Using Data Analysis & AI to Improve Processes
An effort by software giant Microsoft to collect data on employees found that one division, in particular, suffered from widespread dissatisfaction. Because the group included valued engineers with specialized skills, the company was eager to learn the reasons behind the division’s unhappiness. To uncover the answers, they turned to Artificial Intelligence.
Benefits of Data Analysis
Working closely with a data analytics firm, Microsoft took an in-depth look at the reasons for the dissatisfaction that was rampant within this division. They examined employee calendars and learned that these workers averaged 27 hours per week in meetings. Additionally, they looked at email use and found that employees were spending extended periods of time reviewing and responding to emails. Another discovery? While workers transferring to new divisions performed well, Microsoft’s own internal policies required workers to spend a minimum of 18 months in their current division before being allowed to transfer.
This analysis inspired Microsoft to change a number of internal policies and practices. Included were a new approach to meetings, policies encouraging less frequent email use, and a relaxing of the rules for internal transfers.
Microsoft’s approach sums up the importance of data analysis. And while all that data is great, without the tools to effectively analyze it, its potential will never be realized. That’s where artificial intelligence (AI) comes in.
AI and other digital tools are a great way for organizations looking for a better understanding of employee satisfaction, internal processes, behaviors and other factors that affect job performance – both negatively and positively. The end result? Happier, more productive employees. And that benefits everybody!
There are some potential pitfalls in relying on AI, however. Employees who know they are being monitored may feel like Big Brother is watching them. To counteract this, it’s important to be very transparent when using AI. Explain why you’re collecting data, emphasizing your commitment to positive change versus the erroneous perception that you are trying to catch them in the act of doing something wrong. Once they understand that the AI tools you are using will lead to improvements in the workplace, changes that will benefit the entire organization, they are much more likely to “buy into” the program.
Microsoft was able to use the data gleaned from AI to make changes that helped turn around a key division’s job dissatisfaction. If employed properly, your practice can benefit, as well.