What is the right productivity measures: time or outputs? The traditional HR department knows how to accountably measures its activity. The innovative idea behind People Analytics practices is not measurement, but the associations between HR activities and the business KPIs. Productivity is one of the most critical business results, and therefore relevant to projects and products in the domain of People Analytics. However, when I present these basics ideas of People Analytics to HR professionals at all levels, I often hear rejections.

The productivity of knowledge workers

I recall that a global VP of HR once mentioned that since she works in a tech company, she can not possibly hypothesize about the association between HR activities and line of business productivity. I advised her to raise the subject in discussion with R&D leaders in her organization. Like any other business leaders, they must be accountable, and for sure, they measure their productivity. The only question is, How?

However, I do agree with her that measuring the productivity of knowledge workers is more complicated. When we explore employees’ outputs in sales or customer success (for example, in a call center or a field role), outcomes are more straightforward. It’s relatively easy to derive goals and rewards from them. But to measure the productivity of someone who works in a team, in which skills, knowledge, and creativity of the entire team members serve together to reach a goal, is naturally more daunting. And yet, tech organizations do that.

One interesting example was presented this week in an Israeli panel, obviously in a virtual event, by Eldad Maniv, President & COO at Taboola. The panelists discussed “the good, the bad, and the ugly” of measurement in working from home in Covid19 times. But I’ll take only the good from what Maniv shared, as a remarkable example of measuring remote workers. For those of you who are not familiar with Taboola, this company employs about 1400 people in 18 locations worldwide and helps people find relevant content online. They have all worked from home since mid-March. Maniv demonstrated how working from home impacted company measures in R&D, such as Deployed Package and Resolved Tickets.

Time is a common denominator

Clearly, such productivity measures enabled the company to cope with the crisis that severely affected it. And so, we can conclude that R&D organizations know how to measure productivity, and People Analytics leaders can integrate such data into HR data and bring valuable insights. But it also emphasizes the idea that People Analytics practices serve the entire management, particularly Finance. CFOs should use talent data, especially in crisis times, to target the best ways of capturing ROI from people processes and well-being solutions.

 Although Maniv emphasized the outcomes in his discussion, it doesn’t mean that the company neglected to measure the facet of time. Indeed, and like many other case studies about working hours in covid19 times, the company experienced increased working hours during the day. For many reasons, people worked longer hours: the need to juggle between work and parenting duties, the lack of leisure activities outside, the pressure to demonstrate engagement and keep the employment status, and more.

Measuring outcomes is crucial, but time is, and always will be, the common denominator that enables us to objectively sum up the productivity of different roles in the organization. People at different levels of the organization should understand what proportion of working hours contributes to the company outcomes. We don’t spend the entire time creating direct contributions. Sometimes we’re socializing, other times learning, and many other human activities are essential to both individuals and the company as a whole but are not associated with outputs. If this time proportion, in general, is sufficient, we should keep it, otherwise improve it. Within it, we can be more productive and produce even more.

I’m a productivity prodigy!

Personally, I strive to boost my productivity both in outputs and time, and I continuously learn new hacks and use new tools for that. But I must also prevent my own burnout, and there is no one other than me to be in charge of my well-being. Working as self-employed makes me a unique case because I’m both the employer and the employee. However, it emphasizes the mutual responsibility of the employers and the employees. Both should discover the relevant means to enhance productivity without the burnout trap. Engaged employees are considered a blessing for any organization. But even employee engagement has its hazards.

What keeps me productive both in terms of outcomes and time? I want to mention two kinds of digital tools that everyone can embrace this way or another. My outputs as a writer and speaker are my content. While writing these words, I use Grammarly. It keeps my writing correct and precise, and also speeds it up. Grammarly counts each word that I write and reports the number of words checked weekly. It compares my result to previous weeks and other users. Over time, I get better (last week, I was a productivity prodigy!), and I can decide whether to adjust my goals and plans or take a rest.

If you read my blog, you know that it’s hard for me to take a rest. But to be productive over time, I control my calendar in reverence. That’s why I insist people in my network, with whom I’m thrilled to interact by Zoom these days, will use my Calendly.  My friends, clients, students, and colleagues book me when I’m less productive in creating content. It works for me and many others in SMBs and enterprises. For example, if you haven’t done so before, check the Microsoft case study that proves that you get more productive and happier if you wisely book your meeting. Indeed, in that sense, I sit on giant shoulders.

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Productivity and Safety – is there a conflict? This question was raised lately when I completed one-on-one sessions with students in my introductory course “The People Analytics Journey“. The goal of these sessions was to assist students to transform the course materials into an actual analytical project in their organizations. Interestingly, among various business challenges that students raised, Safety was a common concern.

Who owns safety?

Reducing accidents and injuries is a business goal, not an HR goal. In many Israeli organizations, the responsibility for this domain belongs to a safety officer. Therefore, when People Analytics leaders make a hypothesis about employee behaviors and safety outcomes, they must partner with a colleague outside the HR department. But monitoring and changing employee behaviors that contribute to safety is not the entire issue. In some instances, while promoting safety, organizations might unseeingly push their employees to unsafety behavior. A partnership solely with the safety officer will not be sufficient to explore such complex cases.

Safety climate

How an organization pushes its employees to unsafety behavior? Sometimes managers set certain goals that might indirectly encourage the employees to act unsafely or to cut corners with respect to safety procedures. In some organizations, one may find a contradiction between the formal instructions and the way things are done, aka, company culture. To spot such contradictions, I developed many years ago a research tool for organizational safety climate.

Accidents and injuries reduce productivity. However, in the run towards productivity people might forget that. In my safety climate surveys, I offered the management some data and insights about attitudes and behaviors that imply inconsistency between declared procedures and actual expectations of managers. Safety instructions and measures are obviously not enough when the goal of productivity justifies the means of unsafe behavior.

Productivity vs Safety

The most productive organizations are not necessarily the safest ones. Take Amazon for example. This organization uses smart technology to track warehouse worker productivity, i.e., to automatically measure processing times and breaks and generate warnings. Such a tool ensures, efficiently and objectively, that the work gets done. The idea of treating people in such a way may be uncomfortable, to say the least. But if you think about it more deeply, when an employee might be fired due to insufficient productivity, would he cut corners or neglect personal health to gain the expected standards? There are pieces of evidence for injuries related to ruthless quotas in Amazon’s warehouses. The company’s unrelenting surveillance pushed its workers so hard that while hitting their targets, the rate of serious injuries among them was more than double the average for the warehousing industry in the USA.

A delicate balance

This example, based only on the media, is not a statement for or against Amazon. Moreover, my purpose is not to lead you to take a side but to encourage your critical thinking, and hopefully to help executives and HR leaders to take a closer look at practices and consequences.

In competitive environments the importance of productivity raises. But you don’t want to sacrifice safety. So what if productivity tracking could be leveraged to also offer employees safety nudges? Would employees feel differently if tracking them serves their health and well-being? Could such automation offer an intervention that handles the inconsistency between formal safety instruction and actual expectations from employees?

There is a delicate balance that HR professionals must keep in helping business leaders achieve their goals while protecting the interests of employees. Perhaps we need a tool that diminishes the conflict between productivity and safety.

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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!

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