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How is Data Management Different from IT Management?

September 15, 2021

“Some people think data is a matter of life or death. I assure you it’s much more serious than that”. – Bill Shankly

Data is a wonderful asset that delivers great benefits when collected, governed, and managed well. However, it can be damaging when used and managed poorly. Most companies understand that good data management is essential, but many organisations fail to implement good data management practices and rely only on traditional IT management approaches.

Differences Between IT and Data Management

While data management overlaps with IT management, it differs in a number of key ways that demand specialised skills and attention:

1. Data is Key to Core Business Activity, IT is a Support Service
Typically, IT is one of the ‘support’ services within a business. Its functions might underpin the core ‘revenue-generating’ activities but is typically not counted among them. Like finance, human resources, marketing, and a number of other support functions, it is not uncommon to see IT management being outsourced so that the business can focus on core activities.

Control of data is rarely outsourced. Data is a key input to core business activities like financial and operational management and strategic decision making. It also forms a key interface with suppliers, partners, and customers. Data analysis is a core business activity and is often a key driver of revenue-generating ideas leading to increased sales. In fact, data is increasingly a revenue-generating activity in its own right.


2. Data Management is Process and People Focused
IT management is mainly focused on the implementation and maintenance of technology whereas data management is primarily focused on facilitating and enhancing business processes and supporting people in their day-to-day activities.

Technology plays a role but it is only the framework within which data-centric activities are carried out. A database management system, data integration tool, or reporting tool is only a shell for each enterprise to construct its systems to understand their business.

Investing in data technology will make your data systems more successful and the development of good governance practices and effective standards and processes will result in quality data for the business to use to make decisions.


3. Data is Proprietary
While every long-standing company has some proprietary IT systems and applications, most IT assets today are generic, off-the-shelf systems with well-established third-party and vendor-led support and upgrade roadmaps.

Data management systems, on the other hand, might be assembled using relational database management or reporting tools since the nature of data tends to be highly specific. New and future planned data systems will be largely proprietary and the responsibility for managing the data will lie with the business.


4. Data Systems are Dynamic
Data systems can change frequently and often at short notice since business requirements and data input patterns are constantly evolving. The technical barriers to change are often lower for data systems than for IT systems and there is a greater blurring of the lines between end-users and system developers.

Changes to data systems (such as creating new reports or metrics, adding new data sources, or joining data sets in different ways) can often be implemented quickly and cheaply with no new technology and with minimal technical skills. However, these changes can have significant downstream impacts if proper attention is not paid to issues like the quality of the data, the security of the data, metadata, downstream dependencies, data quality, and communication.

The speed and frequency of change means that management of data systems is more reactive than normal IT management. As such, effective policies, standards, and procedures within which people can work independently and safely are essential.

A large part of data management is about facilitating flexibility while preventing serious business and customer problems. Suffice to say, continuous improvement, security, governance, education, communications, and the monitoring and enforcement of rules are all essential ingredients in data management.




Relationship Between Data, IT, and the Business

Data managers, business users, and IT all have different, sometimes overlapping, interactions with data in an organisation.

  • Large parts of data management exist within the business domain, separate to IT.
  • There is significant interaction at low levels. For example, input from the data team is essential in many business processes. Alternately, members of business teams routinely undertake low-level data activities like the creation of new data items, data manipulation, data stewarding, etc.
    There are significant parts of data that exist entirely within the IT domain such as the installation and maintenance of software, BAR, networking, etc.
  • Many of the softer aspects of IT (security management, supporting end users with technical issues, planning and implementing of new systems, security, and licencing) overlap with data management.
  • The majority of IT domain activity occurs separately to core business activities. The business may be entirely dependent on the systems maintained by IT, but IT and business staff rarely interact directly at low level on a day to day basis, outside of logging and resolving trouble tickets.


Technology is not the Problem

Many companies have invested in technology as a first step toward becoming a data-oriented organisation. However, the technology alone isn’t enough. A survey by Harvard Business School found that only 7.5% of organizations cite technology as a primary difficulty when it comes to rolling out data projects. More pressing challenges include:

  • 77% say that business adoption of data initiatives is a major challenge
  • 99.5% identify people and process issues as a challenge
  • 40.3% identify lack of organisational alignment on data projects
  • 24% cite cultural resistance as an impediment to data projects
Data Management Responsibilities

Data Management is defined by DAMA as, “the development, execution, and supervision of plans, policies, programs, and practices that deliver, control, protect, and enhance the value of data and information assets throughout their lifecycle.”

As with most management practices, the central function in data management is governance — the exercise of authority and control (specifically planning, monitoring, and enforcement) over data assets. Data management involves:

  • Working with IT and the business to define overall data strategy and long- and short-term objectives
  • Defining and assigning roles and responsibilities
  • Managing personnel (hiring, training, supervising, developing the necessary capabilities)
  • Overseeing the selection and implementation of appropriate technologies
  • Managing third-party service and technology vendor relationships
  • Overseeing the development and monitoring or enforcement of rules, policies, and procedures, including those for data architecture, data modelling, project lifecycle, data lifecycle, data quality, master data management, reference data management, data retention and disposal, change management, data security, including access control and activity monitoring, and for regulatory compliance, including data protection
  • Overseeing the creation, maintenance, use, and improvement of data assets in line with agreed policies
  • Managing the relationship with the business and responding to business needs
  • Ensuring data service quality and that business impacting issues are addressed
  • Providing on-going education, training, and skilled support for the business in their use of data

This is a broad remit requiring a range of softer skills and a level of involvement in and knowledge of business practices that many IT managers can function without.

The vast quantity of data available today is something we’ve never experienced before. However, according to IDC we’re only using about eight per cent of the data we generate.

Technology is helpful in deriving value from data but not without the people who have the knowledge and skill to understand it and the policies and processes to ensure it’s being used for the good of the business. Only when the people and processes align with the technology can businesses experience real value and individuals can relax and enjoy their football.

Article by John Thompson, Managing Partner in our Data Insights Practice

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