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Translating Technical Data Discourse: Simplifying Jargon for Executive Decision-makers and End-users

In an earlier piece, I suggested a straightforward method to convey data initiatives, such as transitioning your organization into a data-driven entity or creating a new data project, by using three essential dimensions: data, technology, and people, due to the simple fact that these elements...

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Transforming Data Approach: Simplifying Technical Jargon for Leadership and Public
Transforming Data Approach: Simplifying Technical Jargon for Leadership and Public

Translating Technical Data Discourse: Simplifying Jargon for Executive Decision-makers and End-users

In today's data-driven world, understanding an organization's data maturity level is essential for making informed decisions and driving strategic growth. To help businesses navigate this complex landscape, a new tool is proposed - the 3D Data Maturity Assessment Tool.

This innovative tool is designed to evaluate an organization's current data maturity and provide a clear, actionable roadmap for improvement. The tool is based on the Dell Data Maturity Model, a simple and relevant framework for understanding data maturity levels.

The 3D Approach

The 3D Data Maturity Assessment Tool follows a unique, three-dimensional approach. It assesses data maturity across the following dimensions:

  1. Data Management: Encompassing data collection, storage, and organisation.
  2. Governance: Covering data security, privacy, and ethical compliance.
  3. Analytics and Culture/Processes: Including data analysis, decision-making, and the overall data-driven culture within the organisation.

These dimensions form the "3D" axes of your assessment, representing different capability areas or perspectives in data maturity.

Building the Tool

To create the 3D Data Maturity Assessment Tool, follow these steps:

  1. Define the Dimensions and Levels of Maturity: Create detailed scoring criteria for each dimension based on Dell’s framework or similar models like DCAM v3 or 5X Data and AI Maturity Framework. Define maturity levels (e.g., Beginning, Developing, Mature, Leader) to classify where the organisation stands per dimension.
  2. Develop a Scoring Matrix and Criteria: Create a questionnaire or digital tool with questions linked to the scoring criteria that cover all dimensions. Responses will be scored to determine the organisation's maturity level in each area.
  3. Implement a Scoring and Visualization Mechanism: Aggregate scores from each dimension and visualize them as a 3D maturity map or radar chart to easily show strengths and gaps at a glance.
  4. Develop a Roadmap Generator: Based on the maturity scores, develop simple, prioritized recommendations aligned with the Dell model’s improvement areas.
  5. Validate and Iterate: Test the tool with real organisational data maturity assessments, collect feedback from data and business stakeholders, and refine the questionnaire, scoring, and roadmap logic accordingly.

Additional Considerations

  • Incorporate best practices from modern data maturity frameworks that address AI, cloud, and governance factors (e.g., ethical AI compliance, multi-cloud data management).
  • Ensure the tool supports evidence-based assessment by requiring documentation or examples to substantiate scores where possible.
  • Keep the improvement roadmap simple and focused on quick wins and strategic milestones.
  • Consider building the tool with modular features and open APIs to integrate with existing organisational platforms like CRM or ERP.

By systematically mapping Dell's data maturity dimensions into a scored, visual 3D model and coupling it with tailored recommendations, the tool can reliably determine current data maturity and offer a clear, actionable roadmap for ongoing improvement.

The Human Factor

While technology plays a crucial role in data maturity, it's essential not to overlook the human factor. Data literacy is often neglected in data-driven organisations, making staff training a crucial component of any data strategy. Simplicity is key to the majority of staff/users being able to take ownership of the organisational culture.

Executive Sponsorship and Staff Training

To ensure success, executive sponsorship is in place for the data strategy, and staff training is available for data skills. With these elements in place, data is used to make critical business decisions for key initiatives.

The Journey Ahead

The 3D Data Maturity Assessment Tool is a powerful resource for organisations seeking to understand their current data maturity level and what needs to be done to reach the next level. By partnering IT and business units for the data strategy, simplifying communication with management should be aligned with the organisation's strategic goals.

With the first level, "Data Aware," where siloed data is managed, multiple data sources exist, and there is no single source of truth, organisations can begin their journey towards data maturity. The ultimate goal, "Data Savvy," where organisational and data silos are broken down, a data strategy is established, and a single source of truth has been established, is within reach.

[1] Source: Dell Technologies (2020). Data Maturity Model: Assessing Your Data-Driven Capabilities

[2] Source: Gartner (2021). Data and Analytics Leaders Need a Maturity Model to Drive Digital Transformation

[3] Source: Forbes (2021). Why Your Organization Needs A Data Maturity Model

[4] Source: McKinsey & Company (2021). Data maturity: A roadmap to data-driven decisions

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