Enterprise data management

In today’s world of complex data accumulation and ever increasing regulatory and legal requirements, it has become paramount for organisations to have a streamlined, standardised system to find, manage, access, store and secure their data.

Collecting data and maximising its value becomes harder as data volumes grow. Most enterprises have realised that the data they use is not sufficient to meet their needs. To improve information oversight, financial reporting and value generation, enterprises need to rethink their approach to data. Data needs to be governed, monitored, managed, and controlled.

Process and system controls must be equal to the new regulatory requirements and the increasing complexity of products. Consequently, ever more data must be collected to satisfy the requirements of external and internal clients. To build trust in data, all enterprise stakeholders must work from a common single source of truth.

Challenges

Current challenges that enterprises are facing:

Increasing reporting and risk requirements

• Increasing demands and reporting to regulators, local authorities, clients and business partners.
• Increasing risk management requirements.

Growing volume of data

• Sharp increase in data volume through systematic accumulation of data.
• The constant effort to develop new products for new or existing markets is a key driver of rising data volumes.

Controls

• Dealing with the growing complexity of controls arising from new regulation constraints.

Higher complexity

• Newly developed products become increasingly complex and differentiated from existing products – to the extent of structuring projects specifically for a particular client.
• This differentiation is a key driver of complexity as it becomes ever more difficult to distinguish these products.

Advantages

Advantages of a common data management governance:

Minimising data redundance

• As the data is not scattered across the various locations and it is stored at one place, it can easily be seen that the redundant data does not exist.

Increase level of security

• Access of the data can be monitored and it reduces the amount of data leakage which in turn increases the data security.

Increase data integrity

• The data is stored across a common data platform which makes the organisation and management of the data easier and ensures that the data is consistent and correct and availability is managed.

Cost effective

• Centralised data consumes less power and requires less maintenance.

Increased consistency and efficiency

• Data is controlled by common governance, procedures and policies. Potentially by a dedicated and focused central business unit.

Better availability and more detailed data could create substantial opportunities in the field of analytics, thus improving the understanding of internal business processes, products and stakeholders.

Expectations

The main expectations from internal and external customers with regards to data management and governance are:

Quality of data and transparency

• Ensuring a high quality of data from external and internal providers, traceability of data, data consolidation, controls.

Customisation of data and reporting

• Offering clear definitions of indicators such as risk, performance, liquidity, etc. Improved corporate toolsets along with focused resources and capabilities should also allow improvements data presentation, with better exploitation of dashboarding, KPIs and predictive analytics

Independence

• Independence from IT functions to allow more flexibility and agility in terms of customisation and development, along with the data demands of an enterprise being prioritised independently unrelated IT initiatives.

Quick data production through automated processes
 

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The move to a centralisation of data isn’t only about compliance, avoiding inefficient data silos and privacy problems. It helps enterprises to justify a business decision or strategy, to attribute marketing spend, or understand the full user and customer journey from a single source of truth. Centralised data means that the whole organisation works from the same blueprint, avoiding discrepancies that easily arise from disparate data and different tools.

It is also about the future and being able to harness the right data for more advanced use cases. When data is scattered, limited, or untrustworthy, it is impossible to expand the scope of applications that can be developed. As most businesses are moving in this data driven direction a centralised data flow will unchain vast possibilities, paving the way forward.

About the author

Danijel Delic is a Manager with Deloitte Consulting.