Six key external forces—economic uncertainty, the COVID-19 pandemic, the labor market, regulatory compliance, geopolitical instability, and supply-chain issues—are pressuring organizations to react, respond, and adapt to changing business conditions. The resulting rising cost of capital will challenge organizations to become more Hyper-Decisive® or risk degraded operations, customer dissatisfaction, and competitive decline (see the Research Insight “Data Leaders Need to Prepare for the Challenges That External Forces Will Pose”).
For the first time in a generation, business leaders need to manage and operate business models that can succeed in the face of rising capital costs. The external forces identified by Dresner Advisory Services are powerful and likely will continue to affect business cycles longer and more intensely than many expect because they have not experienced it in their careers . . . yet.
Leading-edge data leaders with mandates to drive Hyper-Decisive capabilities and competencies appear to be creating and executing on what Dresner Advisory Services identifies as Digital Grade Intelligence™ (DGI) strategies.
A DGI strategy requires organizations to make two simultaneous and coordinated sets of investments to operate hyper-decisively: improved data management and comprehensive analytics capabilities. Data leaders need to oversee investments that build these as competencies until the organization reaches a DGI level that ensures effective operation of its business models. People, process, and technological aspects comprise this competency. Over time, we expect technology and solution providers will package DGI components and platform elements in the course of their normal development of tools and related capabilities.
An organization’s DGI level—as measured by HDMM—correlates with its ability to generate timely, relevant, and actionable insights. DGI depends on analytical data infrastructure (ADI) and operational data infrastructure (ODI), as well as ongoing investments in five foundational priorities: data quality, data governance, data integration, services and talent availability, and internal skills and training.
Data leaders need to recognize the strategic nature of DGI and the leadership role they need to assume to develop DGI within their organizations. DGI flows first from strategic goals, then aligns to business models that enable those goals, and is supported by two key areas: data management and comprehensive analytics. By creating a DGI vision in this way, data leaders will have a framework against which they then can gear the strategies, objectives, approaches, investments, and execution steps necessary to develop a DGI competency. Milestones in that development are noted on a DGI curve, and DGI maturity is measured using HDMM levels.
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