2014 NASCIO Recognition Award Submission Title: Category: Contact: New Jersey-OIT Data Governance Office State CIO Office Special Recognition New Jersey Office of Information Technology Office of the Chief Information Officer E. Steven Emanuel, CTO/State CIO 609-777-5865 steve.emanuel@oit.state.nj.us New Jersey Office of Information Technology Division of Enterprise Data Services Daniel J. Paolini, Director 609-777-3771 daniel.paolini@oit.state.nj.us Initiation: April 1, 2013 Completion: November 6, 2013 Page 1 of 6
Executive Summary Throughout New Jersey over the last thirty years, agencies have struggled with providing integrated data capabilities to meet management needs. Various approaches have been used, and all shared a few common weaknesses. Data definitions were not standardized, resulting in inconsistent data quality. Redundant efforts were spent on extracting and publishing data in multiple places and for multiple purposes without leveraging data, effort, or understanding. The business rules for the transformation of the data into useful information were locked in the heads of multiple, at times competing, analysts. The reporting infrastructure was expensive and did not provide all of the desired functionality. The data was often only available in the format required by one report community, and not in the format required by others. All of these problems share a common root cause the lack of data governance. Data governance is the formal convergence of data quality, data management, business process management, and risk management around the handling of data in the organization to provide positive control over the processes and methods used by data stewards and data custodians to handle data. Data governance encompasses the people, processes, and information technology required to create a consistent and proper handling of an organization's data across the business enterprise Steve Emanuel, State CIO, directed that the New Jersey Data Governance Office (NJDGO) be established within the Division of Enterprise Data Services to provide for an enterprise approach to improving data quality through data governance. The New Jersey Data Governance Office is responsible for executing the data governance policies and processes determined by the Data Governance Executive Committee in support of the Enterprise Data Stewardship Council. The NJDGO has the responsibility for ensuring that enterprise data governance policies and practices are followed. The NJDGO is responsible for the proper application of the organization s information and data architecture principles and the overall quality and usability of enterprise data assets. The New Jersey Data Governance Office does not represent the data police. Instead, it represents the data sherpas for IT projects. The NJDGO is involved in the development of a set of comprehensive statewide data governance policies, as well as the development of master data domains, common reference data, and open data solution, and an enterprise metadata repository. Page 2 of 6
Description of the Business Problem and Solution Like many organizations, New Jersey faces significant data quality issues. These include inconsistent definitions, data not fit for purpose, ambiguity, and competing systems of record. Every time a manager, a policy maker, or a politician needed information, it was addressed by a one-off scramble to locate data, bring it together, and put it into a useful format. When looked at in isolation, the impact of any one of these efforts was not noticeable. Collectively, however, they resulted in hundreds of data files being moved throughout the organization in an unmanaged way, often with the same data be created and moved multiple times. As a result, the state incurred substantial costs to support the data file creating. Worse, because there were no standards in place to govern the definition, transformation, or use of the data, the resulting information generated had inconsistent data quality. The legacy reporting tools available did not provide functionality that report consumers were demanding, and the tools required substantial technology support and custom programming each time a new report was required. A number of obstacles stood in the way of addressing these data quality and support problems in a comprehensive way. After many years of keeping data internal to their organizations, a culture of data sharing was emerging, in which agencies reluctantly agreed to share data files between each other. While a step towards better information, this actually exacerbated the data quality problems as data was shipped haphazardly through organizations. Agencies resisted the idea of integrated data for reusability. A second obstacle was that the reporting technologies at the time were often in the hands of analysts that were reluctant to give up their very prominent role in delivering information and solutions to management. A third obstacle was that the technology units supporting transactional systems were not comfortable with the idea of their data being available to others. These obstacles were compounded by the lack of authority for a centralized approach. In 2007, the governor signed legislation designating the New Jersey Office of Technology as responsible for information technology in the executive branch. As a result, the NJ Division of Enterprise Data Services (DEDS) in the NJ Office of Information Technology (OIT) published version 4 of the New Jersey Common Information Architecture (NJCIA) in March, 2008. The NJCIA described a framework for information management and also incorporated some basic data governance principles as directed by the new law. The NJCIA was Page 3 of 6
based upon industry best practices as defined by NASCIO, by the Data Management Association (DAMA), and by the Data Warehousing Institute (TDWI). The DEDS was given the task of creating the enterprise data warehousing environment, standing up a data warehousing competency center to support all executive branch agencies, to migrate the existing reporting solutions into delivery systems based on the enterprise data warehouse, to develop policies and standards, and to evangelize this approach to agency business and technical staffs. While the enterprise data warehouse environment grew to incorporate more than two dozen subject areas supporting dozens of data marts for almost every state agency, there were still data quality problems. At the heart of these problems was a lack of consistent data governance. Data governance is the formal convergence of data quality, data management, business process management, and risk management around the handling of data in the organization to provide positive control over the processes and methods used by data stewards and data custodians to handle data. It is a system for decision-making and accountability for data-related processes, executed according to agreed-upon policies which describe who can take what actions with what data, and when, under what circumstances, using what methods. Data governance encompasses the people, processes, and information technology required to create a consistent and proper handling of an organization's data across the business enterprise To address this gap, Steve Emanuel, State CIO, directed that the New Jersey Data Governance Office (NJDGO) be established within the Division of Enterprise Data Services to provide for an enterprise approach to improving data quality through data governance. The NJDGO is under a manager that reports to the Division Director. Within the NJDGO is a six-member Data Architecture team responsible for logical business modeling, model-driven development, and data standards. There is also a four person Reference and Metadata Team which supports metadata documentation and open data. The NJDGO manager and Supervisor of Data Architecture assist the Director with the development and maintenance of the state s enterprise information architecture. CIO Emanuel further directed the Data Governance Office to update the enterprise information architecture to emphasize the importance of data governance to the state s strategic IT direction. As a result, version 5 of the information architecture was developed. The team decided to rename the information architecture the New Jersey Data Governance Framework to reflect its focus and purpose. Page 4 of 6
The existing NJCIA version 4 was split into two documents; the New Jersey Data Governance Framework Strategic Plan, and the New Jersey Data Governance Implementation Plan. On November 6, 2013, version 5.03 of the New Jersey Data Governance Strategic Plan was published and is in use to guide data and information management. Highlights of this version of the information architecture include: Establishing the value proposition for data governance. Focusing on data reusability as opposed to data sharing. Establishment of data governance roles, including data stewardship. Defining the scope of data governance for state data assets. The New Jersey Data Governance Office is the architecture unit responsible for executing the data governance policies and processes determined by the Data Governance Executive Committee in support of the Enterprise Data Stewardship Council. The NJDGO has the responsibility for ensuring that enterprise data governance policies and practices are followed. The NJDGO is responsible for the proper application of the organization s information and data architecture principles and the overall quality and usability of enterprise data assets. The New Jersey Data Governance Office does not represent the data police. Instead, it represents the data sherpas for IT projects. The NJDGO is involved in the development of a set of comprehensive statewide data governance policies, as well as the development of master data domains, common reference data, and open data solution, and an enterprise metadata repository. Page 5 of 6
Significance to the Improvement of the Operation of Government Without data governance around definition and management of state data resources, data quality can only be addressed in a reactionary way. This results in the same data quality issues needing to be addressed over and over again, without systemic improvement to eliminate the problems at the source. Data governance identifies the data stewardship organizations responsible for authoritative sources, but it also provides a mechanism for rationalizing and harmonizing definitions of master data domains that aggregate multiple systems of record. With the establishment of data stewardship organizations and master data domain committees, the State of New Jersey has been able to address data management challenges that have prevented progress in creating high quality, reusable data. Benefits of the Project The New Jersey Data Governance Office has had an immediate effect on State IT initiatives. The following benefits have already been realized: The New Jersey Data Governance Framework has been developed to provide guidance in the state s data management efforts. A Data Governance Checklist was introduced into the state s Business Case Review (a component of its System Architecture Review) so that business owners are made aware of information management requirements and reusable data and technologies that could impact a potential project before it has proceeded beyond the conceptual stage. Data governance was placed around the Offender master data domain to contribute to the success of a data warehousing project for the study of criminal offender recidivism. A struggling cash flow project for the Office of Management and Budget was stabilized and eventually made successful through the introduction of a modeldriven architecture and a formal data governance approach. A Data Governance Academy was launched to provide data governance and management training and awareness to IT and business staff. All of these efforts benefited from the use of components guided by the New Jersey Data Governance Office and the New Jersey Data Governance Framework. All of these efforts were completed leveraging existing resources. These efforts were completed more cost effectively, especially within the context of continuing support and maintenance costs. Many of these efforts were completed more quickly due to the reusability of data and process. We fully expect these benefits to accrue with each new project that we undertake. Page 6 of 6