Strategic advice & alerts to leverage data analytics & new technologies

Leverage data and the technologies that generate it, from ML, IA, NLP, blockchain, IoT, and emerging tech; to data science, data visualization, predictive modeling; to data quality, data governance, and data architecture.

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This Executive Report is an update to a 2015 edition that introduced a process for deriving enterprise architecture (EA) value metrics that align with the value drivers particular to an organization — those important to both the core business capabilities of the organization as well as its key stakeholders. It contains refinements to the process as well as additional information and perspectives from the field regarding the strategic use of value metrics that will, over time, allow the EA organization to be viewed as a strategic resource/partner and eventually earn a seat at the strategic planning table.
This Executive Summary accompanies an update to a 2015 Executive Report that introduced a process for deriving enterprise architecture (EA) value metrics that align with the value drivers particular to an organization — those important to both the core business capabilities of the organization as well as its key stakeholders. It contains refinements to the process as well as additional information and perspectives from the field regarding the strategic use of value metrics that will, over time, allow the EA organization to be viewed as a strategic resource/partner and eventually earn a seat at the strategic planning table.
Confidential computing is a promising technology that seeks to solve one of the remaining impediments to greater cloud computing adoption and data security in general: how to protect data during processing. It also offers exciting possibilities for organizations to develop new collaborative applications.
During the past year, the application of technology to well-bounded problems proved its strengths in the impressively rapid R&D that delivered multiple vaccines in a previously unheard of time frame. The challenging transition from R&D and production to distribution has, however, once again proven that project and change management issues are often more challenging than product development.
No human could possibly read everything, but a machine can. The best you can do with old-fashioned methods is to hire experts to sample a subset of the relevant data and produce written market insight reports. While these studies can be extremely useful, the resulting analysis is constrained by the amount of data sampled. Many companies already use forms of automation to sort through the data with machines, but, in the end, humans still have to read the data and decide what it means.

As has been our tradition for the last several years, we’ve compiled the five most intriguing articles published by the Data Analytics & Digital Technologies practice this year for today’s Advisor. How did we come up with this list? We chose the articles that garnered the most feedback from Cutter Members and clients and those that created controversy among Cutter Senior Consultants and Fellows.

The authors share part of a research project that seeks to “demystify digital transformation” through findings from interviews with senior leaders at seven firms undergoing digital transformation in a variety of industries. One of their major initial findings is the degree to which senior leaders’ digital mindsets determine the success or failure of these initiatives. The authors highlight the importance of an enterprise-wide view, explaining why a project-by-project approach rarely produces true or lasting digital transformation.
Timothy Chiu discusses how data and digital architectures require improved application security and how the new security framework from the US National Institute of Standards and Technology (NIST) endorses this view. As more and more organizations move rapidly to the cloud, he argues, applications and their associated data are increasingly at risk. With support­ing data from multiple sources, Chiu frames the risks through examples of data breaches across multiple industries and geographies. Fortunately, he says, NIST is on the case.