Hipercept Executive Briefing Establishing a Data Governance Program



Similar documents
CRM for Real Estate Part 1: Why CRM?

CRM for Real Estate Part 2: Realizing the Vision

Best Practices for Planning and Budgeting. A white paper prepared by PROPHIX Software October 2006

Best practices for planning and budgeting. A white paper prepared by Prophix

Five Fundamental Data Quality Practices

BUSINESS INTELLIGENCE

OPTIMUS SBR. Optimizing Results with Business Intelligence Governance CHOICE TOOLS. PRECISION AIM. BOLD ATTITUDE.

INSIGHT NAV. White Paper

BI Dashboards the Agile Way

The difference between. BI and CPM. A white paper prepared by Prophix Software

Data Management Practices for Intelligent Asset Management in a Public Water Utility

Make the right decisions with Distribution Intelligence

Enhancing Sales and Operations Planning with Forecasting Analytics and Business Intelligence WHITE PAPER

The following is intended to outline our general product direction. It is intended for informational purposes only, and may not be incorporated into

Contents of This Paper

How To Get A Better At Recruiting And Staffing

Business Intelligence

Business Intelligence

THE IMPORTANCE OF EXPENSE MANAGEMENT AUTOMATION

The Ultimate Guide to B2B Telemarketing

Information Governance Workshop. David Zanotta, Ph.D. Vice President, Global Data Management & Governance - PMO

ElegantJ BI. White Paper. Considering the Alternatives Business Intelligence Solutions vs. Spreadsheets

Automated Business Intelligence

Anatomy of a Decision

PROPHIX and Corporate Performance Management. A white paper prepared by PROPHIX Software June 2010

Enhancing Sales and Operations Planning with Forecasting Analytics and Business Intelligence WHITE PAPER

POWERFUL, FLEXIBLE, AND AFFORDABLE ERP SOLUTION

A business intelligence agenda for midsize organizations: Six strategies for success

Data Warehouse and Business Intelligence Testing: Challenges, Best Practices & the Solution

The Manager s Guide to Avoiding 7 Project Portfolio Pitfalls

Ten Steps to Comprehensive Project Portfolio Management Part 8 More Tips on Step 10 By R. Max Wideman Benefits Harvesting

Customer retention. Case study. Executive summary. General issue

IBM Cognos Business Intelligence Scorecarding

Industry models for insurance. The IBM Insurance Application Architecture: A blueprint for success

White Paper. Self-Service Business Intelligence and Analytics: The New Competitive Advantage for Midsize Businesses

Government Business Intelligence (BI): Solving Your Top 5 Reporting Challenges

Legal billing and predictive coding A fresh way to assess your legal spend

Make information work to your advantage. Help reduce operating costs, respond to competitive pressures, and improve collaboration.

!!!!! White Paper. Understanding The Role of Data Governance To Support A Self-Service Environment. Sponsored by

Customer Activation. Marketing with a Measurable Purpose

WHITE PAPER OCTOBER Unified Monitoring. A Business Perspective

Developing a Business Analytics Roadmap

Populating a Data Quality Scorecard with Relevant Metrics WHITE PAPER

Creating a Business Intelligence Competency Center to Accelerate Healthcare Performance Improvement

Strategies for optimizing your accounts receivable

Greater visibility and better business decisions with Business Intelligence

The expression better, faster, cheaper THE BUSINESS CASE FOR PROJECT PORTFOLIO MANAGEMENT

Making Business Intelligence Relevant for Mid-sized Companies. Improving Business Results through Performance Management

THE TOP 5 RECRUITMENT KPIs

The Business in Business Intelligence. Bryan Eargle Database Development and Administration IT Services Division

Building a Successful Data Quality Management Program WHITE PAPER

7 Steps to Superior Business Intelligence

The 2-Tier Business Intelligence Imperative

Discover the Power of Automating Your Budget: A Purpose-Built Approach to Business Performance Management

Project Management in the Information Technology Industry

What else could you do with the time you spend on budgeting?

Content Marketing in 2014:

The Ultimate Guide to Buying Business Analytics

5REASONS WHY YOU NEED A CRM

Why Modern B2B Marketers Need Predictive Marketing

ON Semiconductor identified the following critical needs for its solution:

Best Practices for Growing your Mobile App Business. Proven ways to increase your ROI and get your app in the hands of loyal users

Business Intelligence. Using business intelligence for proactive decision making

Sage ERP X3 I White Paper

Big Data for Marketing & Sales: Data Accuracy to Business Impact

Best Practices in Enterprise Data Governance

Lead Scoring. Five steps to getting started. wowanalytics. 730 Yale Avenue Swarthmore, PA

Bringing wisdom to ITSM with the Service Knowledge Management System

The Power of Business Intelligence in the Revenue Cycle

The Ultimate Guide to Buying Business Analytics

CONTACT CENTER REPORTING Start with the basics and build success.

Using Microsoft Business Intelligence Dashboards and Reports in the Federal Government

730 Yale Avenue Swarthmore, PA

KEY PERFORMANCE INDICATORS (KPI) DEFINITION AND ACTION

Industry models for financial markets. The IBM Financial Markets Industry Models: Greater insight for greater value

Scalable Enterprise Data Integration Your business agility depends on how fast you can access your complex data

CRM Dashboard for Square Yards: An Application of Business Analytics

The Executive s CXM Strategy Guide

SALES AND OPERATIONS PLANNING BLUEPRINT BUSINESS VALUE GUIDE

10 TIPS FOR ACCELERATING YOUR PIPELINE

FOR IMMEDIATE RELEASE MAY 5, 2016 ARTIS RELEASES FIRST QUARTER RESULTS: FFO PAYOUT RATIO IMPROVES TO 71.1%

FORGE A PERSONAL CONNECTION

Innovation. Simplifying BI. On-Demand. Mobility. Quality. Innovative

Transcription:

Hipercept Executive Briefing Establishing a Data Governance Program Damien Georges Contents Introduction... 1 Data Governance Defined... 2 Goals of Data Governance... 2 People, Process, Tools, & Information... 3 Elements of a Data Governance Program... 4 Obstacles to Implementation... 6 Recommended Approach... 6 Conclusion... 8 Introduction Executives know the importance of making capital investment to increase their assets value. This year s earnings matter less than the condition of the asset that underpins future earning potential. They also recognize that their human resources, intellectual property and brand equity are important components of their business that must be kept in prime condition in order for the company to thrive. One class of assets that is often overlooked is its data. The information that a company has about its operations, its customers and competitors, along with the systems and processes that allow that information to flow from where it is generated to the people who need it, is not simply plumbing. It can be a potential source of competitive advantage or disadvantage. For example, imagine two landlords with similar buildings consisting of a large number of above-market tenants with upcoming renewals. The landlord who can perceive this trend earlier and move faster to offer competitive early renewal terms to their tenants will fare much better than the other. Over the past few years, there has been a steady rise in awareness of the importance of information assets and the need to develop preventative maintenance plans to keep those assets in good condition. The label that has been given these endeavors is Data Governance. This briefing provides a high level overview of this emerging discipline and describes an approach to implementing Data Governance that we believe will result in success for medium and large companies in real estate or financial services companies. Copyright HIPERCEpt, INC. 1

Data Governance Defined Because the term Data Governance contains the word Data, it is often assumed to be within the purview of Information Technology. However, Data Governance is actually a new and fast-growing discipline within general business management. The term encompasses a broad range of ideas and, in practice, means different things to different people. For the purpose of this briefing, Data Governance is defined as a set of actively-managed standards and practices that enhance the quality and controls the use of information within an organization. Goals of Data Governance The primary goal of implementing a corporate Data Governance program is the same as any other corporate initiative worth undertaking, i.e. to increase net income and shareholder value. This goal is achieved through the two primary benefits of a successful DG program: Primary Benefit 1: Reduced efforts and costs related to generating and using data These cost reductions are realized by, for example: Eliminating duplication of effort involved in maintaining multiple copies of information (for example, in Excel-based databases or spreadmarts ); Reducing the time spent interpreting and reconciling information from different sources in the absence of agreed-upon standards; Reducing the time individuals spend independently verifying the accuracy of information in the absence of trusted data quality procedures; Primary Benefit 2: Increased revenues or reduced costs due to the avoidance of poor decision-making based on stale or inaccurate information. A company s profits are driven by the quality of the decisions made by its employees. Decisions made based on inaccurate information can have a significant negative effect on the company s performance. For example, if a real estate company renews a major lease at a certain rent level based on an inaccurate economic analysis, or a stale pipeline analysis, or a stale prediction of medium-term market rents, that lease will not be as profitable as if had been renewed in the presence of accurate and timely information. The benefits described above are specific to a Data Governance program. Business Intelligence initiatives have other well-known benefits not discussed here. However, because BI solutions depend on the quality of the underlying information, the many benefits of BI cannot be achieved in the absence of a proper Data Governance program. In the following section, we delve deeper into the role that information in general and Data Governance specifically plays within an organization. Copyright HIPERCEPT, INC. 2

Hipercept executive Briefing establishing a Data governance program PeoPle, ProCess, tools, & InformatIon All organizations are characterized by the interaction between four basic elements: people, processes, tools and information. A successful Data Governance program must address the ways in which each of these elements influence information quality. The relationship between each of these elements and information (including the relationship between information and information) is described in this section. PEOPLE PROCESS TOOLS INFORMATION PeoPle People are, of course, the most important part of any organization. People play two major roles when it comes to information: they are information producers and information consumers. Most people play both of these roles with respect to different information or even with respect to the same information at different points in times. People produce information for their own consumption as well as for others and consume information produced by themselves and by others. ProCess The information within an organization is affected by numerous business processes, some of which are performed manually, while others are automated. These processes control the way that information is: Obtained Recorded Edited Validated Retrieved Protected Backed-up Aggregated Interpreted Analyzed Communicated Disposed FIGURE 1 THE FOUR ELEMENTS OF ANY ORGANIZATION Information is both an input to and an output of almost every business process carried out in an organization. Because of this tight interdependency between information and business processes, it is impossible to impact either without impacting the other as well. It is also impossible to achieve good information quality in the absence of quality business processes. copyright Hipercept, inc. 3

Hipercept executive Briefing establishing a Data governance program tools People use a wide variety of tools to carry out the many business processes listed above. There are tools that assist with obtaining and transmitting information (e-mail, RSS, web, FTP, portals), storing and maintaining it (documents, databases, OLTP systems), analyzing it (spreadsheets, OLAP systems), and so on, for each of the processes listed above. Governing the way these tools are used and harnessing their power to automate and control key business processes is an important part of any DG program. InformatIon This final aspect of information within an organization information about information is a little more abstract, but can be explained with an example. If someone says, the area is 103.5, the recipient of this information would need to ask a number of follow-up questions before the meaning became clear: What area is being referred to? How it was calculated? What is the unit of measure? And so on. It makes much more sense to say that the gross leaseable area, including parking, is 103.5 thousand square feet, as of January 24, 2010. Information is only meaningful when it can be interpreted and understood within a clear context. This context is provided by information about information meta information which describes where the information came from, how it was constructed, what time period it is relevant for, how certain it is, and so on. The next section describes how people, process, tools and information correspond to the four basic elements of a data governance program. elements of a data GovernanCe ProGram The core elements of a Data Governance program information stewards, quality procedures, systems of record and standards correspond to the four fundamental elements of organizations discussed above and address the role each of those elements plays in determining the quality of information within an organization. InformatIon stewards Everyone within the organization has a role to play in Data Governance, but a special role is played by the Information Stewards. These are the people who are designated as ultimately accountable for the quality of certain INFORMATION STEWARDS PEOPLE PROCESS TOOLS INFORMATION QUALITY PROCEDURES SYSTEMS OF RECORD DEFINITIONS & STANDARDS FIGURE 2 THE FOUR CORE ELEMENTS OF DATA GOVERNANCE copyright Hipercept, inc. 4

subsets of the organization s information. In addition to being formally accountable, Information Stewards also perform the following important tasks related to the Data Governance program: Lead discussions to define information standards (more on this below) Designate systems of record and define system requirements with respect to information quality Oversee information quality audits Champion process re-engineering projects to improve quality procedures The Information Stewards within an organization are the ultimate owners and drivers of the Data Governance program. Quality Procedures Another key component of any Data Governance program is the set of documented procedures that ensure the consistent execution of business processes that impact information quality. The most important quality procedures control how information is obtained and recorded in the systems of record (defined below) and how the accuracy of that information is validated. While many of the procedures tend to be manual, some can be automated. Wherever possible, manual data entry should be avoided and system controls should be relied on to either prevent or detect errors in data entry. Systems of Record The proliferation of information systems within organizations and the increasing easy and affordability of transmitting and storing large quantities of information has created new challenges for information management. Only a few years ago, key information was housed centrally in file rooms or mainframe servers. Today there is enough disk space and processing power in an individual s desktop computer to allow every employee to maintain their own private versions of huge chunks of key corporate information. Hence a key requirement of Data Governance is that a single system be chosen as the system of record for any single piece of information. Designating an Excel spreadsheet a system of record, while not ideal, should not be ruled out. When it is not possible, in the short-run, to store a particular piece of information in a central database, having a single official spreadsheet is better than having multiple, inconsistent spreadsheets. Definitions and Standards The final core component of Data Governance is the set of standards controlling how information should be generated, interpreted and used. The standards should include, for example: Standard calculations for complex metrics (ex. NOI, FFO, GLA, etc.) Standard lists of values (ex. regions, space types, etc.) Standard sources of external information (ex. for exchange rates - the Bloomberg noon rate) Standards removes uncertainty for the producers and consumers of information by creating a common reference point that everyone can turn to when working with information. Copyright HIPERCEPT, INC. 5

Up to this point we have been concerned with defining what Data Governance is. The following sections discuss the challenges of implementing a Data Governance program and how they can be overcome. Obstacles to Implementation Implementing a Data Governance program is not easy. The first obstacle you will encounter is getting senior management to recognize the need for a Data Governance program. Senior managers often assume that the tasks of looking after the company s data is just part of the job for the many people who play a role in producing, compiling and analyzing the information that eventually finds its way to them as polished final reports (which are usually beautiful but often not very accurate). Gaining buy in is further challenged by the fact that some of the concepts involved can be abstract and esoteric. IT professionals spend much of their lives thinking about data, whereas outside of IT data is largely taken for granted. The next section includes some suggestions for gaining senior management buy in, but even after buy in has been achieved, the challenges of implementing Data Governance can be daunting. As discussed above, a proper Data Governance program will touch many parts of an organization s operations. Data owners must be identified and often changed. Business processes may have to be tweaked or completely re-engineered. Employees who were once able to control data (or maintain their own copies of it) may find themselves having to rely on others or new tools to gain access to that data. Finally, there will almost certainly be major implications for information technology. The scopes of data controlled in existing systems may need to change and new integrations between systems may need to be developed. However, as a rule, Data Governance should always simplify a company s technology platform rather than complicate it. The fact that Data Governance programs tend to be resource-intensive and disruptive to established processes within an organization, along with the fact that benefits often take some time to materialize, means that Data Governance programs often start with strong senior management backing and high expectations, but eventually lose steam as the effort begins to take its toll and senior management s fleeting attention moves on to other initiatives. The next section describes an approach that, if followed, can go a long way towards overcoming these obstacles. Recommended approach This section describes a five stage approach to implementing a Data Governance program that we believe offers the greatest chance of success. Stage 1: Building a Grass Roots Campaign As the champion of Data Governance in your organization, your first task is to educate your colleagues within IT and other parts of the business about what Data Governance is and how the lack of such a program is contributing to the pain they experience daily as they struggle to obtain the information they need to do their jobs. This education will take time, but unfortunately it is not Copyright HIPERCEPT, INC. 6

Hipercept executive Briefing establishing a Data governance program a step that can be skipped. Any attempt to kick off a Data Governance program before there is a solid grass roots campaign behind it, based on a shared understanding of both the problem and the solution, is doomed to fail. If issues around data quality are not even on the radar at your organization, it could take months to build enough momentum to begin. If there is already general acknowledgement of a problem related to data or if there is an influential senior manager who has fully bought in and can drive the initiative from the top, this stage can be completed more quickly. The key output of this stage is the establishment of a Data Governance Steering Group made up of key supporters from IT and as many different areas of the business as possible. STAGE 1: BUILD A GRASS ROOTS CAMPAIGN STAGE 2: DEVELOP AN INFORMATION STRATEGY STAGE 3: IMPLEMENT DEFINITIONAL DATA GOVERNANCE STAGE 4: IMPLEMENT OPERATIONAL DATA GOVERNANCE STAGE 5: AUTOMATE IT! Educate the organization Identify sponsors Identify KPIs required to execute business strategy Prioritize KPIs Designate information stewards Define information standards Design data quality procedures Designate Systems of Record Develop ETL, Reports, Dashboards, etc. FIGURE 3 FIVE-STAGE APPROACH TO IMPLEMENTING DATA GOVERNANCE stage 2: develop a high-level InformatIon strategy Once buy in has been achieved, the next step is to develop a high-level information strategy. Corporate Strategy is the management discipline focused on defining how a company creates economic value by delivering products or services that the market needs. As a rule, strategies are not detailed and can usually be summarized in less than a page. So it should be with your information strategy. Working with the Data Governance Steering Group, identify the Key Performance Indicators that relate directly to your company s economic success. These KPIs should include not only backward looking metrics like gross margin, net income, occupancy, but also forward looking metrics that relate to the drivers of future success. For example, relevant forward-looking KPIs for a real estate company may be things like space absorption rates, area under construction, tenant sales trending, and so on. The key output of this stage is a list of prioritized KPIs. Prioritization is important because, as you move from strategy to execution, you will need to narrow your focus to a few KPIs in order to be able to begin delivering results quickly. stage 3: ImPlement definitional data GovernanCe This is the first stage in the actual execution of a Data Governance program and is focused on the People and Information elements of Data Governance. The first task in this stage is to appoint Data copyright Hipercept, inc. 7

Stewards and define standards related to the KPIs that were deemed to be the highest priority in the stage 2. As described above, the Data Stewards should be those who are deemed to be accountable for the quality of the data and should lead the effort of defining the standards. The key output of this stage is a Data Dictionary setting out the official definitions of the KPIs, how they are calculated, who is responsible for generating them, etc. Stage 4: Implement Operational Data Governance This is where the rubber really hits the road. In this stage, with a good strategy and the solid definitional foundation established in stage 3, you turn your focus to Tools and Processes. This is where many companies begin their Data Governance programs and it may seem like we have taken the long road to get here, but it was all necessary. It is precisely because organizations often jump straight to this stage, without doing the proper groundwork that Data Governance programs so often fail to gain traction. This stage is where most of the hard work is done. Based on the standards defined in stage 3, data quality procedures must be developed to ensure that data is created and used in accordance with the standards. Systems of record must be identified and other systems where the data previously resided must be either decommissioned (many of those rogue Excel spreadmarts will be deleted) or made read-only and set up to import their data from the official systems of record. At the end of this stage, your Data Governance program will be in place and working and you will begin to enjoy the benefits of high quality, reliable data. Stage 5: Automate It! The final stage of a Data Governance program is all about speed and efficiency. With a good Data Governance program in place, IT can more easily automate many of the data manipulation tasks that previously had to remain manual because they were non-standard. Reports that previously needed to be massaged by analysts can now be automatically generated by reporting tools. Where users previously needed to manually enter data into systems because the source could not be trusted, automated integrations can be developed. The many promised benefits of Business Intelligence data mining, predictive analytics, executive dashboards, etc. can begin to be realized. Conclusion In the modern information economy, executives understand that they drive profit by making decisions faster and better than their competition. The ability to make good decisions is dependent upon the state of a company s information assets. Data Governance is to the information worker what industrial design is to the factory worker. The goal of this briefing was to shed some light on what Data Governance is and how it can be implemented it within your organization, irrespective of your organization s size. It can seem a daunting task, but it does not need to be. Leveraging the right approach is critical. Steps cannot be skipped, but you can move through them quickly if senior management support is secured early in the process. Copyright HIPERCEPT, INC. 8

Over the next few years, as companies begin to think of their information assets in the same way they currently think about their financial assets, physical assets and human assets, Data Governance will become a part of every manager s vocabulary. As with previous advances in management, those companies that grasp it first will outperform their competitors. For more information on how Hipercept can help your organization establish a robust Data Governance program, please contact us at info@hipercept.com. Hipercept U.S. 239 Washington Street Suite 305 Jersey City, NJ 07305 Canada 18 Haslemere Road Toronto, Ontario M4N 1X5 ColomBIa Calle 7 SUR # 42 70 Office 209 Medellín, Antioquia Europe 130 Old Street London EC1V 9BD Australia 301 George Street Suite 1102I Sydney, NSW 2000 Copyright HIPERCEPT, INC. 9