The promise of big data is finding useful correlations between numerous data sets and variables in a short time span and applying the outcomes for business or scientific purposes. But before reaping those benefits we need data. Fortunately there’s plenty of data available for analysis. The Digital Universe study, sponsored by EMC, estimates that in 2013 some 4.4 zettabytes of data were produced by you, me and things, increasingly things. And it is growing fast! According to the same study by 2020 some 44 zettabytes will be generated and the fastest growing data segment is data generated by things, sensors and embedded systems.
Those sensors measure qualities such as motion, orientation and personal or environmental conditions. They are not just found inside smartphones but increasingly in other electronic devices and also in cars, clothing, furniture, housing, you name it. And because to measure is to know, as the saying goes (Kelvin), the data generated by these sensors is increasingly used by people to start quantifying certain aspects of their life usually with the intention to improve the quality of life. We have an insatiable need for data.
But the quantified self is just the beginning. Quantifying yourself to improve your life or productivity is one thing. But what if others start measuring you up with the same sensors? A relatively new phenomenon is called the quantified workplace where, you guessed right, workers are measured in terms of productivity. Since big data analytics helps us to detect new relevant patterns in oceans of data we have started to identify ever more areas where this can be applied. What could be a better idea than measuring, quantifying and monitoring the workforce?
Actually, quantifying the workforce is not a novel idea. In the past many concepts have been designed to improve the quality of the workforce, one of the last probably being the Balanced Scorecard method that was specifically tailored to drive employee performance. In short, quantifying the workforce can have great benefits to an organization. Employees are measured on various aspects of their work or work related life and on detailed performance parameters of their tasks. These aspects and parameters range from how and where their work time is spent on to quantity and/or quality of output. But since performance is also influenced by the way your personal life is organized, it is meaningful to look further than direct work and work related parameters and also include personal circumstances such as family structure, financial situation, hobbies etc. Almost every aspect of a person’s life can influence work performance. It is not hard to see where the inspiration for the quantified toilets hoax comes from.
Once everything is measured, quantified and analyzed, the results can be used in various ways. It can be used to improve sub-performing employees by pointing out how better performing employees have organized work and life. It can be used to re-organize the business process so that the capital can increase its productivity. But data that is constantly analyzed can also be used to generate a profile of the ideal employee. After that the process of recruiting and selecting people for vacancies will be much more effective and efficient as it saves time, money and the chance of getting unproductive employees is limited.
Big Data for HR analytics or talent analytics makes the quantified workforce possible. Evolv is an example of a company that makes good money with HR analytics or people analytics. They label themselves the recognized leader of workforce optimization. In one of their case studies they analyzed the performance of the customer service teams of Xerox and established the ideal employee profile that would improve long term profitability and curb attrition.
Quantifying the workforce makes especially sense for organizations that have large client service teams such as call centers. Call center jobs are the fast food jobs in today’s economy and as such regarded as a cost factor that needs to be quantified, monitored and controlled 24/7. Since these jobs are very limited in scope and complexity they lend themselves to the new digital punch clock. Whether this will work in knowledge intensive sectors remains to be seen. Moreover the link between private and work life is becoming more explicit, increasingly influencing private life.
Business competition in today’s global economy is tough and everything that helps to cut cost or improve revenue is welcome. Analyzing more data in order to achieve this is only natural. For large companies the human capital factor is extremely important as it is the most significant cost factor. It makes sense to further optimize the workforce as new technology develops to quantify more of the work processes. But will it work in the longer term?
In earlier posts on the future of work (here and here and here) The METISiles contemplated what would happen with work as we know it. More specifically, would there be enough jobs for people to make a living and would work still be the life encompassing paradigm for people? With the concept of the quantified workforce we wonder if a measured, quantified and monitored work environment will not drive people out to start a career as an (e)-lancerpreneur. After all what is the fun for employees to be constantly measured, quantified, monitored and judged upon and pushed around. Let’s face it: next to money fun is the primary work motivator. No need to quantify that.