In ‘The Data & AI Readiness Playbook’ we explain how you can unlock the value of your business data. Quality data is crucial to the effectiveness of AI. Here we look in more detail at the importance of data culture and the practical steps you can take to build a great data culture.
Data is perhaps the single greatest asset of the modern business and the bedrock of successful AI initiatives. But the quality of that data is critical to success.
The ROI of investing in data quality
Already convinced of the importance of quality data? Then skip ahead to ‘Developing a great data culture’, otherwise read on.
When we refer to quality data, we mean that it is accurate, complete, consistent, timely, valid, unique, and reliable. Armed with that, both human and artificial intelligence can arrive at the decisions that deliver real value.
Matthew Ebo is Assistant Strategic Insights Manager at Lloyds Banking Group and a contributor to ‘The Data & AI Readiness Playbook’. Matthew explains, “The cost of AI is an investment, but one that pays off in saved time, better decision-making, and automation of repetitive tasks”.
Developing a great data culture is an investment. An investment in the raw materials for transforming how an organisation operates, competes, and grows. For the business, this can drive value in many ways:
- Better, evidence-based decisions enabling more effective strategies, faster responses to market changes, and improved stakeholder buy-in for new initiatives.
- Increased innovation and agility as the organisation becomes better at identifying new opportunities, anticipating trends, and proactively adapting to changes.
- Improved operational efficiencies as data insights help identify inefficiencies and optimise processes and resource allocation.
- Greater competitive advantage gained from better anticipation of customer needs, reaction to industry shifts, and speedier innovation.
- Enhanced customer experience through superior analysis of customer data, to tailor products, services, and communications to better meet customer needs.
- Boosted employee engagement as staff become more engaged, and invested in the success of the business, by using data in their roles.
- Trustworthiness – data driven cultures tend to be open about business decisions improving trust amongst employees.
A great data culture enables smarter decisions, drives innovation, enhances customer and employee experiences, and provides a competitive edge.
So how do you get one?
Developing a great data culture
We know that AI initiatives are only as good as the data they access, so data quality is key – and great data follows a great data culture.
Data quality isn’t solely the responsibility of IT: it’s everyone’s responsibility. But it is IT’s responsibility to encourage a culture in which everyone cares about data quality“, explains Dan Knott, Data & AI Practice Lead, Cloud Direct.
A great data culture is one where data is valued by an organisation and its people, becoming a key part of daily operations. Here are eight key aspects of a great data culture.
1. Leadership commitment and example
As with most aspects of culture, data culture needs to be led from the very top. Senior management need to be actively involved in communicating the importance of data to organisational success. This needs to be supported with investment in the resources, training, and technology to support data initiatives.
2. Data-driven decision making
It needs to become the norm that decisions, at all levels, are based on data and analysis and not just intuition or hierarchy. Leadership and example are an important part of this. It also means establishing processes that make data analysis a standard part of planning, operational, and problem-solving activities.
3. Data access and democratisation
For IT this means ensuring that employees have easy, secure access to data and analytics tools. Employees should be able to freely share data internally, within appropriate privacy and security parameters, to enable collaboration.
4. Data literacy and training
Key to all this is an ongoing investment in employee’s data awareness and skills, ideally with training tailored to different roles and data personas. This should equip staff with the skills to interpret analytics, know when to use data, and to ask the right questions about data quality.
We’re looking at AI in the same way as other tools which become part of the workforce’s toolbelt, so we have to provide the same level of training for it. It’s not only imperative that the right skills are gained, but that they are regained as time goes on“, explains Mike Downing, Chief Technology Officer at insurance nonprofit WPA
5. Continuous learning and improvement
Alongside formal training initiatives, organisation’s need to develop a mindset of ongoing learning, experimentation, and adaptation – constantly utilising data to refine strategies and processes.
6. Trust in data quality
Underpinning this, there needs to be organisation-wide confidence in data accuracy and consistency. People know where data comes from and how reliable it is. This requires robust data governance, clear data lineage, and transparent processes for data validation and error correction.
7. Collaboration and communication
Success will be evidenced through open communication and collaboration around data, with teams working together to solve problems and share insights. This should be openly encouraged. It is important that this is also supported by establishing a common ‘data language’, so everyone communicates effectively.
8. Accountability and measurement
The final aspect of great data culture is one of transparency and it is an extension of point two. Clear goals and metrics are set for data initiatives, with progress tracked and results linked to business outcomes. With performance KPIs relating to data usage built into everyone’s evaluations.
Together, these elements can help you to build a great data culture that will deliver demonstrable value to your organisation and support effective use of AI.
Next Steps
Download a copy of The Data & AI Readiness Playbook to learn more. You’ll discover how others are preparing for and using AI, and a seven-step process to unlock the value of your business data.
