It seems like every business is struggling with the concept of transformation. Large incumbents are trying to keep pace with digital upstarts, and even digital native companies born as disruptors…
Research shows that businesses using data-driven decision-making, predictive analytics, and big data are more competitive and have higher returns than businesses that don’t. Because of this, the most ambitious companies are engaged in an arms race of sorts to obtain more data, from both customers and their own employees. But gathering information from the latter group in particular can be tricky. So how should companies collect valuable data about time use, activities, and relationships at work, while also respecting their employees’ boundaries and personal information?
In helping our customers adopt people analytics at their own companies, we’ve worked directly with legal teams from large companies around the world, including over a dozen in the Fortune 500. We’ve seen a wide range of cultures, processes, and attitudes about employee privacy, and learned that in every case there are seven key points that need to be addressed for any internal predictive analytics initiative to be successful:
This article was published on HARVARD BUSINESS REVIEW