Reshaping data landscapes: Anatomy of a strategic migration

In today's data-driven business landscape, data transformation that enables your business to better leverage your data for strategic decisions is paramount. Not surprisingly, therefore, one survey of business and IT leaders found that 73% rated data integration as critical or important.* Often, such data transformation entails migrating legacy data into a modern environment that allows you to access your data’s full potential.

To get a feel for how this can work, we’ll look at a prominent environmental solutions company. The company embarked on a transformative journey to reshape their data landscape through a data ecosystem migration project. More than a tech upgrade, the company sought a strategic shift towards an empowered data ecosystem that would foster decision-making at every level. We’ll look at some key aspects of the journey — establishing goals, overcoming challenges, implementing change and measuring outcomes — in turn.

An ambitious path forward

The heart of a data transformation project is establishing goals designed to unlock data's potential. For the environmental solutions company, their ecosystem migration meant gaining:

• Unified insights – establishing a unified data ecosystem to empower confident decision-making
• Agile decisions – accelerating data availability for timely responses to market dynamics
• Data integrity – enhancing data quality through centralization and robust quality control
• Scalability – creating an architecture ready to scale with the company's growth
• Business insights – uncovering patterns and trends for innovation and competitiveness

However, the project wasn't focused exclusively on technology. Rather, it aimed to reshape the business through data transformation. And that meant overcoming a range of obstacles.

Legacy platform challenges from a fragmented past

Overcoming technical debt is among the most widespread challenges in data transformation. Spending on legacy systems is expected to approach $69 billion in 2023. This NTT DATA client faced several challenges rooted in their legacy data platform well before the project's initiation. The challenges included fragmented data scattered across systems, which resulted in disjointed insights. From a productivity perspective, inefficient processes with manual interventions and outdated tools lead to bottlenecks. Data problems were abundant. Discrepancies due to a lack of governance lead to conflicting data points. At the same time, complex data retrieval processes hindered agile decision-making. And expanding operations strained the platform's scalability. As such, the project aimed not only to tackle these issues but also to foster a data-driven culture.

Navigating complexity with strategic design strategies

Addressing such pervasive challenges requires a multifaceted approach to data transformation. To fuel this client’s transformation, we built a modular foundation with seamless orchestration, a centralized data repository and comprehensive data governance. By integrating diverse data sources, we could streamline insights, which, combined with a single source of truth, empowered, swift, informed decisions. Through robust governance, we ensured both data quality and integrity, paving the way for an agile and efficient data ecosystem.

Tangible outcomes and future readiness

Success in transformation projects can be measured in outcomes as defined in the goal-setting phase of transformation projects. For this environmental solutions company, the project culminated in tangible outcomes that shaped the company's present and future, including:

• Data integrity — meticulous governance reduced errors, ensuring data consistency
• Streamlined reporting — dashboards and reports deliver timely, informed insights
• Empowered decision-making — real-time insights enabled swift responses to trends and demands
• Scalability — the architecture's scalability prepared the company for growth
• Cost efficiency — cloud-based architecture translated to cost savings
• Future-proofing — the architecture's adaptability readied the company for technological shifts
• Data-driven culture — enhanced data accessibility empowered decision-makers at all levels

Charting ongoing enhancement

Data transformation projects have specified scopes that allow you to assign a completion status. But completing a predefined project doesn't mark the end to an overall data transformation. It signals the start of ongoing monitoring and refinement. Vigilant monitoring ensures optimal functionality throughout your data ecosystem. As customer needs change, you can adapt. The modular architecture we created for our client allows them to integrate new sources and technologies seamlessly. As a result, their teams are equipped to extract maximum value from the system, building their overall capacity. Their agile ecosystem positions the company for new opportunities, and we remain committed to their success. The legacy of data excellence continues as the company embraces a dynamic future.

Each stage of a data transformation journey incorporates milestones. These take on forms such as achieving goals — such as empowering decision-makers with timely and relevant data — and generating specific outcomes. As the data landscape evolves, harnessing that evolution to empower decision-makers becomes increasingly vital. The power of data is clear — it catalyzes growth, innovation and a brighter future.

If you’d like to discuss aspects of data transformation or any other issues you may be facing, please don’t hesitate to contact us.

^{* 2021 Dresner Advisory Services Data Pipelines and Integration Market Study}