We recently brought together industry experts to discuss the integration of data strategy in today's business world. The panel included Jordan Morrow, founder of BoDiData; Catherine King, Global Head of Brand at Orbition; Ed Sant’Anna, Head of Products at Coio; and Pete Williams, Director of Data at Penguin Random House UK. You can watch it here.
They all agree that building a lasting data culture is challenging but crucial to make a business successful.
Below is a list of the key takeaways from the event and some fresh perspectives on the future of data in business.
1. Data Democratization
Creating a culture with a focus on data empowers people to work with data effectively.
It's not just the technology that's the challenge; it's how people perceive and interact with data.
Jordan Morrow emphasized that everyone in a company, not just the data experts, plays a role in data and analytics. He argued that data literacy is not reserved for specialists but is a crucial skill for all.
2. Data Literacy
Being data literate means you can read, work with, analyze, and talk about data.
In a data-driven environment, almost everyone can feel comfortable with these skills. They don't need to be tech professionals, but they should know how to use data in their everyday working environment.
According to Jordan, it’s crucial to maintain a learning attitude, and encourage everyone to ask questions about business, think out of the box, and dig into what the data is saying.
3. Connecting Technical and Business Teams
AI tools help connect technical and business teams, enabling individuals to understand and apply data in positive ways, enhancing inter-team communication and creating a common language easy to use for everyone. Integrating AI into business must enhance, not replace, data literacy, focusing on aligning AI initiatives with business strategies and ensuring organizational readiness. Clear communication is essential in aligning AI efforts with business goals and key metrics.
4. AI and Data Culture: Security Concerns
AI is a powerful tool enhancing employee productivity, especially through web-based applications. However, integrating AI into business can be challenging, particularly if you want to safely handle confidential data without risking exposure on public platforms.
Businesses are striving to find a balance between harnessing the potential of AI and ensuring data security and privacy. The goal is to integrate confidential data into AI models in a controlled, organized way that maintains both the enthusiasm for these technologies and the integrity of sensitive information.
5. Challenges in Building a Data Culture
Building a strong data culture comes with challenges.
It’s about breaking down barriers so that data flows freely, not just stuck in silos. Creating communities where everyone can share and discuss data is key. The goal is to spread the understanding of data across the whole organization, ensuring insights are always shared and not just confined to certain areas. Also encouraging different departments to use and understand data helps bridge gaps and builds a forward-thinking, data-centric environment.
To do that we need to lead change positively and gradually, focusing on a people-centered approach rather than just imposing new rules, because nurturing a data culture is about collaboration, open communication, and gradual, inclusive change.
It's a team effort, requiring everyone to get on board and see the value of data in their work.
The event ‘Navigating Modern Data Culture’ clarified the role of a robust data culture in driving innovation and maintaining your organization competitive.
A key insight that emerged is the importance of understanding the people within our company and recognizing the value of data when it’s shared. Throughout the discussion, we delved into the challenges to build a robust data culture, always starting from people' needs, enabling them to excel while ensuring technology is a tool rather than a barrier.
This is how to build a data culture that lasts.