On The Execution Velocity Paradox

It is important to recognize that technology deployment and value creation are distinct phases: deployment— covering acquisition and installation— is defined by smart tool selection and readiness assessments; value creation is defined by a longer and more exacting process that necessitates a transformation of enterprise operating models, including changes in workflows, incentives, and organizational design.

For most industrial enterprises— asset-heavy manufacturers, infrastructure networks, extractive industries, among others— the first phase of digital transformation, acquisition and deployment, is largely complete. Advancements in tooling and favorable deployment economics have driven sustained, substantial capital investment into procuring and integrating these capabilities. The second phase, value creation, is where issues arise.

As tool acquisition, integration, and digital ecosystems scale, execution momentum paradoxically slows— precisely when it is most important. Practitioner and management literature consistently finds that linear project management structures, typical of digital programs, are inadequate for tools that are deeply interdependent with one another and collectively dependent on the enterprise's broader operating model. This problem is compounded in the case of AI and advanced analytics, which are frequently built by teams whose assumptions are misaligned with the operational environments where they are ultimately deployed.

The enterprises best positioned to bridge the gap between digital investment and value realization will be those that address these structural issues, reorient their operating models, and treat execution as a multi-pronged strategic discipline. Evidence points to three key interventions: (i) bidirectional governance models that pair lightweight oversight with autonomous, federated delivery teams; (ii) co-development models where data scientists and delivery teams are embedded within operational teams alongside frontline users for a defined period, fine-tuning technology behavior through direct exposure to operational reality; and (iii) deliberate operating model redesign— embedding digital workflows into standard operating procedures, shifting toward event-driven architecture, and restructuring incentives around cross-functional accountability rather than functional siloes.