Digital transformation churn: Why the digital transformation fail rate is so high

Digital transformation failure and the churn rate

The digitisation of the global economy has had many effects on global enterprises but few are more significant than the overwhelming desire to undergo digital transformation. Modern companies are under tremendous pressure to undergo this process lest they be left in the past, but digital transformation failure rates have become a major problem.

Unfortunately the pressure placed on companies to update their operations has lead to companies rushing to incorporate new technologies without fully understanding how they will improve their daily operations. In the past it has been noted that a whopping 84% of companies fail to achieve digital transformation.

The reason for this astronomical digital transformation failure rate has been attributed to everything from complexity to poor organisational structure. While these factors have their place in explaining the high rate of failure amongst modern enterprises there is a more simple explanation; unrealistic expectations.

Approaching this process with unrealistic expectations is one of the main reasons why digital transformation can fail. Not only are companies are under constant pressure to position themselves as ‘thought leaders’ but there is no universally agreed route to implementation.

The digital transformation package: Cloud services, artificial intelligence and the internet of things

Over the past few years this digital metamorphosis has become synonymous with adopting new technologies. The term itself provides little guidance for CTOs and decision makers when setting the technological agenda in an enterprise. On the other hand, the same few technologies come up time and time again: cloud services, artificial intelligence, big data and the Internet of Things (IoT).

While all of these technologies are useful they aren’t relevant to most organisations. Therein lies the problem which could partly explain the digital transformation failure rate.. No two organisations run the same, and there are no technologies that will mesh with every business process. By looking at each of these technologies individually we see that they aren’t a one-size fits all solution.

Firstly we have cloud services. Cloud services are a popular method of digital transformation because they offer a decentralised way for companies to connect to centralised services that are accessible onsite and remotely. Thus many organizations have been encouraged to create private cloud services to stay with the times.

The problem is that private clouds aren’t relevant to most organisations. As Subbu Allamaraju, Vice President of Technology at Expedia puts it, “unless you’ve at least 200,000 servers in multiple locations, or you’re in specific technology industries like communications, networking, media deliver power etc, you shouldn’t be in the data centre and private cloud business”.

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No less important is that by designing a cloud platform you take on a whole host of software management concerns. As Subbu notes, “resiliency remains a pipe dream” because “most private clouds are not resilient to common infrastructure or software failures”.

Unfortunately the story isn’t much better for big data either. The idea of hoarding data to mine out undiscovered insights has caught out many an unsuspecting decision maker. Many companies spend thousands deploying and maintaining data collection platforms for data that they fail to use. In the UK, the average mid-sized organisation is spending £435,000 a year to hold 1,000 terabytes of data that they know to be useless.

If we look towards artificial intelligence we find more of a mixed bag. Artificial intelligence undoubtedly has some wide use cases for pattern recognition, chatbots and anomaly detection. Yet, artificial intelligence needs to be accompanied with robust data management procedures.

Disconnected vanity projects will not deliver digital transformation, no matter how sexy they may seem

For example, even with AI platforms “30% of business intelligence professionals still spend at least half of their time cleansing and formatting raw data to make it ‘analytics-ready”. It would be a mistake to suggest that all enterprises need to deploy an AI platform and staff business intelligence professionals unless they have key business procedures they want to improve.

Digital Transformation failures: The tightrope between ambitions and realistic expectations

Given all the positive press that these technologies enjoy it is no surprise that business owners jump at the opportunity to be a thought leader. These technologies attract a lot of attention and brands like to position themselves as being forward thinking. Pursuing digital transformations looking to shoehorn in new technologies because a company in the FTSE 100 implemented it is a terrible recipe, one that is ripe for digital transformation failure.

As Stephan Pretorius, UK Group CEO and Global CTO suggests, “digital transformation is not a project or an intervention. It is an ongoing process of better understanding how technology impacts the relationship of brands with consumers”. In other words, “disconnected vanity projects will not deliver digital transformation, no matter how sexy they may seem”.

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Those organisations that want to modernise and incorporate AI, big data, IoT or cloud services regardless of their suitability are making a big mistake. Getting caught up in the hype is an easy mistake to make because enterprises are forced to walk a tightrope between balancing their ambitions with realistic expectations.

Without the necessary ambition it is unlikely that any digital transformation initiatives could fail at the outset. However, if this ambition strays too far from targeted goals and expectations, there is the risk of implementing technology that doesn’t integrate smoothly.

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Ensuring digital transformation doesn’t fail

When 35% of executives have cited lack of a clear transformation strategy as one of the biggest roadblocks in their trip towards digital transformation, there is clearly a problem with planning and execution. The only way to combat this is to analyse the suitability of technology on a true-case by case basis.

Digital transformations are not something to be taken lightly and can be very costly if they don’t deliver substantial return on investment. As such it is time we recognised that digital transformation isn’t a one-size fits all solution but a process. Modern enterprises shouldn’t be looking to dabble in technologies in AI just because it is the in thing to do. The wider conversation in this area would be much more productive if we disregarded the idea digital transformation is a necessity for every company. It isn’t. While there may be many companies that benefit from technologies like AI and big data there just as many that don’t. Being skeptical of the hype around certain technologies and setting targeted goals will give enterprises the best chance of successful deployment.

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