Karin Immenroth: Developing Competency In a Data-Driven Business Culture

The advent of readily available data has fostered a new era of fact-based innovations in corporations, where exploring innovations and new systems can be backed up with empirical evidence. And with the disruption caused by COVID-19, there is accelerated adoption in data technology.

So why is it hard for businesses to adopt data as part of their organizational structure?

The biggest obstacles do not stem from the technical side of things; it’s about the culture. In this interview, Chief Data and Analytics Officer for RTL Deutschland Karin Immenroth shares with us how a business needs to transition into a data-driven culture and the approaches that a modern chief data officer (CDO) needs to adopt in today’s digital landscape.

   

The New Landscape of Data Culture

Over the past decade, data has steadily become an influential factor for decision-making processes. Especially in the past year where almost 60% of the global population is constantly online, businesses are looking into data analytics to better understand their customers and employees.

As with the aftereffects of the pandemic and the changing demands of today’s market, Immenroth highlights how the role of the data officer today has changed significantly while pointing out the underlying driving force for data transformation.

 

How has the role of the Chief Data Officers (CDO) changed and what challenges do they face in a post-pandemic market?

Companies didn’t have Chief Data and Analytics Officers ten years ago. That role didn’t exist yet. But because the market is changing dramatically due to progressive digitalization, “Data” as a topic is becoming more and more important. 

The biggest challenge, however, is cultural – it is not enough for a central data area to drive the cultural change, rather the entire company must start working in a data-centric way. 

The DATA Alliance is the central catalyst for RTL Deutschland on its way to becoming a content, tech, and data powerhouse. The pandemic has permanently changed the way we work. 

For us, as the DATA Alliance, the development surrounding “mobile office” is very positive, as it means we can now work across Germany and in a completely flexible way. This helps us find and attract the best talent on the German market.

 

Why are companies still struggling to implement data competency and how has the pandemic affected their hesitancy towards adopting data culture?

We are in the middle of a cultural change, transitioning into a data-driven company. 

RTL Deutschland is a company with over 3,000 employees – a cultural change doesn’t happen overnight. It takes time, and it’s also important to have a few lighthouse projects that carry the topic of “data” into the organization and help spread awareness. 

We must make it easier for our colleagues throughout the company to access data, support them in interpreting data and, of course, show them how to make better decisions based on this data. 

Just like the motto goes, “Use data, be better”. The pandemic has been a positive and driving force behind our cultural change – greater digitization has also brought the processing and implementation of data more broadly into society.

 

Developing and Simplifying Data For Organizations

Without a solid foundation for data culture, businesses will often miss out on the chance to fully utilize the data they’ve collected, or even encounter issues with data consistency or internal processes.

Deloitte reports that only 21% of the global workforce are confident in their data literacy skills. And with 70% of organizations expected to shift to new analytics techniques known as “small data” and “wide data”, businesses that are not data literate will get left behind.

Immenroth dives into how the leadership in RTL Deutschland has steered the company towards developing their analytics sector and advises those who are still trying to find success in building a data competent organization. 

 

What can those in leadership roles do to improve data literacy within their organizations?

We have launched various projects which help our colleagues make better use of data for themselves and their day-to-day work. 

These are, for example, projects like our Reporting Center or our quota tool, Key Vision. We also support various stakeholders in the company by building data products and decision support tools for their businesses. 

At the moment we are particularly active in the marketing, content, and digital sectors. And it’s also crucial for us to continue developing in the analytics sector, as it will enable us to make even better use of the treasure trove that is data analysis.

 

For companies and organizations that are struggling to find success in data, what key metrics and best practices should they focus on to drive the importance of data?

Our experience shows that it makes sense not to overcomplicate the initial steps. Very exciting and useful insights can often be found in simple descriptive data metrics. 

If you then go one step further and use analytics or even machine learning, data science, etc., you’ll often find unexpected results and insights that have been “fleshed out” by the data. 

I recommend a good dose of courage to use unconventional methods and approaches – we have had very positive experiences here and have been very pleasantly surprised on more than one occasion.

 

Starting Small and Establishing Data Competence Centers

In 2021, global big data and business analytics was forecasted to grow to $215 billion while connected IoT devices are expected to create 79.4ZB of data by 2025. 

With global economies adopting data analytics at an accelerated pace, businesses might be tempted to “go big” with investments toward data-driven culture. Immenroth believes that CDOs and organizations should do the opposite instead while building on Data Competence Centers to kickstart their digital transformation.  

 

In the pursuit of a data-driven culture, what pitfalls or common mistakes should CDOs or organizations be aware of?

More doesn’t always mean better. My experience is that it’s best and most sensible to start “small” and then expand gradually. In concrete terms – it is better to always start with a small proof of concept and then decide whether something bigger can emerge from it.

Fail fast and have the courage to make and admit mistakes… This is the best way to learn and then use what you’ve learned in your organization.

 

How would you advise CDOs or data leaders who want to seamlessly integrate competence centers?

My recommendation is to look at where topics related to data are anchored throughout the company. 

Then, based on that, you can build the core for the so-called Competence Center. It is advisable to define central topics and make them the heart of the Competence Center, and it is also fundamentally important that enough “data” ambassadors are distributed throughout the company in the areas correlating to each topic. 

In my opinion, it’s this balance that counts. In any case, our experience shows that a central Data Competence Center can be a very successful catalyst for the transformation of a company.