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Objective and main results

This article reports on a study investigating how data analytics use influences firm agility, and how this effect is moderated by the extent of congruence between data analytics tools and the users, data, and tasks.

Main findings:

The findings show that data analytics use may result in higher firm agility only when the fit between the data analytics tools and people, data, and tasks, is high.

• At the mean level of fit between data analytics tools, data, people, and tasks, there is no significant impact of data analytics use on firm agility.
• At levels of fit below the mean, a negative relation between data analytics use and firm agility is observed.
• As the fit between data analytics tools, data, people, and tasks increases, the results show a positive relation between the use of data analytics and agility.
• The nature of data (i.e. volume, variety, and velocity of data) and analytics tool types are not significantly associated with agility.

The results also show that most companies, even though investing in analytics to various extents, are not in a position to realize the full benefits of data analytics use. Furthermore, having high fit is more important than having high data analytics use without fit.

Summary of practical implications

The study shows that the high levels of fit between data analytics tools, people, tasks, and data represent the glue that enables them to work in tandem, and ultimately yield agility gains through the use of data analytics tools.

When there are low levels of fit, the use of analytics stands to undermine the agility of firms. And when the fit is high, the use of data analytics tools is likely to be fruitful in terms of increasing agility. Managers should therefore ensure proper calibration of organizational resources related to data analytics tools, which is critical for improving organizational agility through the use of data analytics.

When using data analytics, organizations should employ thorough selection processes when acquiring data analytics tools to ensure that the selected tools will most closely match their data, people, and tasks. They can also redesign their tasks to take better advantage of available analytical tools, and managers can initiate training programs or recruit appropriate individuals to improve the people-tools fit.

The concept of fit is dynamic as the needed analyses and the types of data may change over time. Tools that were perfect fit at the point of selection may therefore not remain highly congruent with data, tasks, and people. Fit assessments should for this reason be performed periodically, as well as taking appropriate steps, for improving fit, and not just at the point of selection.

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Tags

Organizational capabilities IT capabilities