What is Data Management in the Era of Data?

By Mike Poyser, Mark Babij & Joon Park of CMA's Customer Insights & Analytics Council

Name a company which does not consider its data as a key asset or at least important enough to store and mine for insight.  Now, name a company which has strong governance of its data and a business-driving Data Management function.  There are maybe a handful of names across both lists, with perhaps a few more names in the latter category.  But the point is clear: while many companies put a lot of emphasis on the importance of data, the investment and management structures to govern data are severely lagging behind where they need to be to unleash data-driven marketing.

For clarity, Data Management, as described by the Data Management Association (DAMA), covers “the development, execution and supervision of plans, policies, programs and practices that control, protect, deliver and enhance the value of data and information assets.” Two things are essential for effective data management: clear Data Governance, and senior Data Management leadership within an organisation.

Data Governance is the framework for establishing strategy, policies and objectives around data.  It helps define data quality standards and policies for ongoing monitoring and measurement.  Governance helps ensure that data is not treated as a by-product of an application or project, but as a valuable asset that needs to be looked after and invested in.  It ensures that an organisation maintains best practice in relation to ingestion of data, and use of common definitions for metadata.  A key outcome from effective Data Governance is that it sets up the organisation to be able to generate value from its data, for example through being more successful in marketing campaigns, making better-informed management decisions and through data commercialisation.

When it comes to strong leadership in data management, many companies still have plenty more to do.  Indeed, the function has the unfortunate history of being overlooked.  It can often fall between the two stools of IT and Analytics, having a sort of ‘in-betweener’ status.  Data Management sometimes sits as a function within IT.  In itself this is fine, but without strong Data Management leadership there is a danger that the focus is too much on delivery of “data projects”, and not enough on enhancing the data asset itself.

Data Management can also sit within an Analytics structure, typically in a more nimble organisation, closer to the end users of data (typically Analytics and Campaigns teams) and aligned to the business.  This can be very effective for setting up a data environment quickly to enable analytics delivery, but is typically not optimal in the longer term.

In reality, there is a strong rationale for Data Management sitting as a distinct function within a business.  This becomes apparent by looking at the roles of the three different functions, as shown in Table 1.

 

Table 1: Overview of how the roles and responsibilities of Data Management are distinct from that of IT and Analytics

 

IT

Data Management

Analytics

Focus

The environment (“the box”) 

This includes the piping of information to/from the box, and ensuring the box is functioning and secure.

The content of what is in “the box”

This includes determining the right structure of the data, and having a detailed understanding of the data and its definitions.

The usage of the data

This involves working with the data to address business challenges and needs..

Role & responsibility  (in relation to data)

  • Infrastructure
  • Systems
  • Security
  • ETL
  • Experts in the data itself
  • Data content
  • Efficiencies in storage
  • Manage as an asset
  • Understand business questions
  • Understand data available
  • Analytical techniques to manipulate data
  • Insight and action focused

 

In a smaller, more nimble organisation, Data Management should arguably be more aligned to Analytics, to enable close support of the business needs. In an established organisation, the Data Management function should exist as the guardian of the data, and have a senior figure leading the governance and utilisation of information as an asset.  The companies that have taken this furthest have even appointed an executive, a Chief Data Officer (CDO), as their most senior data figure. 

Now, ask yourself these questions: does your business have adequate and effective governance around its data?  And is the Data Management function seen as a key team for advancing the performance of your business instead of being a hidden, back-office function?  Great if you can answer ‘yes’ to both questions, and if not, hopefully your company has at least identified that both are critical to future success as we move deeper into this era of data.

In the next blog we will explore the Data Management Journey to becoming an effective customer centric organisation. 

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Michael Poyser, VP Analytics at Aimia

Mark Babij, Associate VP, Customer Insight & Analytics, Canadian Tire

Joon Park, Senior Marketing Manager, BMO Insurance

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Tags: data management, data, analytics, IT, chief data officer, data governance, campaigns