Deloitte’s 2025 tech value research, fielded in May and June of 2025, surveyed 548 business and technology decision-makers across five industries (consumer; energy, resources, and industrials; financial services; life sciences and health care; and technology, media, and telecommunications). Respondents from both privately held and public organizations had a minimum annual revenue of US$500 million and held roles at the director level or above, including as C-suite executives and board members. The survey draws on longitudinal data that Deloitte’s Center for Integrated Research has maintained since 2023.
Cluster analysis
Deloitte’s Machine Intelligence and Data Science team used 41 variables derived from the survey questions for the cluster analysis. We used a traditional methodology to conduct a two-stage mixed cluster analysis, which is a set of statistical methods for processing data by organizing items into groups (called clusters), based on how strongly associated they are; for example, clustering the workforce by job functions or duties. This technique is semi-supervised, which means we do not begin analysis with any preconceived notion of how many clusters exist in the data. We determine the likely number of clusters through various tests (for example, scree plots derived from the agglomeration schedule of hierarchical clustering). We then ran the k-means clustering algorithm, which requires a set number of clusters to be specified.
The researchers determined the value of ‘k’ in the k-means clustering from the scree plot’s indication of diminishing marginal returns on additional clustering from the hierarchical clustering analysis. Respondents were clustered into four groups: right-tracking the strategy (group 1), tech capability builders (group 2), digital mavens (group 3), and profitability masters (group 4).
Predictive analysis
Deloitte’s Machine Intelligence and Data Science team used several multivariate logistic regression models to analyze probable relationships among different variables and outcomes in Deloitte’s tech value survey.
The model took the survey responses and determined the probability (by percentage) that an independent variable (for example, the number of extensive contributors to realizing an organization’s digital ambition [0 to 12]) might be associated with a given outcome (for example, gaining large or very large value from 100% of technology investments). The team controlled certain influential firmographic factors, tuning the model to provide reliable insight into technology value behaviors and outcomes.
The Deloitte Center for Integrated Research used informal path analysis to examine probabilistic relationships that influence outcomes—controlling what they can’t change—and stacking value drivers to achieve multiplier effects.
Index analysis for tech strategy innovation leaders
This leader index was created by determining how many of the seven tech strategy innovation actions each organization implemented to a “very large extent” or “completely.” Organizations that matched four to seven actions were classified as leaders; those matching two to three actions as followers; and those matching zero to one action as laggards.