Data, Analytics, & AI: how trust produces value

Data, Analytics, & AI:  Ενώ η ανάλυση των δεδομένων διαδραματίζει καθοριστικό ρόλο στη λήψης επιχειρηματικών αποφάσεων, λιγότερο από τα μισά ανώτατα στελέχη είναι σίγουροι ότι έχουν τα σωστά δεδομένα για να λάβουν σημαντικές αποφάσεις, σύμφωνα με έρευνα που διεξήχθη από το MIT SMR 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 towards managing and securing data, which is also the cornerstone for building trust. Particularly important are the companies that deal with security and of data, elements critical to maintaining customer trust in companies' use of their personal data.

Data security is at the heart of research responses and has the potential to be further developed through analytics and artificial intelligence. There is also an opportunity to take advantage of the privacy and GDPR confidence-building initiatives to build trust, rather than just being 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 most important pre, therefore there is still much room for improvement and several efforts must be made to bridge this ever-growing gap.

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