Productivity is not a new theme in my research activity. I mentioned it before in many aspects of my writing. But as I took a retrospective glance into my archive, I realized that when I wrote the term productivity in an article, some questions were still hung out there. Perhaps there are too many questions about People Analytics and Productivity. Let me give you some examples:
What are the methods and tools?
When I started to study the People Analytics leader’s role many years ago, I emphasized the challenge of combining people’s data from different sources to deal with business challenges. A leader must understand all employee data and its impact on business performance. It goes far beyond HR kinds of soft metrics or even KPIs of the HR department. Therefore, the leader must understand not only data management, analytics, statistics, and visualization but rather the professional language of partners within the company, who can assist in implementing actionable insights regarding business performance, including Productivity. But what methods and tools transform business questions about Productivity into actionable insights?
What are the factors of Productivity?
I’ve covered the development of the People Analytics profession for quite a long time. Unfortunately, the more it is discussed, the more myths and misconceptions are found. When I described myths about People Analytics that inhibit professionals’ progress, I described Productivity as a part of the entire value chain that HR practices create. HR leaders are not supposed to use People Analytics to measure the efficiency of HR practices but rather to understand the impact of their practices on the business results. HR processes create workforce capabilities that enable the organization to achieve Productivity and other business goals. People Analytics means HR uses people’s data from their processes to impact the business. However, too many HR leaders still consider their dashboards and KPIs as People Analytics. How can we make more HR leaders study the factors that drive business performance, and what are these factors?
What are the trusted resources?
Upskilling and Reskilling leaders to leverage workforce data to impact the business kept me busy this year. Fortunately, there are excellent textbooks that can help anyone who wants to make progress in this field. I cover the literature, and my People Analytics and HR-Tech reading list, which includes +60 items of Kindle editions, is one of the popular resources to many practitioners, consultants, and academic leaders. But although it offers inspiration, practical guidance, validation for practices, new ideas, innovative tools, and an “open door” to a professional community, only one book on my list included the term productivity in its brief. So, if the reading list is insufficient to study Productivity, where can HR leaders find additional valuable resources to help them explore the topic?
What is the business case for using shiny tools?
I believe that as technology develops, People Analytics leaders will be less involved in analysis and be more responsible for Procurement processes and Ethics. Therefore, these leaders must make sense of the HR-tech industry to be able to match tech solutions to business challenges. But sailing through the rough seas of HR-Tech solutions is not an easy task. My list of People Analytics and HR-tech solutions may be a lighthouse to some of the brave sailors. It includes links to innovation and vendors, sorted into categories based on the employee lifecycle. For example, an interesting class in this list contains about twenty solutions for goal tracking, performance reviews, and Productivity. But do HR managers know how to create the business case and leverage the use of these shiny tools to boost Productivity in the organization?
What is the ethical use of the technology?
Leveraging technology to measure employee behavior that boosts Productivity raises ethical questions. I covered some controversial tech solutions in my monthly review of resources about ethics in People Analytics and AI at work. Obviously, in Covid19 times, there were more headlines on this topic. While employers use more surveillance technologies to monitor work from home, it might be the wrong solution because it signals distrust and reduces intrinsic motivation to perform well, which may undermine the goal of increased Productivity. So how can we monitor behavior ethically and reward employees that contribute to Productivity?
The list goes on and on. I wrote about productivity in interviews, events reviews, and case studies; we can find many questions there, too. I’m not going to cover them all right now. But I believe the message is clear. Productivity is a broad topic that includes business angles, people angles, methodology, technology, ethics, and more. It stands on its own. Therefore, in my future learning groups of People Analytics practitioners, we should cover the different perspectives of this subject while each participant practices actual data from their organization.
We should cover all aspects of Productivity in People Analytics practices: Definitions and measures, workforce phenomena and symptoms, tactics in self-management and collaboration, HR-tech tools, and an ethics debate. Obviously, I should also cover Productivity aspects in blogs – shortly and productively!
