Artificial Intelligence can bring in many positives for workforce management
While Artificial Intelligence and automation technologies is still nascent, the building blocks exist to suggest that Machine Learning could ease the burden of complex analysis, surface insights and trigger actions on behalf of managers.
Workforce management is essentially the art and science of managing people in order to have a productive workforce. While there is a lot of science and methodology around this domain, with many current modern methods evolving from the foundational scientific management techniques propounded by Taylor over a century ago, it still requires the fine art of understanding an individual’s capabilities and balancing human expectations to get the most out of people.
Traditionally, in high empathy countries like India, this has largely been the responsibility of the manager, who balances an organisation’s needs with individual wants and abilities. In short, the manager decides who needs to do what, when and where.
To illustrate this better, if a manager has to take any quick decision, he assesses his immediate environment (learns), utilises his personal understanding of the situation (infers), and takes a judgement call (decides). While the manager is extremely effective in smaller groups due to his understanding of the environment around him, as the group size increases, he can no longer maintain a personal understanding of the information around him purely because of the amount of data that is required to be gathered.
In other words, learning takes far too long and the manager is limited by the amount of information he can retain in his cognitive mind. At this point of time, the manager starts relying on other “trusted sources” who can supplement him with the additional information he needs, and even help him with the different options, and decisions that he needs to take.
Technology has been a great enabler over the last few decades. Earlier, transactional systems allowed automating processes in order to reduce the volume of work involved. They also helped organisations ensure compliance by consistent enforcement of rules. And, of course, while all this information was available easily in the system, the flip side is that it often resulted in a deluge of information, drowning managerial decision-making in the process.
It was to augment managerial decision making that decision support systems were introduced in the early 1970s. These systems gave managers access to more data points to help them come with the right kinds of decision. Over the years, these technologies grew more advanced with more colourful and intuitive reports, providing more facts in a much faster timeframe.
