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Digital Transformations: Why are they underperforming on objectives and ROI?

Many companies have embarked on digital transformations but how many have been successful? 

In fact, most digital transformations fail. As per Harvard Business Review, the rate of digital transformations failing to meet their original objectives ranges from 70% to 95%, with an average of 87.5%. On the other hand, IDC forecasts digital transformation investments to touch $3.4 trillion by 2026, growing at 16% CAGR. So, what should companies do differently to justify these massive investments on the horizon and improve the ROI?

I had a lively conversation with Anand Santhanam, an industry veteran and the VP / Head of TMT Strategy at Infosys technologies. Anand has led large scale transformations across major markets across the globe. We deliberated on how digital transformations needed to be viewed differently and what drives success.

How are digital transformations fundamentally different?

Businesses have been undergoing cycles of transformation of this scale for a while now. In the early 2000s, companies initiated online transformations to start interacting with their customers on the internet. Subsequently, there was a proliferation of presence into online channels where customers were spending their time. This resulted in a social transformation of internal systems and processes. As customers went mobile, this resulted in another cycle of transformation as companies added mobile as a new capability to engage customers "whenever and wherever". We also saw waves of cloud transformations and automations using RPA.

However, today’s enterprise digital transformation differs from these prior transformations in its comprehensive nature. It goes beyond IT infrastructure or software upgrades and extends to every aspect of the business, including customer experience, operational process changes, application enhancements, and infrastructure adaptations. Digital transformation is data and analytics intensive.  

Why are most digital transformations underperforming on objectives and ROI? 

First, the digital transformations may not sufficiently emphasize all of the trifecta elements of success – experience, effectiveness and efficiency. Touching only front-end while having back-end systems managed through band aids doesn't help in effectiveness and efficiency. Likewise, emphasizing the dual elements of experience and effectiveness can help in a white glove experience for customers and employees, but may not be financially accretive.

Second, digital transformation needs to keep pace with customer expectations and technological advancements. Digital natives do not carry legacy baggage, and as a result are able to adapt much faster to technology changes. Similarly, customer expectations rise and their willingness to pay incremental dollars for the experience is not a given. Anand brought up an example from the telecom sector, where the American Consumer Satisfaction Index (a reputed, long-standing and scientific measure for telecom services) has remained flat over the last 25 years, even though searching, buying, and getting support for services has become easier through technology enablement.

Further, expectation setting up front needs to be pragmatic and specific. While ambition and aspiration are valuable in driving digital transformation, setting goals that are too high without considering the baseline, practicality, and incremental progress can increase the risk of program failure. In some situations, these programs tend to be oversold early on and disillusion soon sets in. Embarking on digital transformation to maintain a status quo on revenues and profits is a sufficient goal as long as the case is robust.

Finally, time is the biggest enemy of these transformations. Even with the right metrics, business case, and governance in place at the beginning of transformation, over one or two years the digital transformation becomes just another program to manage. Rather than a "big bang" approach, it is more sustainable to have a few micro transformations delivering value early on. Three-to-five-year big ticket transformations will soon be history.

What operational interventions can enterprises consider to improve their chances? 

Build engineering talent at scale. This will be a key battleground for enterprises as they seek to continuously manage complex transformations and keep the digital stack evolving. The AI tsunami will also take place in the next two to three years and therefore it is important to shore up / develop this talent.

Shift towards data driven decision making. The ability to translate data / metrics into insights is a skill and is not readily available in the enterprises. It will take some maturity as brownfield businesses move towards this, even if they have invested significantly in the infrastructure and tools.

Organize teams around practical challenges. It is becoming increasingly difficult for teams to focus on experience, effectiveness, and efficiency at the same time. Therefore, it could make sense to split or segment teams with distinct objectives and have a thin governance layer that manages the competing priorities.

Plan for complexity and chaos. While many enterprises are putting in place product simplification programs, it is inevitable that complexity will still exist as bespoke products and solutions are required. Rather than spending resources alone on rooting out sources of complexity, the enterprises should also build muscle for coping complexity – through increased leverage of service partners, cloud infrastructure, and automation.

Develop clear accountability. There is a risk of fragmented ownership as multiple roles emerge in organizations today, such as Chief Innovation Officer, Chief Digital Officer, Chief Data Officer and the more traditional, Chief Information Officer and Chief Technology Officer. It is therefore vitally important to ensure role distinction and clear reporting lines.

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