Designing a Data Source Discovery App - Part 9: Managing Organizational Data

by DL Keeshin

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December 3, 2024

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Overview

In my last post, I described the design approach for managing location data and using the ChatGPT API to help assign job roles. Today, I am going to discuss the current state of the app design strategy.

The kDS data source discovery app design is evolving. The design now has four key components:

• Managing organizational data.
• Generating interviews based on business keys.
• Distributing and collecting interview data.
• Analyzing data for better insights.

For this post I'll focus on the first component—Managing Organizational Data—and highlight how aligning data with an organization’s structure is the first step of building a data source discovery interview solution.

Why Align Data with an Organization's Structure?

In most organizations, data sources naturally align with the organization's structure. Each business unit or department collects and manages data based on its responsibilities, needs and function. For example:

• Sales might use a CRM to track leads and sales performance.
• Marketing could rely on tools like Google Analytics for engagement data.
• Finance typically uses ERP systems for budgets and financial reports.

This setup makes sense, but it can also create data silos—where information is isolated in one department and hard to share across the organization. Breaking down these silos helps create a unified view of data, making cross-department insights and decisions much easier.

Why Is This Important?

Aligning your data with how your organization is structured helps with:

Data Stewardship

Data stewardship focuses on managing, maintaining, and ensuring the proper use of data, while ownership belongs to the organization. In recent years, businesses have shifted away from the concept of data ownership by individuals or units, emphasizing stewardship to improve data quality, governance, and collaboration. For instance,

• HR manages employee records.
• Sales maintains customer information.
• Operations handles supply chain data.

Identifying Data Silos

Departments often work independently, which can cause data to be stored in separate systems. This makes it hard to:

• Get a full view of how the business is doing.
• Share important information between teams.
• Make data-driven decisions using all available insights.

Mapping Data Flows

Understanding how data moves across departments helps answer questions like:

• Where does the data come from?
• Which teams need this data?
• How is it used and transformed?

Improving Governance and Compliance

• Customer data might need to comply with GDPR.
• Financial data might need to follow SOX regulations.

Managing Organizational Data

1. Collect It

Here are the three main prototype app web forms for collecting organizational data. They are self-explanatory. The first is "Add a Parent Organization", the second "Add A Subsidiary", and the third, "Add Business Units". In this work flow, key attributes like industry, size, revenues, and locations get picked up along the way.