How Data Analytics Can Get You From “Great to Good”

There is no doubt that data analytics has become pervasive among enterprises globally and the benefits are well understood. However, current implementation of data analytics needs to be reexamined. Many enterprises still approach data analytics from a technology perspective to address a plethora of business and management issues. Unfortunately, such approaches can be detrimental especially when the human dimension is overlooked.

Enterprises today employ data analytics to manage and monitor business operations and workforce performance. Decisions are increasingly being made with critical insights from data analytics. However, many managers continue to mistake correlation for causality. Data analytics can identify associations between multiple factors but it cannot determine that a particular factor is the cause or agent for an event (say, a mechanical outage). As such, blind faith in data analytics can be deleterious to enterprises — it can lead to poor decision making and outcomes.

Managers can easily become overly reliant on and overly obsessed with data, trying to measure things to the nth degree despite diminishing returns. Over time, data analytics may displace (to some extent) human experience and judgement in management. Such “management by spreadsheet” or “management through a single pane of glass” practices can easily sap organizational morale as employees engage with so-called “robo-managers”. At times, excessive data can lead to “analysis paralysis” which results in delays in decision making.

Enterprises are increasingly employing analytics and dashboards to measure the performance of their employees. This can create internecine competition within the organization. Interactions can easily become transactional in nature, resulting in cross-collaboration and “esprit de corps” being the obvious casualties. This will be unfortunate because effective, well-functioning organizations are necessary to cope with increasing market competition and emerging disruptive technologies.

There is another insidious threat in the sense that employees may shift their energies inwards — instead of focusing on service excellence and delighting customers, employees spend their energies managing their individual performance dashboards. These employees may even resort to all kinds of subterfuges to safeguard their jobs (for example, I have personally encountered contact centre agents encouraging their customers to rate their service support favourably). Incidentally, middle managers are not exempt from this “dashboard tyranny”. 

The above highlights but a few examples of how poorly thought out data analytics initiatives can bring about undesirable outcomes. It is incumbent on senior leadership teams in enterprises to find the sweet spot where data analytics are judiciously combined with human experience and judgement. Deploying a piece of technology is the easy part, the difficulty lies in anticipating and managing employee responses and reactions. Data analytics should not be treated as a hammer to which every problem resembles a nail. Even leading enterprises risk sliding down from greatness to being merely good if they stumble here.

All enterprises will do well to remember the old adage that “not everything that can be counted counts and not everything that counts can be counted”.