation processes, in reality its penetration throughout enterprise IT systems and industrial automation solutions hasn’t been as wide as you would expect. That’s why deploying AI and ML tools and integrating them into operational processes will continue to be a key part of digital transformation strategies in the years to come.

Here are some of AI tools and applications that we expect to be implemented the most frequently as part of digital transformation projects across industries in the next couple years or more.

Focus on sustainability and resilience.

An increased attention to resilience and sustainability in digital transformation projects and initiatives is one of the main outcomes of the COVID-related transformations and economic turbulence that is experienced globally in the first years of the 2020s.

“The operative word that defines the purpose for digital transformation in 2022 is resilience. The pandemic taught enterprises to be prepared for seismic shifts in the market dynamics and consumer needs. Forward-thinking enterprises will focus on the ability to effectively pivot and deal with change with minimal to no impact to internal and external consumers,” said E.G. Nadhan, chief architect at Red Hat. “There will be increased focus on experimentation with configurable parameters to predict enterprise behaviour using simulated environments. And such experimentation will yield more insight into the optimal configurations that are most resilient.”

Implementation of data fabric solutions.

The role of data and the importance of effective data utilization for various goals across all layers of infrastructure will continue to increase for businesses and organizations implementing digital transformation projects. Delivery and processing of data in modern-day enterprise IT environments is enabled by so-called data fabric.

A data fabric is a software architecture approach aimed at facilitating self-service data consumption and simplifying access to various kinds of data within an organization. Gartner describes data fabric as "flexible, resilient integration of data sources across platforms and business users, making data available everywhere it's needed regardless where the data lives.”  

With such a huge variety of communication standards, systems, devices from different vendors, and components that comprise digital factories and enterprise IT systems, the effective implementation and maintenance of data fabric can be a problem. Clarify is a time series data solution that reduces the complexity of turning your enterprise data sources into value. It is easy to integrate with automation systems and databases regardless of what communication protocols they are using. Clarify provides industrial teams with a next-gen level of time series data intelligence, helping to make data points from historians, SCADA and IoT devices useful for the whole workforce, from field workers to data scientists.

Want to learn how to use Clarify as part of your data fabric solution to save on digital transformation costs and achieve a new level of business intelligence? Get in touch.

Digital transformation framework

As George Westerman, a senior lecturer at MIT Sloan School of Management has pointed out, over the last decade or so the process and approaches to digital transformation have evolved.

“In 10 years of researching digital transformation, we have identified ways in which some companies are becoming “digital masters,” while others fall behind. In seeking to become "digital masters," today’s business leaders should prioritize employee experience, customer experience, and operations,” said George Westerman.

This makes a lot of sense to us at Clarify as well. Originally, the digital transformation frameworks were predominantly focused on the technological side of this process, describing IT systems and tools that should be implemented as part of a digital transformation project. Other areas of business operations, on the other hand, very often ended up being overlooked or did not receive as much attention as they should.

Here’s a digital transformation framework suggested by MIT Sloan experts for use today in the 2020s, the so-called post-COVID era.

Digital transformation framework
Source: MIT Sloan experts

Such a structure seems very reasonable and appropriately all-encompassing, so let’s take it as a foundation and talk about each component of this framework in more detail.

Today’s business leaders should prioritize employee experience, customer experience, and operations to become the master of digital transformation.
George Westerman
, senior lecturer at MIT Sloan.

Business model

Overlooking potential business model enhancements is one of the most common mistakes made by organizations implementing digital transformation projects. It means that companies fail to plan for and include new business models and/or existing business model enhancements when implementing digital innovations.

As you can see on the picture, MIT digital transformation experts specify three aspects of potential business model changes: digital enhancements, information-based service extensions, and multi-sided platform businesses.

Digital enhancement describes all additional services and offers a company can add to its business portfolio with implementation of new digital technologies and solutions. The most common and relevant example of a digital enhancement is the creation of an on-demand service based on the company’s internal technology or IT tool developed in-house for their own business purposes.

Multi-sided platform business is a similar concept, but it describes the development of totally new platforms, publicly available or B2B, to leverage the new digital capabilities of the company. The example of such a business model change are web platforms, like Amazon or eBay, created by various retailers and eCommerce companies to allow the access for third-party businesses.

For us at Clarify, the developer of an enterprise data intelligence solution, information-based service extensions are the most interesting way of integrating new digital transformation solutions into the business model.

It implies companies expanding their business product portfolio with new offers powered with the data (time series data in the most cases) collected internally from their enterprise networks of industrial automation devices, machines, sensors, IT systems, customers, employees and other information sources.

Having a proper data fabric system in place, which is a key part of a successful digital transformation process that we will address later, allows a company to create and maintain a huge Big Data archive. The data collected can then be sold in a raw format for third-party companies or processed for various insights and business findings powering a new business service. For example, Michelin, the largest tire manufacturer in the world, collects data from the sensors embedded into its products and then sells it to other businesses, as well as to end-customers.

Every digital transformation is going to begin and end with the customer, and I can see that in the minds of every CEO I talk to.
Marc Benioff
, Salesforce co-CEO and Chairman

Customer experience

Customer experience is also increasingly relevant in the context of modern-day digital transformation projects. It isn’t uncommon for companies focused on integrating new technologies and enhancing their operational processes to forget about the customer experience and the need to put effort in its customization in line with digital transformation changes.

MIT's framework specifies three basic components of enhancing customer experience in the digital transformation process: experience design, customer intelligence, and emotional engagement. Unlike the business model components which can be used separately from one another, the customer experience framework elements are all interconnected and should be utilized in combination with each other. The goal of proper implementation of these elements is to deliver the highest customer experience and “mass customization” for consumers.

Modern-day customer experience design requires time and effort put into mapping the customer journey, coming up with ways to improve it as much as possible, and testing various approaches to find the most suitable one. Finding ways to engage customers emotionally is a part of it.

And all of the above is powered with customer intelligence, enabling the collection of various kinds of customer data, from company website users behavior to customer surveys and demand observations, followed by a real-time analysis performed by a powerful AI-based data intelligence solution.


The evolution of business operations is obviously at the core of the digital transformation process. Core process automation, connected and dynamic operations, and data-driven decision-making are all essential to succeed in it.

When it comes to core processes automation, it can be achieved with a variety of tools and technologies. Naturally, the latest solutions will play a key role in this process. Industrial Internet of Things (IIoT), robotics, augmented reality, machine learning and other innovative tools, when properly implemented and working in combination, enable organizations to automate many workflows and operations that previously required manual and human labor.

The ability to establish all-encompassing connectivity of all these systems is also crucial. The technologies that allow organizations to achieve a new level of industrial connectivity are cloud infrastructure, new types of sensors and embedded systems, as well as 5G, the next generation of cellular network that enables much faster mobile internet connections, supports a high number of devices within one network (over a million devices per square kilometer) and functions with extremely low latency.

Just like with other core elements of the digital transformation framework, the ability to collect and utilize data is central in successful evolution of business operations. In the digital transformation systems, the operational decisions and business analysis are based on real-time data as opposed to reactionary, backward-looking reports typical to the previous generations of industrial technologies. Naturally, the implementation and maintenance of real-time data processing requires organizations to have a strong set of solutions for centralized tracking, organization, and processing of data. New-generation tools such as Clarify allow companies to simplify and automate this process as much as possible, providing an easy to use, flexible, and robust web-based platform for your information intelligence needs. Clarify is a tool that lets you and your team easily share knowledge and explore industrial data — together. Helping you turn data into actual value, every day.

Employee experience

The shift from predominantly technological, centered around an all-encompassing automation and robotization of all operational processes employee experience, is another latest trend of the modern-day digital transformation frameworks. Also described in the Industry 5.0 concept that emerged as a replacement of Industry 4.0, the employee experience component is focused around adding the “human touch” to the machines and utilizing new technologies for better empowerment of human workers, with robotic solutions and smart machines supporting and augmenting human work instead of robots replacing humans.  

The new approach is centered around integrating human workers and machines in manufacturing and other industrial environments, as well as repositioning human workers from assembly line processes and other repetitive tasks to more creative jobs that require problem-solving, experience and intuition.

The future-reading part of this framework component describes the elevation of the role of human talent and its importance to overall success of operations. This includes using innovative digital technologies, such as VR and AR, machine learning and Big Data, to enhance the employee learning process, create more effective learning materials and employee assistance solutions, as well as to minimize errors and improve safety of all operational processes.

Digital platform

Even though customer experience, employee engagement and business models are increasingly important in the course of digital transformation, the technology platform still plays a vital role in enabling it. It lies in the foundation of any digital transformation project, and none of the goals driving them can be achieved without a well-architected, well-structured and advanced technological platform.

The MIT digital transformation experts specify three elements of a digital platform: core, externally-facing and data. This classification is fairly straightforward: “core” stands for the backend solution powering all the layers of organizational IT infrastructure, from ERP systems and other internal software to mobile apps and email servers. The “externally-facing” part of the platform is the frontend or the part of the company's technological infrastructure that is available and visible to customers, business partners and other parties. This includes websites, applications, web portals and other parts of public IT infrastructure.

Naturally, the data is the most fundamental and basic layer of any digital transformation project, underlying all other systems and components of an enterprise technology platform.  A well-structured and properly implemented data platform fuels an organization with the analytical insights and information necessary to enable all the other processes and workflows that are part of the digital transformation framework.

Legacy systems and digital retrofitting

The main problem in implementing the data exchange necessary to digitize industrial and manufacturing operations is lack of digital interfaces and other capabilities supporting this process in outdated legacy equipment.

This is when the concept of digital retrofitting comes in.

Digital retrofitting is a term describing various processes directed at making changes in outdated legacy machines and systems, modernizing them and enabling utilization of this equipment as part of the modern-day digital industrial network.

What are legacy machines and systems?

A legacy system in industrial automation and business environments is basically any machine, computer platform, software solution or other kind of technology that is outdated, difficult to integrate with modern-day solutions and manage.

As we said earlier, legacy systems often end up being one of the biggest barriers in the process of implementing a digital transformation strategy and building a smart factory. This is why digital retrofitting is often viewed as a way to overcome this problem by integrating new IIoT (Industrial Internet of Things) smart devices and sensors into legacy machinery to enable the connection of this equipment to a digital network and extraction of data.

What is IIoT?

IIoT refers to the extended use of IoT in industrial automation solutions, describing the ecosystem of sensors, machines, robotic devices and other instruments connected together, communicating and exchanging data with both internal and external software automation systems. Today, IIoT is widely used across industries, enabling improved productivity, efficiency and analytics with a combination of innovative technologies that are fueling the new generation of industrial automation.

Digital retrofitting solutions

According to a recently published study of legacy manufacturing systems digital retrofitting, based on in-depth analysis of the existing body of knowledge in this area and systematic literature review of retrofitting work within the context of digital transformation and Industry 4.0, there are three basic categories of solutions to retrofitting legacy machines. They are based on interoperability and connectivity between legacy systems and new technologies. These categories are: starter kit solutions, embedded streaming gateway solutions, and IoT hardware-based solutions.

A few words about each category.

Starter kit solutions.

Starter kit solutions (also sometimes called sensor kit solutions) is a legacy retrofitting approach when a third-party provider deploys a connectivity set on top of existing legacy machinery. Such sets typically include sensors, software, hardware, and an integrated data analytics platform. As the authors of another research paper on digital retrofitting explain, starter kit solutions are used to collect data from legacy machinery in order to use it for measuring the overall equipment effectiveness (OEE), its performance, and conduct machine data analysis. This approach does not directly connect the legacy equipment to the IoT network as the data can be processed in a stand-alone manner. However, data from the machine can be integrated into an existing application or data intelligence platform such as Clarify.

Even though starter kit solutions provide a cost-effective, easy, and quick way to retrofit legacy industrial machinery, this method also has multiple limitations related to the power of collected data as it isn’t generated by the actual machine but rather by the third-party sensors integrated in it.

Authors of the legacy retrofitting meta-study note that only 12.5% of total papers used starter kits as a digital retrofitting solution, which is the lowest representation among the three solutions.

Embedded streaming gateway.

Unlike integrated sensor kits, embedded streaming gateways (also known as embedded system update solutions) enable connectivity of legacy machines with the enterprise IoT network by updating the machine's software. The deployment of any additional IoT hardware on top of legacy machinery is not required.

The fact that no hardware installation is required can be viewed as the main benefit of this solution. However, as authors of another digital retrofitting study found out, embedded streaming gateway solution is only achievable if the PLC (programmable logic controller) has sufficient processing power to apply the protocol transformation tasks without affecting the original control functions. So in order for this solution to work, the original legacy system has to have a strong computing processor to support control and connectivity.

IoT hardware-based solutions.

Integration of additional IoT hardware into legacy industrial machinery is the most popular digital retrofitting solution. It extracts original data from legacy machinery and allows the use of new sensors to generate meaningful data.

62.5% of research papers reviewed by the authors of the digital retrofitting meta-study used this approach as it enables fast data collection from legacy machines and newly integrated sensors. The downside of this method is that it is more difficult to implement due to the complexity and multiple types of communication protocols commonly used to manage industrial networks and data.

The majority of digital transformation project fail

A research conducted by McKinsey has shown that the majority of complex, large-scale digital transformation projects end up a failure, not being able to reach their stated goals and going over budget. According to Kevin Permenter, research manager at IDC, the share of digital transformation projects that fail to deliver real business value is even greater — 84%.

Most business leaders are encouraged by digital transformation mistakes  

You would think such high rates of failures should be discouraging to business leadership, but in fact the majority of company top managers perceive the failures as an indispensable part of future success. A survey of UK tech leaders conducted by Citrix has shown that 77% of them see opportunities for success in their past digital transformation failures. 43% of IT decision makers said they have learned from previous experiences of failed digital transformation projects and understand how to use these lessons to their advantage moving forward. Also, 29% of surveyed tech leaders noted that past failure in digitization led to the identification of a new business requirement or focus.

“It is useful to understand that while most IT decision makers have worked on a failed digital transformation program in the past, many recognise the experience was still of personal value to them and represented a significant opportunity in their careers. While no-one will aspire to be associated with failures, it is beneficial to know that IT leaders recognise the learnings they can take from previous projects that didn’t go to plan,” said Mark Sweeney, regional vice-president at Citrix.

What is a failure in digital transformation?

What result can be considered a failure of a digital transformation project is also a bit of an ambiguous question.

Based on the Citrix survey, the most commonly cited factors considered to define a failure of a digital transformation project were:

Pitfalls and challenges of digital transformation

There are multiple reasons why so many digital transformation projects fail. Let’s go through the most common pitfalls and challenges modern-day organizations can face when implementing a digital transformation project.

Recipe to success. How to approach a digital transformation project

The majority of modern-day business leaders and company managers realize that the digital transformation is unavoidable, and the sooner they start working on implementation of such a project, the better it would be in the long run. However, it isn’t uncommon for them to feel hesitant about the way to approach a digital transformation project, wondering how and where they should start, and what digital transformation strategy to utilize.

Here are several key steps to follow in order to maximize your chances of achieving a success in digital transformation.

Plan any digital transformation project as part of a general business transformation strategy.

It is advisable to start with creating a general digital transformation plan that would include all the aspects of business operations. It doesn’t have to be overly detailed, the purpose of such a plan is for the organization to see a larger perspective on things when considering an implementation of any new digital technology.

Include the adoption of new management and organizational practices as part of your digital transformation strategy.

Keep in mind that digital transformation is about the adoption of new work approaches and management practices across all the layers of the organizational structure. This is why it is important to make sure that your digital transformation strategy includes plans to introduce new ways of approaching business operations along with integration of software and hardware solutions.

Focus on business challenges and organizational issues in your digital transformation strategy.

Another aspect to be aware of when working on your general digital transformation plan is that it should focus on the main issues and problems your organization is dealing with, which can be fixed with an introduction of a new technology. This includes business operations and internal workflow challenges as well as customer experience issues.

Adopt the people change management practices.

People change management is an application of structured approach to enabling the people side of digital transformation. People change management is as important as project management in the course of implementing digital transformation initiatives. As part of this process, review how the changes should affect the roles and responsibilities in your company, how new technologies should improve the management and employee learning process, how digital innovations will help company employees and leadership to communicate more efficiently, and so on.

Put effort into building up your partner ecosystem.

Hardly any business nowadays is able to operate as a standalone enterprise, without a network of partners, suppliers and other entities contributing to the smooth business cycle. This is why it makes a lot of sense to think about your partners when planning and adjusting the digital transformation strategy. Build up and cultivate your partner ecosystem with new technologies.

Build a flexible digital platform supporting long-term evolution.

Even though people change management and approach to work processes are important, the technologies still play a fundamental role. Make sure your technology platform, both the hardware and software layers of it, is flexible enough to sustain changes and upgrades over a long-time period without turning into a legacy solution with all the problems associated with it.

Approach digital transformation as a long-term investment.

As a final part of this list: put effort into adopting a healthy approach to funding your digital transformation initiatives. One of the most common mistakes companies make in the course of this journey is expecting a return on investments way too fast. Any digital transformation project and initiative should be perceived as a long-term investment that won’t deliver measurable results immediately after being implemented.

Digital transformation: successes and failures

As we mentioned earlier, most business leaders try to learn from previous experiences of failed digital transformation projects and see opportunities for success in their past failures. Not paying attention to the experience, both positive and negative, of other companies that tried to implement digital transformation projects is one of the mistakes leading to such failures.

Here are some of the most notable examples of both digital transformation successes and the cases when a project went wrong implemented by leading companies in their fields.

Failure: Miller Coors

Miller Coors, an American beer brewing company, started a project to implement the SAP ERP system in 2013. The solution was supposed to simplify and speed up the supply chain workflows, optimize accounting processes, and boost the efficiency of all MC’s business operations. HCL Technologies, India's fourth-largest technology services firm, was hired for the deployment of this project.

Three years later Miller Coors terminated the project and filed a lawsuit against HCL Technologies and its U.S. arm for $100 million, claiming that HCL failed to meet the project deadline. "HCL was unable to adequately staff the project and maintain the project schedule," said the lawsuit. The implementation of ERP solution, which included two types of SAP warehouse management software — Global Available-to-Promise (ATP) and Extended ATP — was never completed.

Clearly, Miller Coors and HCL both made a number of mistakes when working on this project. Here are some of the most notable ones:

Success: ThyssenKrupp Materials Services (TKMS)

An interesting case of a successful digital transformation data-driven digital transformation project was implemented by ThyssenKrupp Materials Services (TKMS), one of the largest materials distributors infrastructural service providers for the B2B sector in the world. TKMS has over 250,000 business customers around the globe and processes more than 2 million orders every year.

In order to be able to effectively retrieve and utilize data for subsequent analysis and other uses, TKMS has developed an AI-based data management and analytics solution named Alfred after the company founder Alfred Krupp. The solution, implemented in 2018, is based on Microsoft’s Azure cloud platform. It is able to process data and automatically generate predictive maintenance recommendations, stock level notifications, suggestions for material substitutions and best transport routes, as well as other kinds of reports and business estimations.

Also, based on real-time data analytics, the Alfred platform recommends TKMS management on operation sites to expand and to close down, helps company employees with key tasks, tracks material needs at individual locations, identifies supplying locations for each customer, and delivers multiple other business benefits to the company.

Failure: Hewlett Packard

Back in 2003, Hewlett Packard, one of the world’s largest manufacturers of personal computers, printers and various hardware components, started a project to implement a single centralized ERP solution (it was the SAP software again) across all departments of its North American division. Initially HP planned to give up the usage of multiple decentralized legacy systems and migrate to a new version of SAP. All potential workflow and technical issues that could occur as a result of this migration were supposed to be fixed in a matter of three weeks.

In reality, however, the team responsible for the project implementation failed to integrate the newly implemented ERP with old systems and operational processes. This led to serious problems with customer order fulfillment. Specifically, more than 20% of servers ordered were never shipped to the customers.

Overall, the failure of the SAP implementation project ended up costing Hewlett Packard’s Enterprise Servers and Storage (ESS) business division around $400 million in lost revenue and $275 million in operating profit.

Here are some of the lessons the HP management learnt from this digital transformation failure:

Success: Bosch

German multinational engineering and technology company Bosch has implemented a large digital transformation project at Bosch Automotive Diesel System (RBCD), its factory located in Wuxi, China.

Bosch was able to significantly improve the efficiency of all operational processes at this factory, which produces high efficiency and low emission diesel engine parts, by implementing tool identification based on RFID (radio-frequency identification), embedding sensors into machinery, and establishing an IIoT network that interconnects all production components and collects sensor data for real-time analysis.

"Having this data connectivity with our machines allows us to react much faster, be more agile with regards to changeovers, our maintenance time, our breakdown reactions, and with these technologies, we can get much greater insights in these pain points, and that has allowed us to maintain the output that's required," said Stuart Brown, director of Technical Function at RBCD. He also noted that the main challenge for factories on the way to digital transformation lies in finding new talents and bringing in new expertise such as higher level IT skills and mathematical knowledge, which are normally absent within these factories.

Failure: Procter & Gamble

In 2012, Procter & Gamble, one of the world’s largest manufacturers of consumer goods, started a company-wide digital transformation project with the aim to become “the most digital company on the planet.” Lacking specific goals and results-focused innovations, the initiative was problematic right from the start. Even though Procter & Gamble didn’t disclose the total amount of losses from this project, it clearly was a multi-million dollar failure, which led to the resignation of the company CEO.

Based on the experience of implementing this failed digital transformation project, Tony Saldanha, former vice-president of Procter & Gamble, wrote a book titled “Why Digital Transformations Fail. The Surprising Disciplines of How to Take Off and Stay Ahead.”

“What I learned over that experience was that failure was seldom because of the technology, but because of change management and how organizations go about rewiring themselves. 90% of success in digital transformation is determined by change management or the culture of the organization and only 10% by the technology deployed,” said Tony Saldanha in an interview.

Success: BAE Systems

A good example of utilizing IoT and visual reality technologies for employee training purposes as part of the digital transformation initiatives comes from BAE Systems, a British multinational arms, security, and aerospace company. BAE Systems developed an augmented reality solution to improve the assembly of complex batteries used in aerospace embedded systems.

In order to achieve their goal, BAE Systems engineers used HoloLens, smart glasses from Microsoft, and Vuforia Studio, a software tool developed by PTC company that enables easy integration of IoT and CAD data collected from industrial systems into scalable augmented reality experiences.

The VR environment designed with Vuforia Studio provided manufacturing facility workers with three-dimensional real-time instructions on battery assembly. 3D modeling and drag-and-drop structure of the VR training environment allowed BAE Systems to increase battery assembly time by 50%, reduce training time by 40%, improve the quality of the end product, and minimize errors.

Failure: General Electric (GE)

General Electric had been one of the biggest promoters of digital transformation back when this concept wasn’t so widely recognized and accepted by the business community. In 2011, GE started a full-scale digital transformation initiative, building its own IIoT platform and integrating digital sensors into its industrial products. In 2013, the IIoT solution was launched under the Predix brand, supported by GE Predictivity Solutions, various software tools and services by GE aimed to assist GE customers with improving asset performance management and business operations.

In 2015, the company launched a new business unit called GE Digital, responsible for maintaining the Predix platform and developing other innovative digital transformation solutions. Despite multi-billion dollar investments and multiple business projects that were supposed to generate profits, GE Digital wasn’t able to meet expectations of GE leadership and shareholders. Poor performance of GE Digital business unit plummeted GE’s stock price and led to the resignation of Jeff Immelt who was the company CEO at the time.

Let’s take a closer look at the main mistakes made by GE and the lessons learnt from the business failure of GE Digital and Predix IIoT platform.

Success: General Electric (AR technology)

Even though General Electric had its share of digital transformation failures, it can still boast a number of successful projects. The implementation of an AR technology at GE’s jet engine manufacturing facility in Cincinnati is one of them.

Executed in collaboration with a company called Upskill that makes augmented reality (AR) software, GE Aviation developed an AR solution, which connects AR glasses that use Upskill’s Skylight software to the jet engine manufacturing equipment, enabling quick and easy practical training of performing the most challenging tasks for company employees.

“Skylight alerts mechanics through the smart glasses when they need to use a torque wrench. Next, when the Wi-Fi-enabled torque wrench starts to apply torque, it shares the information with the Skylight server. Skylight then tells the mechanic whether they are properly tightening and sealing crucial jet engine b-nuts. Skylight will verify the correct value in real time before the mechanic moves on to the next step. This has tremendous potential to minimize errors, cut down on costs and improve product quality. We’ve also seen an increase in productivity and efficiency improvements,” said Ted Robertson, engineering manager at GE Aviation.

Here’s a video showcasing how GE’s AR glasses work in action.

Failure: Ford

In 2016, Ford, one of the largest automobile manufacturers in the world, started its own massive digital transformation project called Ford Smart Mobility. The new project was supposed to include the integration of digital components into Ford vehicles, manufacturing of electric and self-driving cars, a vehicle-sharing program, and a ride-hailing app.

The initiative ended up being problematic on multiple levels, failing to keep up with great business success expectations. Today, after more than six years of development, the Smart Mobility platform still isn’t completed, and key implementation partners have abandoned the project. In 2017, Ford Smart Mobility business unit reported a loss of $300 million. The failure of the Smart Mobility project to deliver business value was one of the main reasons why Ford’s stock value has plummeted more than 40%, leading to Ford CEO Mark Fields being fired that same year.

Here are some of the main reasons why Ford Smart Mobility digital transformation initiative has failed to deliver:

Success: Brioche Pasquier

Brioche Pasquier, France's leading pastry and breadmaker, is a great example of a digital factory implementation by a food manufacturing company. Having 18 production sites around the globe, Brioche Pasquier fully digitized all their industrial processes and interconnected different production sites into a single network through a cloud platform.

Brioche Pasquier uses Vault data management software for training simulations and technical documentation, Autodesk Product Design & Manufacturing collection and Autodesk Inventor for digital design and 3D modeling of the production line. AutoCAD, Navisworks, and Recap tools are used to scan the company's existing sites in 3D to integrate the data into the digital model.

In addition to digitizing the existing facilities, Brioche Pasquier creates virtual simulations of new factories that are being designed to allow people who are less familiar with reading 2D plans to have a visual representation of the future facility.

“This 3D experimentation is something that we don’t want to become passive for its users. In addition to 3D animations, Brioche Pasquier is going to deploy an active experience in which the digital tools—which were initially implemented purely to serve the needs of industrial planning—will be used to train technicians on their work tools. I think it is reasonable to envisage that staff will be provided with these digital capabilities “within five years,” said Freddy Papin, methods and projects coordinator at Brioche Pasquier.

Failure: Revlon

One of the most recent large-scale failed digital transformation cases happened at Revlon, American manufacturer of cosmetics and skin care products. In February of 2018 Revlon began to implement a new ERP system, S/4HANA, which is the latest version of SAP ERP, across its manufacturing facilities. The migration caused multiple business issues, resulting in hindered manufacturing processes, delayed shipments of finished goods, plummeting sales and tainted relationships with customers in the retail sector.  

As a result of the failed ERP implementation project, Revlon’s net loss in the fourth quarter of 2018 alone reached $70.3 million. The company’s stock price fell 6.9% upon the announcement of such devastating financial results.

Here are the main lessons that can be learnt from Revlon’s failure:

Success: Volkswagen

Since 2018, Volkswagen, another major German automotive vehicles manufacturer, has been working in partnership with Microsoft to implement a cloud platform named Volkswagen Automotive Cloud (VW.AC). The solution serves a multitude of purposes within Volkswagen’s facilities, including the development of automated driving (AD) solutions, smart home connectivity services, predictive maintenance of autonomous and electric vehicles, media streaming, personal digital assistant feature, automatic updates of software in embedded systems in cars, etc.

The VW.AC platform is focused on integrating all the digital services and mobility offerings across all Volkswagen’s brands and models. VW.AC’s engineering team, based in Seattle, has enabled data to be exchanged between the vehicles and the cloud through Azure edge services. The cloud connectivity allows Volkswagen to deliver vehicle updates and new features independently of the vehicle hardware.

In February of 2021, Volkswagen announced a new project in collaboration with Microsoft to build a cloud-based Automated Driving Platform (ADP) on Microsoft Azure and leverage its compute and data capabilities to deliver faster and better automated driving experiences.

“We are building the Automated Driving Platform with Microsoft to simplify our developers’ work through one scalable and data-based engineering environment. By combining our expertise in the development of connected driving solutions with Microsoft Azure and its compute, data and AI capabilities, we will accelerate the delivery of safe and comfortable mobility services,” said Dirk Hilgenberg, CEO of the Car.Software Organisation, a business entity established by Volkswagen in 2020 to make the automotive experience safer, more sustainable and more comfortable for people.

Final words

Clearly, digital transformation is a very complex and all-encompassing process that affects all the layers of organizational structure and business processes. The integration of innovative tools and technologies is only a part of it.

Data in its various forms and applications plays a fundamentally important role in enabling the success of a digital transformation initiative. Which is why adopting a powerful and advanced data intelligence platform should be one of the cornerstones of your digital transformation strategy.

Vetted by reputable industry experts, such as Walker Reynolds, Clarify is an affordable and simple data intelligence platform that can augment your data historian or enable you to properly utilize process manufacturing data collected over the years.

Clarify can be easily integrated with the majority of data historians from all vendors, including the ones that only support on-premise deployments, allowing you to combine data from multiple time series databases, visualizing and accessing it in real time. Clarify also simplifies the process of connecting third-party data science tools and applications to your data for advanced analysis.

Regardless of your data management requirements, the Clarify platform is a versatile solution that can be used as a universal intermediary tool, augmenting your data management infrastructure and solving challenges with processing, integrating and visualizing time series data across industrial automation systems and software components.

Want to see the capabilities of the Clarify platform with your own eyes? Take a tour.


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