Why Data Transformation Needs a Baseline





Picture a mid-sized company diligently collecting customer data for several years with the goal of uncovering insights into market trends, understanding customer behavior and analyzing risk profiles. Despite their efforts, there’s a persistent uncertainty about the effectiveness of their data strategies.

This uncertainty isn’t unique – many organizations are grappling with maximizing the value of customer data.
While understanding and leveraging customer data has become a linchpin for business success in the digital age, many organizations attempt to navigate this digital terrain with a significant blind spot. They lack a clear, foundational understanding of their current capabilities and limitations related to using this wealth of insights.
Put another way: they don’t know their “unknown unknowns” – the unidentified risks, gaps or challenges – when it comes to their customer data.
That’s why it’s crucial to establish a clear, objective baseline for an organization’s data maturity. This foundational step is precisely what a data maturity assessment, such as a “Return on Customer Data” assessment, accomplishes.
This article will explore why setting a baseline for data transformation is crucial to improving decision-making, and how a customer data maturity assessment can help reveal hidden challenges and drive business results.


What are your “Unknown Unknowns?”

Most organizations have unseen gaps in their data strategy or execution, which can hide inefficiencies and obstruct growth opportunities.
For instance, an organization might collect extensive customer data but cannot effectively use it for personalized marketing strategies due to unrecognized gaps in data integration and analysis capabilities. Failure to identify and address these unseen gaps can impede progress and hinder the organization’s ability to grow.
A data maturity assessment can help illuminate the “unknown unknowns” that may have been hidden until now.


A Baseline is the Foundation of Transformation

Embarking on a data-driven transformation without a clear baseline is like setting sail without a compass. The baseline serves as the critical starting point from which all improvements and strategic planning initiatives are measured.
It’s not just about understanding where you stand; it’s about laying out a roadmap for where you want to go. Without this clarity, efforts to evolve and enhance data capabilities can be misdirected or, worse, entirely futile.
Here’s why a clear baseline is crucial for building a data-driven transformation:
  • Proper direction and focus
    A baseline provides the necessary structure and focus for data-driven transformation efforts. It enables organizations to set realistic goals, prioritize efforts, allocate resources efficiently, track progress over time and find areas for improvement.
  • Benchmark for measuring progress
    A baseline in data maturity is a reference point or a standard against which progress can be evaluated. It sets up a starting point from which organizations can measure how far they’ve come and identify areas for improvement. By regularly measuring progress against this benchmark, they can also identify trends and patterns in their data use practices.
  • Improve strategic planning
    Having a baseline in place empowers organizations to develop strategic plans with greater precision and effectiveness. Aligning data initiatives with broader business goals becomes more straightforward with a clear baseline in place. Organizations can ensure their data-driven strategies are directly tied to achieving specific business goals, whether it’s increasing revenue, improving customer satisfaction or enhancing operational efficiency.
  • Enable risk mitigation
    Establishing a baseline plays a critical role in the early identification of potential risks and challenges throughout the transformation process. By understanding their current data capabilities and limitations, organizations can predict obstacles before they escalate, enabling them to implement proactive mitigation strategies.


Leverage a Data Maturity Assessment

A data maturity assessment, like the Return on Customer Data Assessment offered by Material, delivers valuable insights into an organization’s data management practices. It goes beyond surface-level evaluations to map out the current state of data maturity, offering a comprehensive view of strengths, weaknesses and areas for improvement.
By considering a dozen different areas including data governance, quality, security and the strategic use of analytics and AI, the assessment uncovers hidden challenges and opportunities that may have been previously overlooked.
This assessment enables organizations to transform their approach to customer data, making it more efficient, secure and strategically aligned with business goals. It helps position organizations for greater success in using customer data to drive decision-making and growth.


Use Case Examples

Consider the hypothetical example of a large media company with a substantial online presence. The company has invested in collecting customer data but hasn’t seen the expected uptick in engagement or sales.
A Return on Customer Data Assessment reveals a few crucial insights:
  • The data is incomplete as web traffic and ecommerce data are not integrated with the customer primary record in the CRM used for segmentation.
  • The data collected isn’t being effectively segmented or analyzed in real time to inform marketing communications and personalization


Armed with these insights, the company could bring in a Customer Data Platform and use advanced, real-time analytics and marketing automation tools to drive campaigns and personalization efforts that significantly boost customer engagement and sales.
Another scenario involves a financial services firm struggling with customer retention. The assessment uncovers the firm’s data security measures are not up to industry standards, leading to customer apprehension and churn. By addressing these security gaps and communicating these enhancements to its customers, the firm not only bolsters its data security posture but also restores customer trust, leading to improved retention rates.


Beyond the Baseline

Identifying hidden challenges and establishing a data maturity baseline is just the beginning. The real value comes from using these insights to drive actual business results. This process involves several key steps:
  • Sort and prioritize findings
    Not all insights will carry the same weight or impact. Organizations must prioritize these findings based on their strategic goals and the potential for business impact. This helps to allocate resources effectively and address the most pressing challenges or opportunities.
  • Plan strategically
    With a comprehensive grasp of their current standing and areas in need of enhancement, organizations can craft a strategic plan that targets these gaps and capitalizes on opportunities.
  • Implement recommendations
    Action is where insight translates into value. Whether it’s adopting new technologies, refining data governance practices or enhancing data security measures, the effective implementation of these recommendations is critical. Organizations must ensure they have the necessary resources, support and accountability mechanisms in place to execute these recommendations successfully.
  • Continue improving
    The data landscape is ever evolving, as are an organization’s goals and strategies. Regular reassessment and refinement of data practices ensure organizations stay agile and competitive. With proactivity, organizations can stay ahead of emerging trends, challenges and opportunities in the data-driven landscape.


Achieving Data Maturity is a Journey

Becoming a truly data-driven organization starts with setting a clear baseline of your current data maturity. A Return on Customer Data Assessment provides this foundation, as well as insights to help you navigate challenges and drive data-fueled growth.