Data, Analytics, & AI: how trust produces value


Data, Analytics, & AI: While data analysis plays a key role in the business decision-making process, less than half of top executives are confident they have the right data to make important decisions, according to a survey conducted by MIT SMR Connections with the support of SAS.

The research entitled “Data, Analytics, & AI: How to trust delivers valueFocuses on the degree to which companies have confidence in the data they collect and analyze.

data analytics

The added value of analytics and new technologies, such as artificial intelligence, begins with confidence in them. Companies interested in creating a data-driven culture, where people understand data and leverage advanced analytics to make better decisions, give priority to building trust around the data being collected and stored, and the knowledge they provide. It is this confidence that reinforces the culture they seek.

The global online survey of MIT SMR Connections was conducted with the support of SAS, on behalf of the MIT Sloan Management Review. A total of 2.413 people took part in the survey, 70% of whom are executives, senior executives or members of the business board.

However, research shows that only 15% of respondents use advanced analytics to make business decisions. Less than one in ten uses automated analytics and only 7% applies artificial intelligence and machine learning technologies to decision making.

The "Utility Gap"

Although 76% of respondents said they have increased access to data they find useful - which is not surprising as data volumes are steadily increasing in the context of business digitization - only 43% believe they often have the right data for making appropriate decisions. This "utility gap", as characterized by MIT SMR Connections, reveals a recurrence of the phenomenon, since similar responses had emerged in a similar survey conducted in 2017.

This shows a confidence gap, which is also reflected in the next question. Only 10% of respondents said that they always trusted the data, while 40% (on average) sometimes trusted the data.

Three key conclusions

One of the most important findings of the research is that there is a need for greater commitment and investment in the management and securing of data, which is also the cornerstone of building trust. Particularly important are businesses concerned with security and data protection, critical to maintaining customer confidence in the use of their personal data by companies.

Data security is at the heart of research responses and can be further developed through the application of analytics and artificial intelligence. There is also the opportunity to leverage privacy and GDPR initiatives to build trust, rather than just working as part of compliance processes.

Finally, although adopting an analytics-based culture improves innovation, only a small percentage of respondents are involved in activities that develop employees' knowledge of data analysis.

Finding staff with the right skills is one of the major challenges, so there is still much room for improvement and much effort needs to be made to bridge this ever-widening gap.

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