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How Do Data Skills Affect Firm Productivity: Evidence from Process-driven vs. Innovation-driven Practices

机译:数据技能如何影响公司的生产力:来自过程驱动的证据与创新驱动的实践

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As digitization of various economic and human behaviors become more prevalent, we examine whether data analysis capabilities can help with process- and innovation-oriented firm practices. Using detailed, firm level data on employee data analysis capabilities combined with a survey of organizational practices for 330 large firms, we find that while neither data skills nor process-related practices affect productivity directly, they have a substantial positive interaction. Specifically, firms with process-related practices receive a greater marginal benefit for the presence of or acquisition of data-related skills in their workforce. However, we do not find the same complementarities between data-related skills and innovation-oriented practices and at times the interaction can even be negative. These results are also unique to data-related skills and not IT skills generally. Overall these results highlight the potential tradeoffs of using data analytics at firm, similar to the tradeoffs between exploitation and exploration. We show that value of analytics (at least over our 1987-2007 sample period) is in enabling the use of internal and external data to drive process improvement, but data analytics capability does not immediately translate to greater innovation.
机译:随着各种经济和人类行为的数字化变得更加普遍,我们检查数据分析能力是否可以帮助进程和创新导向的公司实践。使用详细的,在员工数据分析能力上使用详细的,坚定的数据分析能力结合了330个大公司的组织实践调查,我们发现,虽然数据技能和流程相关的实践都没有直接影响生产率,但它们具有实质性的互动。具体而言,与过程有关的实践的公司在其劳动力中存在或收购数据相关技能的情况下获得更大的边际效益。但是,我们在数据相关技能和创新导向的实践之间并没有找到相同的互补性,并且有时互动甚至可以是消极的。这些结果也是与数据相关的技能而不是IT技能的独特。总体而言,这些结果突出了在公司使用数据分析的潜在权衡,类似于剥削与勘探之间的权衡。我们展示了分析的价值(至少在我们的1987-2007采样期间)在使利用内部和外部数据来驱动过程改进,但数据分析能力不会立即转化为更大的创新。

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