7 sins of digital transformation
4. Expecting IT leaders to know how to lead transformation initiatives
In my recent book, Digital Trailblazer, I advise CIOs to train and mentor leaders to drive transformation initiatives.
4. Expecting IT leaders to know how to lead transformation initiatives
In my recent book, Digital Trailblazer, I advise CIOs to train and mentor leaders to drive transformation initiatives. These leaders often come from IT backgrounds, such as product management, program management, application development, data science, and IT operations. They will have succeeded in managing technology initiatives but may not have the confidence or experience to lead transformation initiatives and deliver outcomes.
When CIOs don’t consider the mentorship, training, and support required to develop these leaders’ confidence to handle the many challenges they will face during transformation initiatives, they are doing their deputies a disservice. How will they learn customer needs, manage through conflicting priorities, align self-organizing teams on vision, oversee change management, or handle detractors?
Growing a leadership team of digital trailblazers is a greater challenge today than during earlier digital transformation waves due to hybrid working, talent shortages, and the wide range of frameworks and best practices increasingly involved in such initiatives. CIOs that don’t drive standard ways of working or governance models may find teams debating which agile frameworks to adopt, what devops tools to focus on, or how to implement design thinking into their roadmaps.
There’s too much at stake for CIOs to limit learning programs to skill development and to leave leadership development for CHROs to oversee. One approach for CIOs is to partner with the CHRO on investing in transformational leadership programs and developing a vision of the enterprise’s future of work.
5. Assuming self-organizing teams will meet security and compliance requirements
Regulatory and security stakes are as high today as they’ve ever been, with enterprises also introducing sustainability goals, diversity objectives, and other ESG requirements that innovation leaders must factor into digital transformation initiatives. Assuming everyone involed in driving innovation is well versed in all the regulatory and security constraints is a sin with considerable ramifications.
Expecting developers on self-organizing agile teams, data scientists, and user experience specialists to have all the required knowledge and best practices can lead to material risks and implementation setbacks. CIOs must ensure security and compliance experts are plugged in and collaborate effectively with all teams involved in digital transformation initiatives.
“Connected and efficient collaboration across the enterprise is foundational to understanding the role of technology change, the use cases, and the right approaches to them,” says Andres Velasquez, technology consulting principal at EY. “Ideally, the organization will focus on institutionalizing ways of working that streamline how the business’s functional, technology, data, and change management teams experiment with and learn from new technologies.”
6. Investing in AI without a strategy or data governance
Generative AI looks to be a foundational priority for CIOs over the next few years, but as Brett Hansen, chief growth officer at Semarchy, says, “like any new technology, a thoughtful, pragmatic approach needs to be applied.”
Thankfully, CIOs have a wealth of experience here, as Joerg Tewes, CEO of Exasol, explains: “Businesses have always needed to transform their massive amounts of data into actionable insights. While AI will, in theory, accelerate the process, the particulars remain the same.”
But debate remains about how much of CIOs’ prior work in delivering data-driven capabilities will translate to the next machine-enhanced era.
“Organizations who think they can leverage artificial intelligence as a bolt-on to their existing digital transformation strategies are doomed to failure,” says Kjell Carlsson, head of data science strategy and evangelism of Domino. “AI is a fundamentally different set of technologies that requires a separate strategy and capabilities.”
And a key facet of that is data management. “Before embarking on a complex digital transformation journey, leaders must assess the viability of their data and implement a comprehensive cleansing and management strategy to ensure data is accurate and complete. Otherwise, AI will base its outputs on incomplete or inaccurate assumptions, leading to potentially disastrous ramifications for the organization,” Hanson says.
Also at issue are organizational issues that could magnify problems as AI becomes increasingly relied on, says Tewes: “To minimize complexity and create synergies, the CIO and CDO must report to the CEO. All three must align business and data-management strategies, complemented by streamlined data and analytics capabilities.”
All too often, digital initiatives don’t do full justice to the underlying data management needs for success, and those requirements — and how they are accomplished — may be changing as AI is increasingly brought on board. Moreover, nonalignment on data strategy, especially as pertains to data governance and where to assign leadership responsibilities, will come back to haunt you if you don’t get it right.
7. Declaring digital transformation a journey without communicating a roadmap
Many CIOs will say, “Digital transformation is a journey,” but do they all readily communicate and update that journey’s roadmap?
Roadmaps give employees a sense of direction, an explanation of purpose, and convey strategic priorities. They often indicate business objectives, planned investments, M&A possibilities, and share a vision of where the journey will lead, along with the stops along the way: target technology types, technologies with planned sunsets, timing, planned integrations, prioritized features, and target delivery timelines.
“One of the more common missteps we see with organizations going through a digital transformation is underestimating the decision fatigue involved,” says Asaf Darash, CEO of Regpack. Here, roadmaps help constrain the types of decisions, when they are needed, and limit the options.
CIOs should beware of developing roadmaps in an ivy tower, however, without getting into the weeds to understand customer needs and stakeholder business objectives. Equally important is spending time with technologists to learn more about modernized architectures, technology platforms, and AI/ML capabilities.
“Effective IT leaders must take an interest in what’s being done at the ground level to drive a successful digital transformation,” says Jeremy Burton, CEO of Observe. “If IT leaders don’t sweat the details and the business impact of these new technologies, such as microservices, continuous delivery, cloud-native infrastructure, and AI, they’ll fall behind.”
Whether digital transformation is a journey or a core organizational competency, CIOs should conduct a learning retrospective with their leaders to avoid repeating past issues and deadly sins.
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