This paper is characterized as an essay capturing the need of Enterprise Information Management supporting business operational efficiency, decisions, more specifically managing the information is an asset to the organization. It aims to present and discuss the basics of EIM, its benefits and challenges in implementation at organization level. It concludes that a right strategy needs proper roadmap to define how to implement the EIM, by highlighting Coforge's methodology to define the EIM strategy.
Whenever any business transformation happens to an organization, the IT specific solutions for data center, infrastructure, and architecture are modernized and evolved. However, the business would continue struggling on information if it is not delivered to right person at right time. A proper information management addresses this issue. Following are the major reasons to establish Enterprise Information Management (EIM) in organization:
To improve the information management capability and overall information management practice at enterprise level
To establish right information governance for managing information assets throughout their life cycle
To be accountable to meet legal and regulatory compliance requirements
To reduce the duplication in work for addressing the business processes
To maintain data consistency at enterprise level with proper data quality management and governance
To manage enterprise data, both structures and unstructured data, and extracts meaningful information to business stakeholders based on what they want
To ensure right information delivery to right person at right time in right format
To understand information as a valued asset at enterprise level
To improve access to the right information in a secured environment by protecting the data repositories with proper encryption, security control for access
To have right policies to manage the information management
To ensure accurate and complete data in reports required at operational as well as tactical / strategic needs
It brings following benefits:
It helps in improving data quality, integrity, and consistency. By this, data reliability factors within business increase.
It helps to improve business processes and rules used for data quality management
Information is easily shared across business groups, helps in improving operational efficiency and effectiveness.
It enables to establish single version of truth in a standard enterprise based data hub, enabling better decision-making at organization level.
It reduces overall IT cost.
It brings business values such as standardized information as per the business needs without any anomalies, data is in compliance to the regulations, more insight to the data
EIM has lots of benefits to both technical as well as business stakeholders. To define a good strategy on EIM, organizations face some challenges.
Challenges of EIM Strategy
Enterprise information management is not all about the management and governance of information. It needs right people, processes and technologies to drive right information management at enterprise level. It needs right strategy and plan to begin with. It has following challenges:
While managing the structured information is easy by establishing the right integrity and by adding the business glossary / catalogue, unstructured information brings the challenges due to its nature of variety, volume and velocity. Unstructured data is much more than structured data in any organization. Further, unstructured data volume gets multi-fold over period of time.
Presence of variety of processes and data of similar nature in different systems for different business groups bring a major challenge to establish a common understanding process, standards, nomenclatures agreeable to all.
Due to presence of numerous applications, the data is silo. Each application has its own structure and definition to data. This gives different meaning to the data and brings no single source of truth. It also makes difficulty for the people to collaborate. Data inconsistencies and redundancies impact business results.
As each business group owns their respective data, enforcing / adhering to enterprise data governance policies and rules is tedious and time consuming process. Creating standards for information classification at enterprise level and getting concurrent views from all stakeholders for the same is a major challenge. Some organizations struggle to have buy-in from different departments even after having an EIM strategy if those standards are not discussed with them while defining the strategy.
Critical Success Factors for EIM:
Executive leadership commitment for establishing EIM
Stakeholders commitment, drive and embrace the new / change in capabilities through EIM
A well-defined technical and data architecture
Suitable governance framework to manage and maintain data quality
Define data management practice
Clear governance and accountability environment
Improvement of EIM capability and practice
Treat information as a valued asset to the organization
Drive an information management culture across the organization
Take ownership of EIM processes
Develop a unified approach to defining, measuring information and its management
Take ownership of defining and improving the policies, guidelines and standards
Implementation of proposed initiatives
Go for continuous improvement planning
Coforge’s Methodology to define EIM Strategy
Following figure illustrates the methodology that Coforge follows to define EIM strategy.
The four phased methodology is described below.
Phase I: Discovery
Data is collected from the organization on different areas. Some of the critical focus areas and their descriptions / information required from the organization are mentioned in below table.
EIM Focus Area
EIM Focus Area Information Required
Building blocks and their purpose in enterprise solution. It covers how it is scalable to adapt the data growth, change in processes to execute strategies. It defines the data flows, data transformation covering the business rules to standardize and integrate the data to bring single source of truth of data at enterprise level.
Data model design pattern, its scalability, establishing data integrity at enterprise level
Need to know if the business glossary is same across the business groups. Do they have proper clarity in the definition without any ambiguity
Processes covers the different information oriented processes are documented and used in the EIM solution. Consistent and automated processes bring maturity to the solution.
Need to verify the presence of data security and protection policies, guidelines. It is necessary to find out what all security compliances are adhered.
Data quality covers different dimensions such as data accuracy, data standardization, data timeliness, data consistency, data timeliness, etc. for the information shared with the business It is also necessary to know the use of corporate taxonomies, consistent rules and processes at enterprise solution.
Data Organization / People
Roles and responsibilities defined under enterprise solution. It is also required to know the presence of Center of Excellence (CoE) group to work on information management. For proper data quality management, data stewards are required to establish rules and guidelines for data quality and to monitor the improvement of data quality.
Tools and Technologies
There are many tools and technologies used to support data repositories at enterprise level. Though it is not critical to have multiple tools for same purpose, it is better to have rational and have standardized tools at enterprise for different purposes.
Phase II: Assessment
Following activities are conducted during assessment phase.
System Assessment: Expert access different building blocks of EIM to assess the functionalities of different modules against data management requirements (standards, guidelines, security, etc.). It is important to find out how the systems are configured and to realize gaps between system settings and the requirements. For example, it is to check if there is any report duplications or overlap to a large extent while accessing the BI repository.
Interviews: The interviews involve business and technical holders of different levels from top management to level of normal users / administrators. One of the objectives was to know their involvement in designing, managing and governing in enterprise information management. The interviews involved the top management who are responsible for budgeting and program sponsoring, the top management at department / business group level, users at operational level, and the technical teams (IT technical team and application support team).
Analysis: The information collected from the available artefacts, system access and through initial discussion is analyzed to find out if there is any gap in information management as per industry standard practices. Also, it is to verify if the actual reality of the system and information management is par with the requirements from the stakeholders. For any gap, it is necessary to find out the feasible solution for overall information management.
Phase III: Validation
The team discuss with different groups of stakeholders to validate the findings from overall information gathering and prior discussions with the stakeholders. The discussions bring the industry standard practices of EIM and challenges / gaps in existing EIM to the management. The team present what are the critical gaps and possible initiatives to overcome the same to the stakeholders and ask their opinion.
Phase IV: Finalization
The consulting team find out the ball park estimations for different initiatives and verify the interdependencies of those initiatives. As per the business criticality, interdependencies, and quick implementation time, the team determines which are short term initiatives (quick wins) and which are long term initiatives. After that, the team defines the roadmap for EIM strategy along with possible tangible and intangible benefits. Finally, they present the EIM strategy report to the stakeholders.
Assessment of EIM Strategy
Some organizations may have EIM strategy in place to manage EIM activities to achieve key objectives such as improving information sharing, information integration, etc. However, they struggle to know the effectiveness of the strategy and to examine EIM strategy through an external agency before it gets implemented. In that case, Coforge would assess the strategy as well. Following points are considered for assessing the strategy:
Key issues and challenges associated with EIM
Policies, rules and standards used for effective implementation of EIM
Roles and responsibilities defined for EIM
Tools and technologies associated with EIM and how they are managed
How the strategy is able to address current and future issues