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Data Office as Part of Enterprise Architecture

13 March, 2019 | Charles Ngando Black | More Data Geekery

A Data Office has become a reality as part of many organizations’ enterprise architecture frameworks.  A data office can support moving the organization toward a data-centric view for enterprise services and solutions..

Introduction

Data Office, data service, data-centric architecture, data governance, chief data officer, etc. are some terms that have become part of the language of data management professionals.  More than concepts, these phrases reflect current or future realities within organizations.

Enterprise Architecture provides a relevant framework for explaining these changes, while identifying the opportunities each can offer to any organization.

To explain the concepts and value of a data office, recall the classic and simplified schema of an enterprise architecture, using the data office as one of the new building blocks that contributes to the transformation of the traditional enterprise architecture.  Use cases demonstrate the value of the data office, since their implementation requires the development of shared data management capabilities.

A data office includes the concepts of data service and of data-centric architecture.  Moving toward a data-centric enterprise architecture also affects relationships across data stakeholders and requires rethinking the data management organization and rules.  Integration of these changes in an enterprise architecture can be implemented according to a scheme that respects the enterprise business model.

New Enterprise Architecture

The traditional organization of work often has led to the division of staff into three categories, depending on whether it was directly, indirectly, or not in contact with the client.  Front office, middle office, and back office derive their meanings from this distinction.

The work automation (company computerization) has preserved this division for the information system, understood as a structured set of capabilities developed by a company to process data.  These capabilities include staff and the roles played by members’ staff, and includes processes, functions, applications, data, infrastructure, organizational units, etc.

The diagram below shows the simplified diagram of the enterprise architecture.

Figure 1 – Simplified Diagram of Three Divisions in Office Capabilities

Front office is the top of enterprise architecture.  Its capabilities are activated by (direct interaction) or for (indirect interaction) the client.  They serve the needs of marketing, client communication, sales, pre-sales, client service, etc.

Back office represents the lower part of an enterprise architecture.  The client cannot activate its capabilities.  These activities are internally oriented and serve the needs of production, purchasing, logistics, inventory, accounting or human resources management.

Middle office is the intermediate part of an enterprise architecture.  Its capabilities are not activated for the client (no interaction) but are intended to contribute to the execution of external rules and / or internal rules.  They serve the control needs of compliance, internal control, accounting reconciliation, risk management, auditing, sales administration, etc.

In recent years, this classic scheme has been enriched by new building blocks, which aim to create and maintain shared capabilities in different areas, including information security, data protection, analytics, digital or data management (see diagram below).  The Data Office, in charge of data management, has thus emerged, alongside other cross-functional building blocks such as Analytics Office, Information Security Office, Privacy Office or Digital Office.  These building blocks are placed under the responsibility of new roles, respectively Chief Data Officer, Chief Analytics Officer, Chief Information Security Officer, Data Protection Officer (or Chief Privacy Officer) and Chief Digital Officer.

 

Figure 2 – New Simplified Diagram of Office Data Capabilities

Use Cases Requiring a Data Office

The classic scheme (i.e. without a data office) can handle intra-zonal (back office, front office or middle office) and inter-zonal-contiguous (front office and middle office or middle office and back office) use cases effectively.  However, due to the data sharing requirements, the development of shared data management capabilities becomes mandatory to handle inter-zonal–noncontiguous (back office and front office) or global (back office, front office and middle office) use cases effectively.

Following are some use cases that require the implementation of a data office.

 

Purpose Use Case Data Sharing Challenges
Client Management:

Client Service, Client Experience, Multi-Channel contact, 360° client view, etc.

Provide real-time position or status (stock, bank account, product under maintenance, etc.) Develop front office (Website) capabilities to integrate real-time back office (logistic, core-banking, maintenance system, etc.) data
Provide the customer the opportunity to update their personal data Distribute updated data from the front office to the middle office (internal control, etc.) and to the back office (order processing, billing, etc.) in near real-time
Develop a complete view of the client Consolidate Front Office data (CRM and Web) with back office data (physical contact points, order processing, invoicing, etc.), middle office data (risk, controlling, etc.) and external data sources (social media)
Risk & Compliance Management:

Risk Reporting, Compliance Reporting

Develop a risk reporting Integrate Front Office data on commitments, with external data (regulation repositories, ratings, etc.), Back Office data on positions and recoveries, and Middle Office data on guarantees, risk assessments
Process personal data breaches Integrate Front Office data (security incidents, requests) with Middle Office Data (risk assessment and impact analysis, compliance reporting, etc.), Back Office Data (record of processing, data classification, etc.) and external data (regulation or supervisory repositories, social media, etc.)
Innovation & Product Marketing Management:

Product/Service Marketing, Innovation

Provide a single view of all bank accounts held by a service user Integrate Front Office Data (CRM, Web and Mobile) with Back Office data (accounts and historical account positions) and External data (target banks)
Inform about a malfunction of a product (vehicle, wagon, plane, etc.) and refer to a maintenance team Integrate Back Office data (device description, maintenance history) with External data (sensors, dashboards or other output devices) and Front Office data (Web and / or mobile)

 

Conclusion

As organizations become increasingly data-focused, their need for an office that addresses the enterprise scope of data (front office, middle office, back office) becomes more apparent.  In addition, the adoption of an enterprise architecture that includes the reality of data, its management and centrality in the architecture’s framework grows with the scaling demand for data and information.

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