Data-powered enterprises vastly outperform their peers on multiple financial measures, realizing 70% more revenue per employee and driving 22% more profits, according to a new report by the Capgemini Research Institute entitled, “The data-powered enterprise: Why organizations must strengthen their data mastery.”
In this research, Capgemini surveyed technical executives from 500 organizations with at least $1 billion in revenue for the previous financial year.
Data mastery is critical to gain a competitive edge. Only one in six (about 16%) organizations can be categorized as data masters based on several factors of data mastery, including the necessary data tools and technologies required to use and leverage data as well as the appropriate data vision, governance, skills and culture.
While organizations have made headway on data-driven decision making and auctioning, 50% of organizations put data at the heart of decision making.
At a country level, data-driven decision making is more prominent in the United States (77%), Germany (69%), and the United Kingdom (69%). The Indian companies surveyed trail behind: only 34% say that decision-making is entirely data-driven.
In terms of sectors, banking (65%) and insurance (55%) are more data-driven. While progress has been made, a majority (51%) of the time, businesses still use historical data (a reactive decision-making approach), meaning they lose out on a competitive advantage. Only 23% of the time do they use predictive approaches, while 18% of the time they use prescriptive approaches and use an autonomous or self-optimizing approach just 8% of the time.
Data-driven companies enjoy significant financial and business benefits
Data masters enjoy between a 30% to 90% advantage in metrics across customer engagement, top-line benefits, operational efficiency, and cost savings. For instance, Capgemini’s research shows that data masters realize a 19% increase in sales of new products and services compared to 12% for the rest, a 63% improvement.
Gaps exist between perceptions and expectations on data initiatives
Major gaps exist between business executives’ trust of data and the technical executives’ perception of this trust: only 20% of business executives trust the data while 62% of technical executives believe their business users do so. Of the organizations where data is not trusted, the research found that only 24% were able to monetize their data assets in comparison to 83% where it is trusted. Poor data quality is a major contributor to this mistrust: only 27% of business executives are happy with their data quality while 54% of technical executives think their business users are happy with the quality.
While many organizations have started on their data journey, less than 40% are able to harness the power of activated data. In terms of sectors, 54% of banking business leaders agree that harnessing activated data gave them a sustained competitive advantage, compared with only 32% of retail business leaders. Of the enterprises that are considered data masters, 95% have an appointed Chief Data Officer (CDO) and 77% stated that the CDO has been instrumental in realizing the data vision of their organization. Given the prominence of this role, it is perhaps not surprising that 84% of organizations surveyed stated that their CDO reports directly to the CEO, CIO/CTO, or Chief AI Officer. The overall roadmap to harness data needs not only to be addressed not only in the technology department, but up to and including the C-suite.
“Business leaders fundamentally need to look at their data strategy and innovation pathway,” says Zhiwei Jiang, CEO of Insights and Data at Capgemini. “We still don’t have enough data-minded leaders at the C-suite level to drive organizations on the right data journey. There’s a lot more at stake for businesses who don’t act; from operations to sales, customer engagement, revenue and profitability. Those that can monetize data and convert these into assets will thrive. Those that don’t will get left behind. A mindset change is needed – leaders must accept and embrace an agile culture of experimentation if they are to achieve data activation.”