When the urgency of digital transformation grips an enterprise, IT teams are pulled in multiple directions, cobbling together COEs, taking meetings with vendors previously engaged by the business, and educating those who will listen about the possibilities and limitations of new technologies. That has left IT leaders with little time to see to their own function’s internal transformation. That’s starting to change, at least in one key area of IT service delivery.
A recent performance study by The Hackett Group assessed the progress IT leaders have made in digitizing their functions’ core processes. We measured levels of “digital activity,” which spans the continuum of technology exploration, pilots, current implementation projects and completed deployments. The greatest overall activity level is currently associated with the processes of application development. The app dev column in the heat map below has the most dark-red markers, indicating that more than one in three survey respondents are working with the various technologies to transform development.
Distribution of digital activity levels across IT core processes
Source: Digital Transformation Performance Study, The Hackett Group, 2019
App dev is understandably a prime target for transformation – migration to cloud-based SaaS and rapid development techniques should make the function more agile and responsive, and that will elevate stakeholder perceptions of IT. But it’s not enough. Less than 15% of respondents are applying digital tools to improve IT’s data management, application maintenance, performance management and other processes. Only a holistic approach to service model transformation can create the “Smart IT” function of the future. Key characteristics of that future function include:
- A high percentage of IT services available to the user community through self-service applications that include smart digital assistants and chat bots.
- IT processes, both internal to IT and cross-functional, handled without human intervention through smart-process automation tools such as intelligent agents and software robots.
- Portfolio management governed by demand and supply insights derived from AI-enabled predictive and prescriptive analytics.
- Robust master data management that facilitates access and usability of diverse varieties of data from internal and external sources.
- Business-facing talent that emphasizes data savviness and practical knowledge of artificial intelligence application to solve business problems.
- Responsive function performance management enabled by predictive and predictive analytics, expressed in business-relevant metrics.
- Intelligent cybersecurity systems that leverage AI to learn and adapt to evolving threats.
How many of the above characteristics depend solely or even mainly on application development capability? Not many, really. There’s a far bigger picture here, and IT’s future depends on its leadership to start focusing on it.