Building a data culture at a century-old company

November 25, 2019
SCMP Insights
What does it mean for a news organization to build a culture around data and truly embrace it? At the SCMP, this is a question we have spent significant time considering. In the last few years, we’ve begun taking steps to not just use data, but to also thrive on it as a means for providing readers with high-quality journalism.

What active steps do you think is important for a company to take in order to build a good data culture? (education etc)

Perhaps the most critical component of driving business process efficiency is training, educating and evangelizing why data matters. The story-telling process requires the cross-pollination of data tools and culture to shift decision making from intuition to data-driven. Weekly online editorial meetings, slack, and email alerts for under-performing / over-performing content, daily insight emails summarizing wins/losses, and dynamic TV dashboards all contribute to driving this change. This helps to form rhythms encouraging data reliance on real-time reporting. Key performance indicators (KPIs) enable teams to better track progress and have increased accountability for targets; dozens of training workshops were held to ramp up staff on tools, features and tie data relevance into each individual’s’ day-to-day. As the organization continues to transform, we’re encouraged albeit kept quite busy by the 10x increase of data requests over the past 3 months.
 
While we’re often perceived as a local paper, we have a growing global presence online with over 80% of our traffic coming from outside Hong Kong.

With better tools and more responsive ad-hoc analysis via Tableau, BigQuery and Airflow, 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 that creating a transformative culture starts with investing in our people. The impact was particularly apparent in our data-driven transformation, democratizing data via various tools within the organization, empowering our teams to make smarter decisions. Measuring the impact of those choices gives us the agility to adapt quickly when necessary. With the advent of these initiatives around data storage, centralization, and automation, we’ve seen massive gains in efficiency, growth in our core metrics (traffic, revenue) and a rising tide of excitement, morale and engagement at the South China Morning Post.

Should data drive decisions? What’s the right balance?
While data is not usually the sole variable in driving a decision, it should play a role in most decisions. I prefer to call this 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 which is a big step from the “gut-feeling” or intuition driven decisions that were more the norm previously.

A/B Testing Headlines with Chartbeat

A good example of this is A/B testing headlines in the newsroom. Sometimes editors have differing opinions on which headline works and which doesn’t, the best way 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 US-China trade war content has been a hot topic as of late and several headlines were written in the British style with Trade Row (Row as in a fight or brawl). However, since our audience is largely coming from the US now, Trade War picked up much more traction as Americans generally read “row” as “row, row, row your boat” not as “fight”.

What do you think is the best data culture?
In many ways, all of the things we just talked about. Ideally, an environment where everyone has the knowledge and ability to access to the data they need. Each person across the company should understand the value of data to their team as well as their individual work and be able to have self-serve access to actionable data to execute on their day to day work. Data tools should be largely automated and the data team’s focus should primarily be focused on generating insights, enhancing recommendations, and building tools that employ AI, ML, and algorithms that help drive the business onwards and upwards.

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