Assessing and implementing a Data Governance program in an organization

Assessing and implementing a Data Governance program in an organization

Executive Summary As companies realize the importance of data and the challenges they face in integrating the data from various sources, an increasing number of companies have started exploring data governance. With more users integrating data from various external data sources and using data discovery tools across the organization, improved data governance is critical to ensure efficient and effective use of data while enabling users to make better business decisions. Self-service data and analytics are fast becoming the standard and, increasingly, business users are demanding direct access to data to gain their own insights. Better business outcomes will ensue as data insights get more accurate. This will put the emphasis on value creation and the onus on Information Management to produce better sources and streams and easier aggregation and integration that any user can leverage in any application he or she wishes. Organizations in general and business models in particular increasingly rely upon confidential data such as intellectual property, market intelligence, and customers personal information. Maintaining the privacy and confidentiality of this data as well as meeting the requirements of a growing list of related compliance obligations are the top concerns for government organizations and enterprises alike. What business process does this data support & what is the criticality of this process? Do we document, communicate and promote the value of this Information Asset? What are the risks to the Enterprise if this Data / Information Asset be unavailable? Can we prioritize the Business Information that we want to qualify and quantify? Do we have policies to manage the Data as a Business Asset? Do policies govern Architectural Changes, which in turn, Do new business govern Data & technology Quality? initiatives get impacted if the value of a Data Asset is unknown? How do we implement the right level of control in our management of our key Data Assets? 2 Assessing and Implementing a Data Governance Program in an Organization Assessing and Implementing a Data Governance Program in an Organization 3

Essential components of Data Governance In today s data-driven world, a data governance framework touches practically every part of an organization s data management process-data Replication, Archival, Security, Backup, Policiesdown to individual technologies such as Meta Data, Data Lineage, Governance Council, Change Management, Master data, Business Process Management, and Risk Management surrounding the handling of data in an organization. How to assess an organization s Data Governance maturity Given below is a diagram that depicts the ITC Infotech s Data Governance Maturity models with 4 R s as major milestones: Recognizant, Receptive, Regulate and Reform. Before adopting an approach, it is important to assess the current state of maturity of the data governance capability. Change Management People & Processes DATA GOVERNANCE Tools & Information Architecture Data Ownership & Accountability Information Management Curve! Automation of Governance using software applications! Quantitative Process-improvement initiatives Level 4 REFORM People & Process Metadata Privacy/Security Master Data Management & Data Quality Data Ownership & Accountability Establishing Enterprise Data Council, Data Stewards, Policies around data frequency, source availabilityetc. Definitions, lineage (where does this data come from), business definitions, technical metadata Identify and control sensitive data, regulatory compliance Information Maturity Level 2 RECEPTIVE Level 3 REGULATE! Create Data Management Council! Standardized Processes & Stewards engaged! Centralized Master Data Repository & Compliance Efficiency! Ownership and Process flow defined along with the RACI matrix! Standardized processes through Manual intervention! Data Quality process in place with continuous monitoring! Improve Business effectiveness & efficiency Data Quality and Monitoring Data must be complete and correct - measure, improve, certify Master Data Management Ensure consistent business critical data i.e. Members, Providers, Agents, etc. Level 1 RECOGNIZANT! Data, a by-product of application! No Governance in place Information Lifecycle Management (ILM) Data retention, purge schedule, storage/archiving Information Accuracy & Organization Confidence 4 Assessing and Implementing a Data Governance Program in an Organization Assessing and Implementing a Data Governance Program in an Organization 5

Assessing the Data Platform Developing the right technology framework is critical to an organization s ability to automate, manage, and scale out its Data Governance program. The Organization needs to identify a robust data integration technology infrastructure that can support the program s processes, policies, standards, organization, and technologies. When one evaluates a data integration technology platform, it is important to examine its ability to ensure that:! All enterprise data can be accessed, regardless of its source or structure! Data is available to users and for applications when, where, and how it is needed! Data is accurate and valid! The value, structure, and meaning of data are consistent and reconciled across systems, processes, and organizations! An audit trail for the data and internal controls have been appropriately implemented! Data can be accessed securely Implementing Data Governance in an Organization In general, data governance has been perceived as an impediment for the business to react proactively to changing scenarios more effectively and efficiently. Hence there is substantial reluctance from business to adopt a structured governance process. This is where most governance processes fail to take off. As a result, what is described as the enterprisedriven approach is typical of traditional governance strategies ensues where a lot of work is done but very little is actually accomplished over the long run. A common mistake in using traditional data approaches is that they either take a business-driven or IT-driven approach that leads to biased decision making and process definition. As a result, it does not reflect the needs of the company s overall governance effort. Therefore, in the initial phase, it is always good to have a lot less governance and not attempt to implement everything in one go. One can set up the process by using Excel spreadsheets and e-mail workflows, and add new governance activities gradually. The ITC Infotech approach to building a structured Data Governance program ITC Infotech s approach to governance has promoted a healthy, collaborative relationship between the business and IT teams. This has helped acquire critical business buy-in for the process and thus adoption has become less cumbersome. We focus on enabling our clients business and IT teams and motivating them to do the right things. ITC Infotech has developed Data Workshop Questionnaire, Maturity Model & Data Quality Framework across industry that will be leveraged for approaching the Data Governance engagements. We follow a structured approach for Strategy Consulting to actual implementation in a phased implementation depending on the maturity level of the clients, this enables to possibly understand how people will actually use the system, thereby enabling the company to build something that meets their actual needs. An Illustrative Strategy & Maturity Assessment approach: Step 6 Present to key stakeholders a Strategy for implementing Data Governance Step 3 Conduct Maturity Assessment using ITC Infotech maturity model Step 1 Identify stakeholders and prepare for interviews & workshops Step 4 Perform Analysis for Data Quality, Architecture & Integration by leveraging ITC Infotech framework for DQ Step 2 Conduct workshop and interviews with key business and IT stakeholders Step 5 Assimilate findings, analyse and prioritise gaps & develop roadmap 6 Assessing and Implementing a Data Governance Program in an Organization Assessing and Implementing a Data Governance Program in an Organization 7

Key Deliverables The document would be concise, factual, practical, and educational that includes.! Maturity Level Illustrative Implementation Approach: The implementation approach will be based on the maturity level of the Organization, however below is an illustrative approach.! Data Management Structure - Role & Responsibilities Short-term plan Long-term plan! Data Maintenance, Persistence and Archival! Data Integration - Ownership & Responsibilities! Data Quality & Security! Business Intelligence - Meta Data Modelling! Process Flow and Change Management - Workflow & Approval (RACI Matrix)! Roadmap & Next Steps Step 1 Step 2 Step 3! Implementation of Data Quality, Security, and Backup in Database schemas! A formal Data Management Council & Data Standard Council with subject matter experts as a central function advising functional/technical areas and projects. >Set direction for Data Quality >Monitor Data Quality >Report status for qualityfocused initiatives >Identify stakeholders, establish decision rights, clarify accountabilities >Establish rules for data usage and data definitions! A vision for Enterprise Data Governance is defined but not fully brought in across the business! Create a Master data approach and identify the Master entities! A proper Change Management Process is implemented! Create a holistic Governance Program to include all departments and systems! RACI / accountabilities for all aspects of data are defined; workflows established! Executive level sponsorship established and full terms of reference for a DG council established. Sub-groups start to be put in place! DG fully recognized by C level executives with regular meetings and decisions communicated; DG Council part of business internal controls! Reduce the dependency on the manual tools like excel etc., and explore the usage of tools like Collibra, SAP Master governance, Informatica etc., for automation! Continuous monitoring of the Data Governance program for optimization and change >Clarify the value of data assets and data-related projects! Explore the usage of Metadata and Data Lineage! A long term solution roadmap on Master data, Change Management, Portfolio rationalization 8 Assessing and Implementing a Data Governance Program in an Organization Assessing and Implementing a Data Governance Program in an Organization 9

ITC Infotech Expertise & Consulting & Information Governance Capabilities Our agnostic portfolio of technology and! Master data management technology business process solutions help organizations consolidates millions of records and makes to better govern and oversee their complex, unified and validated master data instantly fragmented, dynamic, and security-sensitive available to a wide range of systems data environments.! An integrated, end-to-end data governance We have been working on innovations in areas environment empowers data stewards and such as Data Integration, Data Governance & other stakeholders to oversee and manage Quality, Enterprise & Modern Data warehouse, data in real time as it is created, collected, Cloud BI, Mobile BI, and Big Data. We offer and used numerous industry industry-specific solutions,! Data Integration framework to unify diverse such as a PNR Data Model for Airlines, Data and disparate information environments Quality, Enterprise Performance & Loyalty Framework for Hospitality, and Partner Data! Comprehensive performance management Manager for Airline & Insurance. helps to define, communicate, and measure goals related to their data governance Our consultants assist with strategy strategy development, best practices, identifying value, and gaining visibility into the broader organization. We leverage our Data Quality Framework, Data Audit and Governance maturity checklist to profile data in a way that tangibly measures the condition of the data in support of the business case. We also help identify short- and long-term technology requirements in support of the business case and ongoing data governance. We offer: Use case for Data Governance Risk and compliance:! Dodd Frank Act, BASEL II/III, Sarbanes-Oxley Act, IFRS, Equal Credit Opportunity Act! Durbin Amendment, RESPA and meeting other regulatory compliance Customer:! 360 degree view of customer profile! Omni-channel approach to generate new revenue streams, profitable customer acquisition and loyalty Data:! The blending and harmonization of diverse data sets from diverse sources and formats! Shadow BI across the Organization! Data stored in Public or Private cloud Conclusion The First step to a Data Governance program is to build a compelling business case which is key to successful implementation and sustenance of a data governance initiative. In order to achieve enterprise data governance, there is a critical need for proper planning along with executive sponsorship and a continuous improvement program that can help make the necessary adjustments in the company s governance structure as it matures over a period of time. It is useful to start the program in a small way and gradually build it up across the organization. With this in mind, constructing a case for data governance remains one of the most challenging things for an organization to successfully accomplish. ITC Infotech comes with the relevant experience and expertise to help companies chalk out a clear Data Governance program by taking a measured and customized approach.! Advisory consulting to helping companies build the compelling case for a Data Governance program.! Real-time data quality management capabilities, including profiling, matching, and merging, cleansing, and enrichment, help to proactively prevent bad data from corrupting stores of information 10 Assessing and Implementing a Data Governance Program in an Organization Assessing and Implementing a Data Governance Program in an Organization 11

Author Kishan Venkat Narasiah, Consulting Lead DWBI & Analytics, ITC Infotech Co-Author Viros Sharma, Vice President & GlobalPractice Head DWBI & Analytics, ITC Infotech 14 years of Industry Experience, currently More than 20 Years in the DW/BI Consulting and working in the capacity of Senior Technical Practice-Building space. Worked for Multinational Architect level advising clients on BI road map, IT companies like Bearing Point and igate in Information Strategy, Value realization, Data India and USA. AMP from IIMB. Double Masters Governance as well as managing and delivering in Mathematics and Computer Applications. DWBI projects. Perform advisory role on complex Business Intelligence projects and act as subject matter expert in defining requirements of most complex business initiatives. About ITC Infotech ITC Infotech is a specialized global scale - full service provider of Domain, Data and Digital technology solutions, backed by a strong business and technology consulting focus. The company caters to enterprises in Supply Chain based industries (CPG, Retail, Manufacturing, Hi-Tech) and Services (Banking, Financial Services and Insurance, Airline, Hospitality) through a combination of traditional and newer business models, as a long term sustainable partner. ITC Infotech is a fully owned subsidiary of USD 8bn ITC Ltd one of India s most admired companies. www.itcinfotech.com contact.us@itcinfotech.com 2015 ITC Infotech. All rights reserved.