Here’s how I define these three key areas of data management:
Process Definition:
Process definition is the documentation and standardization of how work gets done within an organization. It establishes clear workflows, responsibilities, and procedures so that data is collected and managed consistently across teams.
Data Governance:
Data governance is the framework of policies, standards, and accountability that ensures data remains accurate, secure, consistent, and reliable. It helps organizations maintain trust in their data and use it responsibly.
Tech Stack Management:
Tech stack management is the strategic oversight of the tools and systems used to collect, store, integrate, analyze, and report on data. It involves ensuring that technologies work together effectively, support business goals, and provide users with reliable access to information.
Together, these three areas create the foundation for high-quality data and better decision-making across an organization.
Process definition: Mapping how each team works, documenting every step they take to execute their day-to-day activities.
Data governance: Mapping the fields used to collect information throughout the process and identifying which systems store that data.
Tech stack management: Organizing the systems that will be used to run day-to-day operations, and monitoring them to ensure that when reports are needed, the insights generated are accurate and reliable.
For me answering these questions starts with another question. This goes back to the work reality I experienced in my last job. What is the value of the whole process? For the company to to scale, for the individual team member to be be able to contribute best to the organizations success (measurable). This clarification is important for me, as we did not have a central RevOps person/department. To start with process definition, etc. I would first need to convince management to give me the go to get together the responsible departments and to work togehter on these topics.
For process definition I would primarily work with all departments working with the sales funnel - Marketing, Sales, Operations, Customer Services. Here it would be important to really put the customer in focus to start aligning existing processes or start from scratch.
For data governance I would start with my team (if I have one) to review existing data sources and labels and make a first draft for a governance document. This would also include the processes we agreed upon and data templates as well as bringing these two together with possible reporting options which would then be possible. This would make also the first workshop results tangible and give me buy in for the next steps.
For tech stack management I would start working with IT to determine which tools are available, match it the process requirements and ask IT to support in minimizing cost and maximizing efficiency.
Process definition means breaking down a workflow into simple, manual micro-actions that ultimately produce a final result. Once every action is mapped, you must ask a crucial question: “Is it actually worth automating this process?” As a golden rule, you shouldn’t spend 10 hours trying to figure out how to automate something that would otherwise only take 30 minutes to do manually.
2. How do YOU define data governance?
Data governance means identifying exactly what data we have and defining which fields are strictly necessary. For example, if we are analyzing website performance, we only extract the essential data points needed to see if the site is well-made or has issues. It acts as a strict filter against obsolete or redundant fields. For instance, it’s useless to track both a “Website URL” and a custom “Company Domain” field if they serve the exact same purpose. You don’t need every single field that somebody asks for, as that only accrues tech debt.
3. How do YOU define tech stack management?
Tech stack management is the process of deciding which tools are genuinely needed and eliminating overlaps. For example, using both Airtable and Excel for data management is completely redundant. Instead, you select one (like Airtable), integrate it directly with your CRM, and define exactly what those two tools do. It means building a fully integrated stack rather than constantly chasing the “perfect” new tool that only adds unnecessary complexity.
This is about mapping and standardizing workflows across sales, marketing, and customer success. It means clearly documenting how data is collected, how leads move through the funnel, and how handoffs happen between teams. The goal is consistency—so everyone follows the same playbook and data flows smoothly without gaps or duplication.
Data Governance
This is the framework for managing data quality, security, and compliance. It ensures that the information your teams rely on is accurate, accessible, and protected. Governance covers rules for data entry, ownership, permissions, and compliance with regulations (like GDPR). Without strong governance, even the best processes and tools can produce unreliable insights.
Tech Stack Management
This is about selecting, integrating, and maintaining the right tools to support your defined processes. It means avoiding tool sprawl, ensuring systems talk to each other, and regularly auditing whether each platform adds value. A well-managed tech stack reduces friction, saves costs, and empowers teams with the right capabilities at the right time.