Digital transformation is synonymous with business transformation. There is a broad recognition of the need to transform through technology, as every company now is a technology company - “Tech is the business, and the business is tech”. And digital transformation is really about acceleration of growth using data, tech and AI. A practical way to get started on this mission is to then cascade it into more meaningful and executable targets for the team – for instance - customer centricity, product design and internal productivity.
Strategy and Organization
The redefinition of Digital Transformation is highlighted in one of the areas of emerging Tech - Generative AI, an area that is driving dividends already. As we look to find productive use cases in AI, customer centricity is where the bulk of the “home run” use cases are playing out, from advising wealth managers, automating software development, and knowledge enabling maintenance experts, salespeople, and contract managers. For example, in the consumer goods industry, computer vision enables applications that convert an in-store picture into next best order recommendations to expand shopping baskets - or provide a leg-up in distribution to check and instantly alert on errors in what’s been put into the package against what was ordered. Similarly, a productivity application for sales operations is returning on capital already with the automation of RFQ responses - traditionally a resource intensive process had meant a smaller aperture of RFQs that could be responded to, now with Generative AI there has been a tenfold increase in responding to proposals. Finally, digital twins and developer productivity is seeing significant returns, for instance - code review used to be a one-day (24 hour) average wait time (which across a large team of developers can be a significant waste) – and is now down to 15 mins with “Generative AI code review as a service”.
In this context, the role of the Technology team is changing from service provider to thought partner. The maturity curve in the industry traditionally goes from digitize to differentiate to disrupt – and leaders are already at a 50 - 40 -10 distribution of work compared to the average 90 - 10 – 0. Additionally operating models are maturing with clarity and coverage of three role models - the CIO, the CTO and Incubation leader - as a good way to simultaneously balance fixing the foundation with changing the business and reimagining the future. Finally, as return on capital has become the key driver of business use cases, identifying discrete value drivers has become even more critical to scaling successfully.
The operating model is also evolving – as technology organizations rebalance between centralized to federated to hybrid operating models. In addition, the strategic balance between outsourcing and insourcing is maturing – some have brought technology back in house with noteworthy results - 70% increase in output, 30% reduction in workforce, with 30% upskilled talent. In many ways the discussion around AI and Digital Transformation is going from cost (reduction) to benefit capture. Correspondingly, “COE”s are being replaced by “Communities of Practice”, with a focus on building reusable assets that can be built upon by other teams.
Culture and Talent
Culture is a primary driver of success in Digital Transformation – transformation is 10% tech and 90% people. And culture starts at the top - companies that are ahead in emerging tech have buy-in from a visionary CEO, and coverage by the board in a transversal way - and this top-down focus is seen as the accelerant to digital transformation.
To be truly disruptive in the age of Generative AI requires a mindset shift from deterministic to probabilistic. Many enterprises have prided themselves on developing products and solutions that always work – but the AI world has to tolerate a probabilistic outcome. A good exercise to shift mindsets is to imagine starting the business from scratch and examining core assumptions – for instance, If Elon Musk were to run my business, what would he do? For some traditional industries like financial services, creating a R&D lab to drive disruption can push more breakthrough innovation than the typical focus on incremental innovation and productivity use cases.
Talent is a critical success factor – and tech innovation/execution is now core to success. As enterprises look to transform their culture, acknowledging generational differences and expectations of the younger workforce is key. “The younger generation is used to working in a digital-native world.” Empowering employees and business units with the right tools and skills is also essential.
Getting to Scale
Transformation is about speed of implementation – “the ideas by themselves don’t matter – what matters is the speed of execution.” And so, technology leaders must be able to balance the ambition to innovate with the capacity to deliver. With increasing regulatory pressures, understanding what freedom of maneuver you have is key. The everyday balance between capacity and the ambition of trying everything is hard to manage. Application sprawl is horribly wasteful and killing/culling is always hard - but critical to do. Many organizations are on a journey of fundamentally rearchitecting their stack in a three phased approach - Stabilizing, Innovating and Transforming. As an example of this approach, one is looking at simplifying their 300 plus application landscape to a more manageable and consolidated set.
Balancing resilience, endurance, and agility is key. Digital Transformation is expected at speed, but the reality of the business is complex and if you go too fast, you might lose your core business. Transformation needs to be seen in the context of the business, with a focus on understanding all products and services and their level of maturity. “IT needs to deeply understand how the business is making money and what the competitive advantage of the company is”. The balance between ideas and execution is key and Lean as a methodology serves as a good framework to approach this, with the focus on balancing the operating processes definitions. Seen with this lens, transformation is really about the speed of idea execution -
One way to drive this transformation at speed is through citizen development - provide a basket of tools and set up guardrails for safety, but in the end use hackathons and dragon dens to fundamentally crowdsource innovation. And in all of this, Generative AI is moving from the amber to the green zone. The key is to be very clear on objectives, of course be very robust around the guardrails and then achieve leapfrog innovation at the edge. This idea of mass innovation with robust guardrails is gaining significant momentum. Notably, “AI can be seen both as a tool and as a teacher”, and this is an important consideration around the “do jobs go away” discussion.
In the end digital is the enabler for business transformation, and digital transformation is really about business strategy, as many corporations are going from selling products to services. Seen in that light digital transformation is then really about D&A change. One company is testing a buddy system with their top 300 leaders - joining a business executive with a digital person as a shadow. This extends across the organization - including senior execs and boards. Redefining Digital Transformation needs to go hand
Executive Technology Board (c) | North America & Europe