Get the Value Out of Your Data

We often hear about the importance of being data-driven, digitalization, and the potential of AI to revolutionize operating models. These advancements aim to help organizations become more efficient and gain a competitive edge in their markets. In today’s world, where digital systems and platforms play a crucial role, it is essential to have a deeper understanding of customer and organizational needs. By aligning our expectations and investments in data and digital technologies, we can maximize their benefits.In our journey towards digitization, we have focused on efficiency, automation, and gaining a competitive advantage. However, we have sometimes made the mistake of simply migrating old technologies onto new infrastructure without considering operational changes or retiring outdated systems. This approach resulted in limited additional value or cost savings, as we still had to maintain both old and new technologies. Often, the focus has been on technology adoption rather than understanding the true needs of the organization.

So what is missing? Our digital processes and systems are primarily meant to handle data efficiently and faster than we can manually. It might be time for us to shift towards a more data-centric approach, supported by technology, to unlock greater value.

What should we focus on to get more value from the data we possess? Here are some examples:

• Improved decision-making
• Enhanced operational efficiency
• Better customer understanding and personalization
• Identifying trends and market opportunities
• Driving innovation and product development
• Risk management and fraud detection
• Improved security and compliance operations

By prioritizing these areas, we can unleash the full potential of our data and technologies, enabling us to achieve our goals more effectively.

Overall, the value of data lies in its ability to provide organizations with insights, intelligence, and a competitive edge in an increasingly data-driven world. By leveraging data effectively, organizations can drive growth, improve operations, and make smarter decisions to achieve their business goals.

Treat your data as an asset

Focusing on data, requires looking at data as a strategic asset and treating it accordingly, ensure that your organisations strategy and the data strategy are aligned. Start by treating your data as an asset to ensure quality and controlled distribution of the data. Data assets can be seen from both a strategic and operational viewpoint with different focus:

• Strategic Data Assets– refer to data that is critical for supporting the long-term strategic goals and objectives of an organization, managed through a data governance board, typical examples here being your customer data or financial data portfolios.
• Operational Data Assets– refer to data that is necessary for day-to-day operations and immediate decision-making within an organization, for example data to be used in a customer campaign, or data used for financial reporting on investment progress. The operational data assets feed into the strategic data assets

By starting with the Strategic data management, you prioritize the data that’s important for your organisation, identify what data adds value and what must be protected.

Having identified and focused your data strategy at the senior management level, it is important to look at Operational Data Management and collaborate operationally. Understanding your operational data needs and aligning the right digital services with cross functional teams ensures delivery and control at an operational level, starting with:

• Enable collaboration across the organisation, as data will flow across silos.
• Identify and empower the data experts in the organisation.
• Understand how the data is used.
• Understand where the data is processed.
• Understand where the data is stored.
• Secure where the data is and ensure that it is used for the correct purposes.
• Align your technology and architectural delivery patterns to enable reusable components.
• Build flexible data products that will provide insight that are useful to the organisation.
• Manage the data products lifecycle.

Agility and Transparency in Data Strategy implementation

A robust data strategy should have clearly defined outcomes and measurements in place to trace the value it delivers. However, it is important to acknowledge the need for flexibility during the strategic and operational phases. Consequently, defining deliverables becomes crucial to ensure transparency in the delivery process. To achieve this, adopting a data product approach focused on iteratively delivering value to your organization is recommended.

The evolution of DevOps, supported by cloud platform technology, has significantly improved the software engineering delivery process by automating development and operational routines. Now, we are witnessing a similar agile evolution in the data management area with the emergence of DataOps. DataOps aims to enhance the speed and quality of data delivery, foster collaboration between IT and business teams, and reduce the associated time and costs. By providing a unified view of data across the organization, DataOps enables faster and more confident data-driven decision-making, ensuring data accuracy, up-to-datedness, and security. It automates and brings transparency to the measurements required for agile delivery through data product management. Moreover, data product traceability boosts tactical decision-making and provides transparency by measuring progress on deliverables, not just tasks.

Once you have set up the operational structure, it is important to enable your ways of working. Agile cross-functional teams have become the norm, and it is essential to implement roles such as product managers and scrum managers to oversee delivery and direction. Additionally, having data owners and stewards is crucial in anchoring decisions and ensuring the follow-through with specific actions. With the increasing adoption of cloud-based platform approaches by vendors, leveraging data platforms allows you to choose and adopt tooling that suits your specific needs. However, it is vital to have a clear understanding of your organization’s requirements.

Then prioritize the areas that are important and as you gain better insight and understand what data can be trusted to help you with your decision making, in measuring efficiency or for customer and market trends. A collaborative and agile approach to understanding your data landscape will aid in your organizations strategic goals and when planning to utilize digital services such as AI.

Jonathan has extensive experience in the private and public sector, working across Europe, with over 25 years of strategic and operational industry experience across a variety of industries. As a Consulting Director at Tietoevry Create and a member of the Chief Architect Forum, Tietoevry Create is a global IT company with 24,000 experts specializing in cloud, data, and software, serving thousands of enterprise and public-sector customers in more than 90 countries.