BCG’s Proprietary Research
BCG’s leading position as a strategic partner in delivering digital transformations with our clients gives us a unique ability to provide insights on transformation success. We undertook a systematic and forensic analysis of 70 BCG-supported digital transformations. We supplemented this analysis with external research among 825 executives who have undertaken digital transformations in their companies. The combined data set covers all geographies, industry sectors, and types of digital transformation.
We conducted a detailed survey asking all participants about the goals of their transformation, how successful it has been, and the degree to which each of more than 35 potential influencing factors were in place. (See the exhibit.) These factors covered:
- Leadership commitment
- Strategy and approach taken
- Governance
- Financial and people resourcing
- Starting capabilities (such as technology and agile)
We then used the resulting data set to empirically analyze which combination of factors, if performed sufficiently well, had the biggest impact on success and which combination differentiated successful transformations from those that were less successful. The six critical success factors emerged from this analysis.
We defined the success of a transformation on a scale of 1 to 10 using a combined success score. This score was based on a set of survey responses that included the percentage of predetermined targets met and value achieved, the percentage of targets and value met on time, the success relative to other transformations, and the success relative to management’s aspirations for sustainable change.
To determine the most effective combination of critical success factors, we used a multivariate analysis on the full list of potential influencing factors. We employed a multivariate linear regression approach, run using the “R” coding language. All input factors were included in the initial regression analysis, with the combined success score being the target or output variable. R2 and adjusted R2 values for this initial regression analysis were measured, as well as the coefficients and standard errors for each input factor. This analysis determined that this particular combination and concentration of factors explained more of the variance of the data points than any other combination. For example, adding the sixth factor increased the likelihood of success significantly (by about 20%) while adding a seventh factor had a negligible additional impact. Thus, we can say confidently that our combination of the six success factors best determines the success of a digital transformation.