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Enterprise Information Management Enables Business Excellence

Enterprise Information Management Enables Business Excellence

Enterprise Information Management plays an enabling role in achieving Business Excellence. Effective EIM is based on common understanding about related concepts and definitions

Enterprise Information Management (EIM) plays a vital role in enabling Business Excellence (BE). As a first step towards leveraging the full potential of the synergy between BE and EIM, it is crucial for an organization to develop a common, comprehensive organization-wide understanding of the related concepts and definitions and develop models such as the BE data model and the Corporate Performance Management (CPM) data model of an organization.

What Is Business Excellence?

BE can be defined in several ways. For the sake of this article, the definition used is based on the  European Foundation for Quality Management (EFQM) definition. BE is described as outstanding practices in managing the organization and achieving results, all based on a set of fundamental concepts or values. These practices have evolved into models for how a world class organization should operate.

Business Excellence Dimensions

Business Excellence has three (3) dimensions: Direction Setting, Execution, and Results.

The Direction Setting dimension includes defining the organization’s purpose and vision; and developing the organization’s strategy, as well as steering the culture of the organization. The Execution dimension includes engaging an organization’s stakeholders, creating sustainable value, and driving the organization’s performance and transformation. The Results dimension includes the results of stakeholder perceptions and strategic and operational performance. Figure 1 depicts the dimensions of BE.

Figure 1. Dimensions of BE (Based on the EFQM Excellence Model)

A Word About Data Models

In general, a data model is an abstract model that organizes elements of data and standardizes how they relate to one another and to the properties of real-world entities (Figure 2).

A conceptual-level data model is the highest level of the data model; it is used to represent business entities and the relationships between them. There are many notations that can be used to represent the relationship between business entities. This article uses the Crow’s Foot notation (Figure 3).

Figure 2: The ER model is used to represents the business entities and the relationships between them
Figure 3: The Crow’s Foot Notation

Business Excellence Data Model

Each of the dimensions in Figure 1 has several criteria: the direction setting dimension has 2 criteria, the execution dimension has 3 criteria, and the results dimension has 2 criteria. In addition, each criterion of the direction criteria and the execution criteria has its respective criterion-parts, and each of these criterion parts are tracked against several radar elements which are measured through several radar attributes. However, the result criteria are directedly tracked against several radar elements which are measured through several radar attributes. Figure 4 depicts BE conceptual-level data model.

Figure 4: BE conceptual-level data model

Figure 5 depicts an illustrative example of the data sets of the execution dimension which includes 3 criteria: engaging stakeholders, creating sustainable value, and driving performance & transformation:

  • By drilling down to the driving performance and transformation criterion parts (the parts of criterion 3), there are 5 criterion parts associated with criterion 3.
  • By drilling down again to the radar elements of criterion part 1 of criterion 3, there are 3 radar elements connected to this criterion part.
  • By drilling down to the radar attributes of each of these radar elements, the approach radar element can be measured through the sound and aligned radar attribute, while the deployment radar element can be measured through the implemented and flexible radar attribute, and finally, the assessment and refinement radar element can be measured through the evaluated and understood as well as the  learn and improve radar attributes.
Figure 5: Illustrative example of the data sets of BE execution dimension

Business Excellence and Corporate Performance Management

One important question is how the BE model works with the CPM model? Figure 6 shows the relationship between the BE data model and the CPM data model.

The right-hand side of Figure 6 includes an example of a data model of a typical CPM framework (a balanced scorecard framework, for example). In this data model:

  • An organization might have several strategic objectives
  • Each strategic objective is tracked against specific key performance indicators (KPIs).
  • A strategic objective, however, might also be realized through several initiatives where each initiative is tracked against specific KPIs as well.
  • An objective might also be addressed through several strategies, and strategies might be realized as well through initiatives that are in turn tracked against some KPIs.

The left-hand side of Figure 6 includes the BE data model. The KPI/radar-attribute link entity in Figure 6 shows how the BE data model is linked to the corporate performance management data model. The key performance indicators are related to the radar attributes of the result criteria through the KPI/radar-attribute link, where the KPIs are measured through the performance management system and the KPI figures are used to feed the data to the excellence model radar attribute entity of the BE data model.

Figure 6: The relationship between BE data model and CPM data model

What is Enterprise Information Management?

Enterprise Information Management (EIM) is an integrative discipline for structuring, describing and governing information assets across organizational and technological boundaries to improve efficiency, promote transparency and enable business insight.

Enterprise Information Management Dimensions

Figure 7 shows that EIM has three dimensions: Framework, Initiatives, and Domains. The Framework dimension includes 7 components: vision, strategy, metrics, data/information governance, organization and roles, information lifecycle, and enabling infrastructure.

The Initiatives dimension includes all types of initiatives an enterprise might need to implement its EIM program. Typical EIM programs might include initiatives such as data warehousing, master data management, metadata management, enterprise content management.  EIM programs may algin with analytics initiatives such as business intelligence, real-time operational intelligence, big data analytics, textual analytics and data science, machine learning, and artificial intelligence-enabled analytics. An EIM program might include a corporate performance management initiative as well.

Each of these initiatives might span across several information domains. So, the third dimension of EIM is the collection of information domains. Typical information domains include master data, operational data, analytical data, content, social data, machine data, metadata, and other data. Finally, it is worth noting that all the components of the EIM framework can be applied on the level of the EIM program as a whole and on the level of each specific initiative in the program.

Figure 7: EIM Dimensions

Enterprise Information Management Data Model

Figure 8 depicts the EIM data model. It shows the relationship across the 3 dimensions of EIM. The relationship between the EIM building blocks and the EIM initiatives is a many-to-many relationship. For example, a data warehousing initiative should have vision, strategy, metrics, information governance, organization and roles, information life cycle, and enabling infrastructure building blocks (Figure 9). Also, a strategy building block should exist for each initiative of the EIM program (Figure 10).

An EIM Initiative might span across multiple information domains. For example, a data warehouse initiative can span across the master data, the operational data, the analytical data, and the metadata domains (Figure 11). A modern data warehouse can also span across the contents and the machine data domains (based on Inmon’s DW 2.0 reference architecture and Gartner’s Logical Data Warehouse Reference Architectures, for example).

The information-asset entity is a linking entity that converts the relationship between the Initiative’s entity and the information domains entity from a many-to-many relationship into two one-to-many relationships. This link entity includes the information assets used by the EIM Initiatives in each information domain.

Information assets might also include information objects (or data sets) and each information object may be used by many persons in the organization.

Figure 8: The EIM data model
Figure 9: A data warehousing initiative should address all the EIM building blocks
Figure 10: A Strategy building block should exist for each initiative of the EIM program
Figure 11: An EIM initiative might span multiple information domains

Conclusion

As a first step towards leveraging the full potential of the synergy between BE and EIM, it is crucial for an organization to develop a common, comprehensive organization-wide understanding of the related concepts and definitions.  This process should cover all the dimensions of BE and EIM and should be available to the entire organization for explanation and review.

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Dr. Hayfa Bu Hazzaa, DBA. Eng.

Hayfa Buhazzaa is an enterprise information management strategist, enterprise architecture leader, data warehouse / BI strategist with broad experience across petroleum and utilities.

She has exceptional, demonstrated skills in developing and implementing programs in the areas of enterprise information management, corporate performance management, enterprise architecture and industrial automation and control systems.  

Hayfa Buhazzaa holds a DBA in Enterprise Information Management, an MBA in Global Leadership and Management, and a B. Sc. in Computer Engineering. She is certified as a Digital Business Transformation Manager, Data Science Specialist, and Text Analytics Specialist.

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