Data Governance: Where Does it Fit in Your Customer Data Management Plan?
The digital advertising environment is in a state of upheaval thanks to new privacy laws, browser and device protections, and closed digital platforms. Google's latest announcement this month that it won't replace third-party cookies with alternative user-level identifiers has amplified the noise.
These continual disruptions have a common thread running through them: the importance of owned customer data. But having first-party data won't help support business objectives if it's not high quality and the process of handling that data doesn't ensure people's privacy. To address the seismic shifts happening in digital advertising and keep up with an increasingly competitive, consumer-centric landscape, brands must adjust their customer data strategies and get their data "houses" in order. This is where data governance and data management come in.
Data governance and data management are often used interchangeably, but they're not the same. This post focuses on the former, with a nod to some of their differences and how they're interrelated. The goal here is to equip brands with a data governance framework that enables them to make more agile and informed decisions that drive business growth. Adopting this framework will lead to better business outcomes and better experiences with and for your customers.
Data governance is a necessity for modern businesses, but it is also one of the core challenges facing chief marketing officers who seek strategies to deliver compliant, ethical, and personalized marketing that drives business results. Fewer than a third of B2C organizations (31%) have robust governance frameworks that ensure the safety, reliability, and trustworthiness of their customer data, according to a recent Forrester Consulting study commissioned by Neustar.
What is data governance?
I often use this metaphor to bring data governance to life: When I play a game for the first time, I like to read the rules so I understand how to play, what actions I should take, what responsibilities I have to the other players, and how other moves affect me. Data governance is like a set of guidelines focused on the integrity of data, how these information assets are acquired, used, and protected so that they are handled consistently throughout the organization. In today's dynamic digital environment, data governance strategies have to be flexible and agile, not a set of hard-and-fast rules.
That sounds like data management, no?
Data management, by contrast, is best viewed as an IT practice. For example, if your company uses a CRM database to store customer data, that's a form of data management. Data governance would outline how your IT teams collect, validate, store, organize, protect, and otherwise maintain the data.
A data governance framework, as an example, helps determine how the information in a CRM system should be used in an email marketing campaign.
Is ethics part of data governance?
Ethics is an increasingly important consideration after some high-profile privacy scandals in recent years. That means regulatory compliance and ethical data use approaches have to be a part of a governance framework so employees are aware of proper data standards before pursuing new data-driven initiatives. Creating an approach to ethical data use might be one of the most challenging parts of a data governance strategy because deciding the right thing to do -- and how to create value for all stakeholders -- is not always clear.
Why does my marketing organization need to have a data governance framework?
Brands that don't close the data and partnership gaps created by organizational silos remain unprepared for changes to the digital marketing landscape, and the stakes around that lack of preparedness will continue to mount. What do I mean by that? In this view, privacy teams are responsible for addressing compliance and data ethics concerns, while marketing and analytics teams stay in their own lanes and use data, but don't have a focus on the privacy aspects of data use. As a result, instead of informing how privacy, marketing, and analytics workflows align, privacy considerations are too often seen as a hindrance to marketing. .
A key goal of a data governance framework is to break down data silos in an organization. It aims to harmonize data across all three pillars of data-driven marketing through a collaborative process. A comprehensive marketing strategy requires coordination between marketing management, privacy, and analytics teams in order to work in a modern B2C business where customer data environments are constantly disrupted, according to the Forrester study.
By creating uniform policies on the use of data, along with procedures to monitor usage, data governance can give decision-makers more reliable information as well as ensure compliance with new data privacy laws and other regulations.
What are some other benefits of a data governance framework?
You know the old slang expression, "garbage in, garbage out?" Computer programmers began using it to express the connection between poor quality input and faulty output. Data quality remains a concern, especially as companies collect more unstructured customer data from texts, voice messages, and IoT.
A data governance framework promotes both better-data quality and trust that the data integrity is consistently reliable and accurate. How? It helps create:
- Data quality definitions that determine the condition of the data, as well as its adherence to data policies.
- A business glossary that records the meaning of all data, ensuring clarity and preventing repetition.
- Roles and responsibilities for who cares for and maintains which data.
- Data catalogs that locate and assist with the understanding of the data.
What are some successful data governance principles?
George Firican, the director of data governance and business intelligence at the University of British Columbia and leading expert on the topic, has come up with data governance principles. I've selected five that are most applicable to marketing organizations like yours:
1. Data is a strategic enterprise asset and should be managed as such.
2. Data governance is a program and a business discipline, not a project, which needs ongoing investment, support, and exposure.
3. There is only one actively-managed and trustworthy version of the truth for enterprise data.
4. Data management needs to comply with legal and regulatory requirements, internal policies, and follow industry best practices and standards.
5. Data governance efforts, goals and objectives, priorities, decisions, and deliverables (procedures, processes, standards, policies, frameworks, etc.) are always communicated and made available to the entire organization.
Data governance needs to become a strategic priority because CMOs are under pressure to deliver measurable results. In a recent CMO Council report, 91% of marketers said that there was an expectation by senior management and board members that marketers drive measurable growth, with one in three saying that their business leaders felt it was the primary mandate of marketers today. As a result, CMOs and other marketers must lean into data – aggregated from across departments – to provide actionable insights for a better customer experience and decisions that drive company growth.
Get "Transforming Customer Data Management: Bridging The Gap Between Consumer Privacy And People-Based Marketing," a Forrester Thought Leadership Paper commissioned by Neustar, for the latest industry insights on how to:
- Meet the greatest business challenges of the moment across privacy management, data governance, and marketing management with comprehensive, identity-based strategies
- Bridge the widening gap between privacy, analytics, and marketing to operate effectively in a cookieless, disrupted customer data environment
- Leverage identity resolution and identity management to provide a single view of the customer to future-proof cross-channel, personalized marketing experiences