Sidestep High Failure Rates in Digital Transformation

Smart city and communication network concept

Adopting digital transformation (DX) leads to significant growth for organizations when compared to their lagging peers, according to McKinsey and Company research. McKinsey suggests that there are five approaches to plan for and incorporate into any digital transformation (DX) project: ensuring lean process design, digitizing the customer experience, selective process outsourcing, incorporating analytics to aid with decision-making and using intelligent automation for non-core human tasks.

These five approaches make sense; however, there are many speed bumps along the way that will amplify the risks of any DX undertaking. The reality is that few organizations are ready to attempt such an endeavor. The obstacles are enormous. Mapping and documenting processes, culture and change management, access to data science skills, access to the data itself, and managing many moving parts of an implementation are just a few of the complex tasks that an organization must tackle.

As a result, these capability problems have led to a change of thinking both on the part of enterprises and by the organizations that provide services to them. It is critical to examine the key challenges along with potential strategies to resolve these problems.

Addressing the Talent/Skills Shortage

The talent/skills shortage is one key enterprise challenge cited by just about every digital transformation study conducted. According to McKinsey research, 24% cited lack of digital talent as significant; 39% of respondents to a recent Riverbed Technologies survey cited the same problem. The logical remedy—at least near-term—is the use of contractors and consultants as “staff augmentation” to enable organizations to progress with their digital transformation projects while keeping their costs reasonable.

Accessing Good Data

Adequate data is also necessary to power these new cognitive automation tools. For machine learning to work well by providing unattended automation and insights into data, organizations need the ability to curate large data sets. These data sets need to be free from bias and statistically representative. There is initial anecdotal evidence that the use of machine learning will highlight a new problem of the data rich versus the data poor. 

Dealing with Budget Constraints

Slightly more than 50% of organizations are constrained by limited budgets when it comes to implementation of DX strategies, according to the Riverbed Technologies study. Novel approaches are under consideration to benefit from DX while removing the upfront costs. One is to outsource the process to a service provider that has significant experience applying automation capabilities to an end-to-end process. Increasingly, these services are no longer based upon the traditional “lift and shift” Full-Time Equivalent (FTE) model. Instead, they are based upon output or outcomes. Other budget-constrained organizations are starting with processes that are the most expensive, but less strategic and more contained. 

Process Complexity and Visibility

Approximately 40% of respondents in the Riverbed study indicated that a key constraint is the complexity of existing processes as well as the inability to “see” the process end-to-end. This is most commonly attributed to cross-department workflows. It stands to reason that many organizations developed processes over time and without an overarching strategy. Therefore, the effort to reduce complexity and visibility into each step of the process was sacrificed at the altar of “just get it done” tactics.

Most large enterprises consider digital transformation a must, but sidestepping the high failure rates of DX projects will continue to be a challenge. So developing that overarching strategy, attending to the key approaches that are essential to every DX project and implementing incrementally to see what works (and what does not) will go a long ways toward making your projects fail-safe. However, while simple rules can be used to create a generalized framework suitable for any organization to help guide your project, the specific needs and “personality” of each organization must inform how each project is really implemented. 

>>For more insight on this topic, check out Greg's article in Future of Sourcing on how to make your digital transformation project a success.

Greg Council, Vice President of Marketing and Product Management

Greg Council is Vice President of Marketing and Product Management at Parascript. Greg has over 20 years of experience in solution development and marketing within the information management market. This includes search, content management and data capture for both on-premise solutions and SaaS.