What does it mean for a news organisation to build a culture around data and truly embrace it?

At the South China Morning Post (SCMP), this is a question we spent significant time considering. In the last few years, we’ve begun taking steps to not just use data but thrive on it as a means for providing readers with high-quality journalism. We have seen first-hand that relevant data can be used to improve the way a newsroom works and thinks.

There are several active steps that are important for a company to take to build a good data culture. Perhaps the most critical component of driving business process efficiency is training, educating, and evangelising why data matters. The storytelling process requires cross-pollination of data tools and culture to shift decision-making from intuition to data-driven. Weekly online editorial meetings, Slack, e-mail alerts for under-performing/over-performing content, daily insight e-mails summarising wins and losses, and dynamic TV dashboards all contribute to driving this change. This helps form rhythms encouraging data reliance on real-time reporting.

Key performance indicators (KPIs) enable teams to better track progress and increase accountability for targets. We held dozens of training workshops to ramp up staff on tools, features, and information on how to tie data relevance into each individual’s day-to-day work. As the organisation continues to transform, we’re encouraged albeit kept quite busy by the ten-fold increase in data requests over the past three months.

While we’re often perceived as a local newspaper, we have a growing global presence online with more than 94% of our traffic coming from outside Hong Kong. With better tools and more responsive ad-hoc analysis, we’re building a stronger data culture at SCMP, empowering business leaders and managers to access real-time data and make more powerful, data-informed decisions.

We believe creating a transformative culture starts with investing in our people. The impact was particularly apparent in our data-driven transformation, democratising data via various tools within the organisation and empowering our teams to make smarter decisions. Measuring the impact of those choices gives us the ability to adapt quickly when necessary.

With the advent of these initiatives around data storage, centralisation, and automation, we’ve seen massive gains in efficiency, growth in our core metrics like traffic and revenue, and a rising tide of excitement, morale, and engagement at the SCMP.

While data is not usually the sole variable in driving a decision, it should play a role in most decisions. I prefer to call these data-informed decisions. Throughout the course of the past two years, we’ve seen an increasing trend in business leaders asking for and considering the data piece before making decisions. This is a big step from the “gut feeling” or intuition-driven decisions that were previously the norm.

A good example of this is A/B testing of headlines in the newsroom. Sometimes editors have differing opinions on which headline works and which doesn’t. The best way to decide is to put it in front of our users and see which one they click on the most. Then, regardless of which one we might like, we know what works and what doesn’t.

The U.S.-China trade war content has been a hot topic as of late and several headlines were written in the British style with the words “trade row” (“row,” as in a fight or brawl). However, since our audience is largely coming from the United States now, “trade war” picked up much more traction as Americans generally read “row” as in to “row a boat” not as “fight.”

The best data culture is, in many ways, all of the things we just talked about. Ideally, it’s an environment where everyone has the knowledge and ability to access the data they need. All people across the company should understand the value of data in their teams as well as their individual work. They should also have access to actionable data to execute on their day-to-day work.

Data tools should be largely automated. The data team’s focus should primarily be focused on generating insights, enhancing recommendations, and building tools that employ Artificial Intelligence, Machine Learning, and algorithms that help drive business onward and upward.

While we recognise there is still plenty of work to be done to become a data-first organisation, we see a clear path toward building this culture into our future as a step in the right direction.

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