3 Reasons Why Digital Transformation Fails

Why digital transformation fails

With the massive leaps in technology over the last 10 years, many industries are going through a transformation that will see almost every business become digital natives.

Becoming a digital native means applying and adopting the philosophies, engagement processes and the fundamental tools that our current technological infrastructure offers the world of business, politics, healthcare and the sciences in order to become far more efficient.

Efficient at what, exactly?

It’s about becoming more efficient in three crucial areas: speed, adaptation and simplicity.

This means becoming faster than everyone else and always remaining ahead of the competition; adapting to new infrastructures, perspectives and processes, while aligning with the vision of a progressive future; and finding ease in simplifying mundane, as well as complex tasks and operations that are in dire need of retrofitting.

While this sounds amazing and like something that we should all be looking forward to, digital transformation still fails. So what is it that’s preventing the quick, wide-spread adoption of AI and digital transformation?

why does digital transformation fail? 

There are a number of reasons why this impressive technology isn’t getting the respect and acknowledgement that it deserves.

These reasons can be categorised into three separate points:

  • Fear/lack of understanding;
  • Outdated (legacy) infrastructures and ideologies;
  • A lack of resources/support structures.

Fear and Misunderstanding

One of the biggest issues with embracing digital transformation is the fear and confusion that this new technology brings. Whether a bank, an airline, or a retail chain, reluctance stems from the lack of knowledge surrounding this new technology.

People are inherently fearful of change, especially if the outcomes are unknown and unpredictable.

Certain operations, procedures and processes have been in place for decades, because they’ve worked. So introducing a whole new approach to dealing with these outdated, and often mechanical, ways of running organisations will certainly be fear-inducing. 

The majority of people have unrealistic connotations of what artificial intelligence, machine learning and modern technology is; making applications, building websites and using the internet isn’t what digital transformation entails – it goes much deeper than that. 

Popular culture (movies, television and music) has also left us with the false impression that AI will develop to a point of relying on its own consciousness; one that is malevolent and a threat to the human race.

However, this couldn’t be further from the truth. 

While this technology certainly is powerful and goes far beyond human intelligence, it is made for people, by people. Humans ultimately wield the power to use this technology in order to problem-solve and find solutions to issues, struggles and challenges that we face in both business and life; it’s simply a tool that can process, analyse and output data way better than humans ever could. And it’s all for our benefit.

Outdated (Legacy) Infrastructures and Ideologies

With legacy thinking and infrastructure having set the standard for decades, we’re used to operations and processes that work for us. Going against that means changing an obstinate viewpoint of reality and coming to terms with a complete shift in paradigm. 

The narrative of “if it works, why change it?” persists in far too many industries and becomes a huge barrier to embracing the new infrastructures and philosophies that come with contemporary technology. 

Manual procedures, methods and approaches simply don’t match-up to the processing power that automation and AI have. Indeed, the traditional approach to doing things works and has worked for a long time, but it’s nowhere near perfect. 

And because old infrastructures exist, it becomes difficult to extract data effectively and get past the security and red tape; these infrastructures are often complex and don’t mix well with other technology and without the support of corporate governance, not much can be done to speed up it’s adoption.  

We need to understand that most of the methods we use are outdated and antiquated. Leaving behind old thought and embracing this new technology for faster and better solutions, processes and procedures is critical to success in this day and age.

Lack of Resources and Support Structures

While money is certainly an obstacle to adoption, a major issue lies in the unwillingness to embrace change. C-suite executives, along with other seasoned professionals, make it difficult to change processes and policies.

The culture that exists has been around for a long time. Approaches that have made companies successful are difficult to let go of. IT veterans that have built legacy databases and infrastructures are reluctant to see their hard work and efforts scrapped or changed. To top it off, it isn’t necessarily easy to find new talent to handle and manage this new technology.

Internal resistance is a huge problem when it comes to the implementation of digital transformation and creates unnecessary obstacles that often see it fail.

And with a lack of resources – in the form of funding, talent and infrastructures – a large portion of organisations struggle to transform their existing systems in an effective way. 

Digital transformation fails due to many reasons and it’s almost entirely up to business leaders and the c-suite to learn and progress their organisations in ways that will properly embrace the benefits and opportunities that come with AI. 

The possibilities are seemingly endless and the sooner every industry realises this, the better our world will become.  

More on AI, Machine Learning, Chatbots over Here!   

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Michael Cowen
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Michael Cowen

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Michael Cowen is the CEO of teraflow.ai and co-hosts the Making AI Podcast. Michael is the Ex Deloitte Digital Director and Mindshare Digital Partner. He focuses on the way business models and culture shift and change to change the way people that they work in an AI-enabled organisation.

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