The willingness of Britons to stand patiently in line, waiting for their turn, has come to define us as a nation. It could also be a habit that harms our productivity. Today, the sheer volume of data running through businesses is increasing at an exponential rate. Unfortunately, some organisations remain intent on making them stand in line before they can use it.

Too many seem happy to install a data scientist as a gatekeeper to their data. This ensures that large bottlenecks build up when access is required, reducing efficiency as a result. Isn’t it worth asking why some organisations seem more interested in forcing their employees to queue than allowing them to use this data in a meaningful sense?

The benefits of opening up access to data are clear. A recent Economist Intelligence Unit (EIU) study found that organisations which increase the access to data see an improvement in financial performance.

A recent letter from outgoing Groupon CEO Andrew Mason to staff at the struggling company cited ‘a lack of data’ which he admitted had overridden his intuition as to what was best for customers. Today there can be absolutely no excuse for a lack of data causing issues in any way, shape or form. For today’s businesses, the way they deal with data is as much a part of their every day role as it is picking up the phone or writing an email. It’s clear why those who fail to see data’s value can suffer financially as a result.

What businesses must realise is that, when given the appropriate tools, any employee, in any department, is capable of producing data-driven insights from any given data set. By abolishing the queue at the data scientist’s desk, freeing the data and opening it up to everyone through use of data analytic dashboards, organisations can harness the power of their own collective hive to increase performance. Indeed, allowing staff to explore and question their own data to create conversations, questions and insights could not only help to reduce these bottlenecks, but could even help them to change the way they operate forever.

This is not a suggestion that the role of the data scientist is now completely redundant. There’s still a need for data scientists to be able to delve deeper into data, just as long as it’s not at the expense of enabling staff to make their own amazing discoveries. As much as people in Britain enjoy observing proper behavioural etiquette by patiently queuing, and waiting their turn, isn’t it time we re-examined whether or not a queue at a data scientist’s desk is a help or a hindrance?