The Human Side of Data Operations

In 2006 British mathematician Clive Humby coined the phrase “Data is the new oil.” Today, almost 20 years later, this analogy continues to hold true.

The reality though is that, like oil, data is often dirty, messy, and expensive to acquire and process in order to extract and deliver its true value, that is, actionable and timely learnings and insights for better decision-making.

This brings us to the human aspect of this process and, particularly, the people involved and responsible for it.

When bad data flows through the analytical pipelines of an organization, analysts and other end-users often end up having to deal with all the necessary cleaning, prepping, and processing of that data. These are often individuals who should be focused on mining this data for insights and opportunities, rather than being bogged down with all the messiness of the “oil extraction and processing.” As a result, this can lead to frustration, waste of individual and collective precious time, lowered work satisfaction, and potentially even quality of life, as it can pose challenges related to work hours, anxiety, and mental stress.

The root cause, in most cases, sprouts from the absence of operational rigor around data, which can become a case of “cleanup on aisle 4.” If you ever experienced this in the grocery store, you will realize that it is generally not an enjoyable or rewarding situation.

We have often raised the need for operational excellence in data, including sound data governance, as a key ingredient for creating operational efficiency in an organization. This approach not only delivers a tangible (positive) fiscal impact, but also can improve the working conditions for all involved, which can be priceless.

As we experience(d) the Great Resignation and “quiet quitting,” it is important to address the human dynamic of why data operations are of the utmost importance. Creating an efficient and rewarding experience can empower individuals and teams to be more creative in their day-to-day tasks, which can lead to greater productivity, satisfaction, and retention. This translates into improved quality of life for employees and value creation for organizations.

Attracting and maintaining exceptional analytical talent is not an easy task in the currently overly-competitive landscape, so the challenge becomes even greater when 80% of their work time is meant to be dedicated to the frequently endless and grueling process of data cleansing and prepping.

“Dirty data” can erode motivation and, with it, quality of work. Hence, we need to pay greater attention to our people and what impacts their ability to function and derive value/meaning from the tasks they perform; we need to become better at recognizing and effectively addressing potential barriers.

This will directly influence the value your business can get from analytics and create a workforce that will not seek greener pastures elsewhere in order to “escape your toxic oil fields.”

Data may be the new oil but it doesn’t exist without people, our greatest assets. So let’s not ignore what negatively impacts our people while they work to extract and deliver the true value promise of data analytics.

If you haven’t yet, start thinking about the current state of data operations in your company. You will likely realize (quite rapidly) that room for improvement is abound.

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