Across industries, data governance is a fundamental requirement for guiding the effective and compliant collection and use of the massive amounts of data companies now have access to. It’s not only a protective measure, reducing risk and ensuring compliance with data protection initiatives, but is also a way to capitalize on the true value of data.
Nowhere is this mix of risk and opportunity more urgent than in e-commerce. E-commerce companies have unprecedented access to a vast amount of personal, behavioral and financial consumer data with an aim to use much of this data for data-driven marketing and decision-making.
At the same time as fulfilling their duty to safeguard this data, e-commerce companies also want to develop increasingly sophisticated data use plans that will let them understand their customers as fully as possible. This could be everything from personalization algorithms and engines to targeted marketing, understanding customer journeys and analysis of user behavior. These use cases and the risks they can entail require a careful approach to protecting sensitive data and putting processes in place to define policies, standards, quality, security and data roles, that is who is entitled to what data and in what situations.
These key considerations lead to the creation of your data governance strategy.
What Is Data Governance?
Let’s take a quick step back, though, and think about what data governance is. Data governance encompasses the end-to-end process of bringing consistency and transparent organization to how you collect, process, maintain, store and secure data in enterprise systems. Data governance goes beyond basic data management, although data management and tools fall under the data governance umbrella. Data governance includes definitions of how you collect and use data responsibly, ensure the quality of the data collected and the storage processes you have in place to make the data as secure as possible while safeguarding your own alignment with data handling regulations, such as GDPR.
Your data governance strategy will be underpinned by your data governance framework. You can look at your data governance framework as a set of pillars on which your data governance strategy is built. Your data governance framework will grow naturally from your overall data strategy, and careful choices about collecting only what you will need, use and are entitled to access will lead to an auditable trail of your decision-making and compliance. One potential set of pillars could look like this:
You want to establish trust in data and its quality and consistency while instilling a clear data-centric mindset. To foster this new mindset, you want to create a set of processes for transparency, accountability, security and compliance as well as the tools and access that will help data flow to where it needs to.
Defining what you need to achieve with a data governance strategy will inform this pillar. What does your data governance program need to include? Does it address data privacy and security? Does it include thorough authorization and accessibility controls? Does it specify collection, storage, processing rules and how this is managed over time, i.e. data lifecycles, that correspond to your need and use as well as what is allowed from a legal compliance standpoint? Is auditability built in?
What teams or people are involved with your data governance program at each step? Define the roles: do you have data scientists? Do you have a data team? Do marketing staff need access to data platforms or just to data reports? Are external agencies and contractors interacting with and requiring access to these platforms and systems? Who will be affected by data governance programs or activities? These relationships to data and data tools need to be mapped out as a part of the governance strategy as well.
How (structures, tools and technologies)
What kinds of structures and solutions must be introduced to control data management, permissions and access, monitor compliance and enforce your data governance strategy?
These pillars take into account many data governance best practices, but they may look different depending on your business and what you want to achieve. Essentially, the purpose is to identify all the factors that contribute to managing and protecting your company’s data assets.
Data Governance Versus Data Management
Aren’t data governance and data management the same thing? While many businesses look at data governance mostly from the regulatory control and policy point of view, it should also include data management, which is a subset of a data governance strategy. Developing a complete data governance strategy, as highlighted above, should be looked at not just as an opportunity to ensure that data is secure, adheres to data policies you’ve set and does not get misused, but also as a unique opportunity to seek data quality and integrity to make your own work easier and to make data easier to work with. When you have a clear data strategy guiding what data you collect, and why you’re collecting it, data governance is almost an afterthought.
Data management itself encompasses the technical aspects of collecting and storing data, making it, first and foremost, an IT discipline. It contributes to your data governance strategy but is a hands-on practice that includes processes and systems – the solutions and tools a company uses to collect, store, organize, validate, process and maintain data throughout its life. Data management may include data stewardship, data warehousing, data architecture, data quality management, data security, among a number of other categories of physically and logistically managing the data.
What Is Master Data and Master Data Governance?
A subset of this data is master data, and you may create a separate approach to master data governance. Master data is the data at the heart of specific categories or domains you have defined as core to your business. With e-commerce, you will want to determine these categories to ensure that you have consistent, accurate data covering each core category. To simplify it, master data governance boils down to getting everyone on the same page. Developing and maintaining master data requires that everyone in an organization has the same definitions, policies, rules, tools, processes and workflows to work with.
Understanding and Applying Data Governance Best Practices
Armed with a clearer understanding of data governance, it’s clear that it goes beyond data management and data tools. Data governance is a strategic imperative as well as a path to considerable organizational benefits for e-commerce companies, including:
- Potential cost savings in data management
- Increased value and visibility of data in the organization
- Minimize security risks and boost data privacy
- Standardization and accuracy in data, policies, procedures, and standards, for easier transparency and auditability
- Improved data quality for better applicability in data-driven marketing and activity, such as customer segmentation, customer behavior insights, customer journey and conversion analysis, attribution, etc.
Data Governance Best Practices
Every company and its data-informed goals are different, but in moving toward data governance, there are a number of basic best practices you should consider and build on:
- Remember that data governance encompasses all the factors listed above: people, processes, methods and technologies. You should consider all of these as you develop your data governance strategy, but don’t get lost in the details.
- Before you get started on this process – or change an existing one – you will want to communicate and inform all the relevant teams and people and get feedback and buy-in. Your people will determine the success of your data governance endeavor – you need them on board.
- Set clear roles. Again with people, you need to know who is driving the governance process, and who is hands-on with data, managing and/or using it.
- Define your pillars. As listed above, figuring out your why, what, who, and how will help you develop your data governance strategy and start to deploy it.
Data governance is not optional. For e-commerce companies relying on granular data to do data-driven marketing, to predict trends, to understand inventory management, to understand customer journeys and buyer personas, and other advanced analytics cases, data governance is essential. It lets you empower your teams with clear, consistent policies and access to key data while also protecting sensitive data and ensuring regulatory compliance.
Ready to discuss how data governance fits into your overall data and digital marketing strategy? Contact us today.