How do You Measure Productivity in Your Teams?

The conventional method used to measure productivity in manufacturing companies is output divided by input. This method is ideal for the manufacturing industry, since workers focus on one task for a specified number of hours, thus making it easier to set a benchmark for the measurement of employee input. In the knowledge economy, it has been difficult to track the quality of effort. Hence, most companies focus only on capturing output (e.g. tasks completed, tickets closed etc.), then try to set incremental improvement goals based on what “feels reasonable.”

The reason the technique worked well for companies in the manufacturing industry is that they compared both output and hours put in. Just using one parameter (effort or output) is not adequate. For knowledge workers, effort is usually estimated as time spent in the office. This is not very accurate, since for a number of reasons, the time and quality of effort tends to vary widely between employees. Compared with workers in the manufacturing industry, knowledge workers have many different tasks that they work on - some important, few critical and others that are neither. They find it difficult to prioritize, have to attend meetings and unscheduled discussions and calls, and are exposed to myriad distractions - be it personal phone calls, browsing, and those persistent whatsapp pings.

Similarly, output is not always easy to track. A research paper by the U.S. Army titled “Evaluating Knowledge Worker Productivity” states that not all production can be quantified. Cases in which the final product is developed by a number of employees (such as software development or testing teams) present a particularly intractable problem. This has been attributed to difficulties in measuring the input of individual employees within the teams.

Workers in manufacturing companies also work in teams, but since each of them is performing a single operation, it is easier to measure the individual contribution of each team member. This is not the case in the knowledge economy since collaboration between each team is a major portion of the input effort. Measuring tasks is possible, but how does one quantify the collaboration efforts of knowledge workers, especially those in the software development industry?

The various methods of measuring employee productivity used in software development, IT services and the BPO industry all focus on output, relegating the time and effort put in by workers to the background. It is equally important to obtain, collate and analyze employee and team effort. Only then will managers and the business be able to not only measure true productivity but also to improve it.

To get a true measure of productivity for knowledge workers, managers must take into account the input effort (time on different tasks, meetings, emails) and ensure that it is both adequate and with the right emphasis to achieve the best possible outcome. However, acquiring this effort data is a major problem. The only method that exists is the Timesheet, which is highly subjective and frankly, an anachronism in today's high technology world. Seemingly, obtaining a measure of productivity for work in the knowledge economy is all but impossible.

The key to solving this problem is to automatically capture employee activity data, which can be done by deploying automated effort tracking tools within the workflow processes. These tools give companies the ability to capture effort accurately and provide them with analytics at both user and team level. It helps them measure employee engagement and team utilization levels, rather than relying on subjective inputs from timesheets and manager perceptions about how busy their teams are. When combined with output metrics available with the teams, it becomes possible to have a 360 degree measure of productivity. Managers can use team level patterns to decide if workload has been allocated fairly across their teams, while senior execs can take informed staffing decisions based on utilization trends. Similarly, each employee effectively has a 'mirror' to their own work, and can find ways to improve their performance while potentially optimizing their time in office instead of staying late or carrying work home.

You can check here the People Analytics Solutions from Sapience to map and increase the productivity of your organisation