Tag Archives: Data Governance

Best Kept Secrets for Successful Data Governance

data governance

Best Kept Secrets for a Successful Data Governance

If you’ve spent some time studying and practicing data governance, you would agree that data governance is a challenging yet rewarding endeavor.  Across industries, a growing number of organizations have put data governance programs in place so they can more effectively manage their data to drive the business value. But the reality is, data governance is a complex process, and most companies practicing data governance today are still at the early phase of this very long journey.  In fact, according to the result from over 240 completed data governance assessments on http://governyourdata.com/, a community website dedicated to everything data governance, the average score for data governance maturity is only 1.6 out of 5. It’s no surprise that data governance was a hot topic at last week’s Informatica World 2015.  Over a dozen presentations and panel discussions on data governance were delivered; practitioners across various industries shared their real-world stories on topics ranging from how to kick-start a data governance program, how to build business cases for data governance, frameworks and stewardship management, to the choice of technologies.  For me, the key takeaways are:

  1. Old but still true – To do data governance the right way, you must start small and focus on achieving tangible results. Leverage the small victories to advance to the next phase.
  1. Be prepared to fail more than once while building a data governance program. But don’t quit, because your data will not.
  1. Why doesn't it fit?!One-size doesn’t fit all when it comes to building a data governance framework, which is a challenge for organizations, as there is no magic formula that companies can immediately adopt. Should you build a centralized or federated data governance operation? Well, that really depends on what works within your existing environment.
    In fact, when asked “what’s the most challenging area for your data governance effort” in our recent survey conducted at Informatica World 2015, “Identify roles and responsibilities” got the most mentions. Basic principle? – Choose a framework that blends well with your company‘s culture.
  1. pptLet’s face it, data governance is not an IT project, nor is it about fixing data problems. It is a business function that calls for people, process and technology working together to obtain the most value from your data. Our seasoned practitioners recommend a systematic approach: Your first priority should be people gathering – identifying the right people with the right skills and most importantly, those who have a passion for data; next is figuring out the process. Things to consider include: What’s the requirement for data quality? What metrics and measurements should be used for examining the data; how to handle exceptions and remediate data issues? How to quickly identify and apply security measures to the various data sets?  Third priority is selecting the right technologies  to implement and facilitate those processes to transform the data so it can be used to help meet  business goals.
  1. Business & IT Collaboration“Engage your business early on” is another important tip from our customers who have achieved early success with their data governance program. A data governance program will not be sustainable without participation from the business. The reason is simple – the business owns the data, they are the consumers of the data and have specific requirements for the data they want to use. IT needs to work collaboratively with business to meet those requirements so the data is fit for use, and provides good value for the business.
  1. Scalability, flexibility and interoperability should be the key considerations when it comes to selecting data governance technologies. Your technology platform should be able to easily adapt to the new requirements arising from the changes in your data environment.  A Big Data project, for example, introduces new data types, increased data speed and volume. Your data management solution should be agile enough to address those new challenges with minimum disruption to your workflow.

Data governance is HOT! The well-attended sessions at Informatica World, as well as some of our previously hosted webinars is testimony of the enthusiasm among our customers, partners, and our own employees on this topic. It’s an exciting time for us at Informatica because we are in a great position to help companies build an effective data governance program. In fact, many of our customers have been relying on our industry-leading data management tools to support their data governance program, and have achieved results in many business areas such as meeting compliance requirements, improving customer centricity and enabling advanced analytics projects. To continue the dialogue and facilitate further learning, I’d like to invite you to an upcoming webinar on May 28, to hear some insightful, pragmatic tips and tricks for building a holistic data governance program from industry expert David Loshin, Principal at Knowledge Integrity, Inc,  and Informatica’s own data governance guru Rob Karel.

Get Ready!

Get Ready!

“Better data is everyone’s job” –  well said by Terri Mikol, director of Data Governance at University of Pittsburgh Medical Center.  For companies striving to leverage data to deliver business value, everyone within the company should treat data as a strategic asset and take on responsibilities for delivering clean, connected and safe data. Only then can your organization be considered truly “Data Ready”.

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Data Governance Maturity at Your Organization?

Data Governance

Data Governance Maturity

If you are a Healthcare provieder, having a complete view of your member’s data will improve your service. The more detail you have on each member, the more effective you can be at providing the service they deserve.

It is probable that all of the information on a member is stored in several different systems – so getting the complete picture can be difficult. In addition – controlling access to this information is an important part of any organization’s overall strategy. And finally – data assets become more valuable the more you use them. If three divisions of an organization all share information about their interactions with a customer, the organization as a whole is better able to service the customer, at lower cost and with high customer satisfaction.

Data governance is used by organizations to exercise control over processes and methods used by their data stewards and data custodians in order to improve data quality. Data governance is a control that ensures that the data entry by an operations team member or by an automated process meets precise standards, such as a business rule, a data definition and data integrity constraints in the data model. A data governor uses data quality monitoring against production data to communicate errors in data back to operational team members, or to the technical support team, for corrective action.

How far along in the Data Governance journey is your organization?

  1. Is your organization currently unaware of Data Governance?

There is minimal focus on data quality or security, data isn’t prioritized in any meaningful or actionable way, there is no measurement around data governance and it isn’t managed.

  1. Is your organization in the initial phases of Data Governance?

Data Governance is primarily grassroots driven by a few passionate individuals, rules are implemented in an ad hoc fashion, with policies or standards are part of functional requirements in an IT project, which is only considered successful if the IT release is considered successful.

  1. Is Data Governance at your organization repeatable?

For these organizations – data governance is still grassroots, but gaining attention at the IT management level. There are documented IT governance and standards driving metadata resuse and improved collaboration across IT projects. The success is measured primarily on improved IT efficiencies. This is typically managed through a pilot project.

  1. Defined Data Governance

This is lead primarily from senior IT through adoption of competency centers and centers of excellence. Project leadership is primarily through IT, but there is business involvement. The success is measured on operational metrics at a project level.

  1. Data Governance that is Managed

The Data Governance program is sponsored by business leaders, initiated as part of a broader strategic enterprise information management program. Data Governance will live through multi-phase, multi-year efforts but measured based on the success of the program.

  1. Optimized Data Governance

There is top-level executive sponsorship and support. Data governance is embraced as a self-sustaining core business function managing data as a corporate asset. Success is measured on the total impact to the business, not just confined to specific programs or strategies.

There is a fantastic site (http://governyourdata.com/ ) that is an open peer-to-peer community of data governance practitioners, evangelists, thought leaders, bloggers, analysts and vendors. The goal of the governyourdata community is to share best practices, methodologies, frameworks, education, and other tools to help data governance leaders succeed in their efforts.

One of our customers, UPMC has a great blog post on their implementation of a Data Governance council and the challenges they faced making it a priority in their organization.

To figure out where on the continuum of data governance maturity – there is a Data Governance Maturity Assessment Tool through the governyourdata.com site. A maturity assessment level sets current gaps and strengths and paves the way for defining a successful strategy. The process of assessing an organization’s maturity should include interviews of relevant business and IT staff, business risk surveys, business analyst time and activity analysis, and other techniques. Once your assessment is completed – you can identify the appropriate steps you need to plan for to develop an Optimized Data Governance approach for your organization. Where does your organization stand?

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Becoming A Data Ready Enterprise

What is a Data Ready Enterprise?

One that is able to treat data as a strategic asset throughout the organization. One that invests in its enterprise architecture to build a foundation of data ‘readiness’. One that incorporates data into its culture and uses it to drive high performance teams.

Data Drives Profit

In a recent research study, ’Data drives profit in a data-ready enterprise’, more than half of respondents agreed that ‘An effective data strategy can be a competitive advantage for companies’. Yet less than 25% of those same respondents stated ’Our data management is good enough to satisfy our current needs’.

So we know that data is important – yet are we challenged in creating a data ready culture? Are we really only mediocre at best when it comes to managing data? With digital transformation initiatives in full swing (or behind us for those movers and shakers) and our key business processes automated, how do we pivot from focusing on the application to focusing on the data? It starts with defining business strategies at the top and building capabilities throughout necessary to become data ready.

What are the unique business strategies and capabilities required to be data-ready?

In most enterprises, there is a function that focuses specifically on the corporate strategy typically as part of a C-Suite. In order to transform to the data ready enterprise, this function will need to define policies, corporate goals and initiatives that focus the rest of the organization to adopt data management best practices and drive necessary change. This may even include creating an organization dedicated to the organization’s data management function and capabilities with a leader, such as a Chief Data Officer, who may not necessarily report to the CIO.

In order to make key business decisions based on a data-ready framework, organizations should leverage their enterprise architecture teams to identify data assets that are required to support each business function’s needs. Once those assets have been identified, key capabilities – such as data quality, data integration, mastering data, and data governance – need to be developed and matured.  Rather than boiling the ocean, start with a key business initiative that would benefit the most from a focus on the data itself.

How do you get started?

If your organization is just starting on its transformational journey to becoming a data ready enterprise, focus on one or two key business initiatives that will significantly benefit from a data ready framework. For example, most Informatica customers start with one business initiative, such as ‘Total Customer Experience’ or ‘Next Generation Analytics’, to build their data ready organizational capabilities. By leveraging the enterprise architecture team, identify common requirements and technologies that can be leveraged across multiple initiatives, and focus on quick wins. Here is where an Intelligent Data Platform approach can offer significant value over point solutions or projects (deploy once, leverage everywhere).

If you are at the very beginning just trying to get support for why this transformation is critical for your business, download the ‘Data drives profit in the data ready enterprise’ ebook. If your executive management team agrees and is looking for how to get started, download the ‘How to organize the data ready enterprise’ ebook.

It’s time to get ready – data-ready!

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Put Yourself Ahead of Digital Transformation Curve – Informatica World 2015

The rapid advancement we are seeing in social, mobile and other digital technologies have transformed the way of our life significantly. My commute to airport for business travel takes three taps on an app on my smart phone and a leading retailer I shop frequently, knows what I like, which product I have put on the cart using my iPad, which products I “liked” on their social channels so they can do real-time recommendations while I am at their physical store. Their employees are now armed with information that is integrated in ways that empower them be more customer-centric than ever before.

All these rapid changes just over a decade are bought to us by companies that pioneered the digital transformation and data is at the center of this revolution. These organizations gained competitive advantage from social, mobile, analytics, cloud, and internet of things technologies. In a world filled with data of different variety, volume and velocity, it’s more important for organizations to become data-ready. While the potential for insight in big data is massive, we need a new generation of Master Data Management to realize all the potential.

In the contrast of this rapid change fueled by data, growing number of companies are realizing that they now have a massive opportunity in front of them. At the centers of this digital transformation is master data that provides an opportunity for organizations to:

  • Better understand customers, their household and relationships so they can do effective cross-sell and up-sell
  • Identify customers interacting with company via different channels so they can push relevant offer to these customers in real time.
  • Offer better product recommendations to customers based on their purchasing and browsing behavior
  • Optimize the way they manage their inventory leading to significant cost savings
  • Manage supplier relationships more effectively so they can negotiate better rate
  • Provide superior patient care and cure harmful deceases at early stage by creating patient-centric solutions that connect health information from more and more sources
  • Master wellhead and other upstream exploration and production assets so they can do better crew allocation and production planning
  • Be compliant to complex and ever changing government regulations leading to significant savings in terms of fines and punishments

We will talk about all this and more at Informatica World 2015 which is happening next week in Las Vegas. Join us for the MDM Day on May 12 followed by Information Quality and Governance track sessions on May 13 and 14. Register now.

We have 37 sessions that cover Master Data Management, Omnichannel Commerce, Data Quality, Data as a Service and Big Data Relationship Management. You get a chance to learn from Informatica’s customers about their experience, best practices from our partners and our vision and roadmap straight from our product management team. We will also talk about master data fueled Total Customer Relationship and Total Supplier Relationship applications that leverage our industry leading multidomain MDM platform.

Informatica world 2015

Here is your guide to sessions that will be covered. I will see you there. If you want to say hello in person, reach out to me at @MDMGeek and follow @InfaMDM twitter handle for all the latest news. The hash tag for this event is #INFA15


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Healthcare at Informatica World 2015

Healthcare at Informatica World 2015

Informatica World 2015

If you follow me on LinkedIn than you already know that there is no place I would rather be than in front of a client – virtually or in person. There is simply nothing that energizes me more than gathering the insights from client advocates. With this said, it will be no surprise that Informatica World makes me giddy; like a kid in a candy store – over 1500 clients telling their stories and sharing valuable lessons learned.

For healthcare alone, over a dozen payer and provider organizations have volunteered to share their use cases, their stories and their lessons learned. The array of brands represented is second to none; i.e. Kaiser, UPMC, Cleveland Clinic and Humana.

Beyond sessions, clients ask for more opportunities to network with peers and get hands on with the next releases of products and we listen!

  • Healthcare cocktail reception Tuesday evening
  • Healthcare Industry breakfast Thursday morning
  • Hands on Labs with industry specific content
  • Partner technology showcase

A complete list of healthcare sessions + a few you hot topic sessions is below. I look forward to seeing you in Las Vegas next week!

Informatica World 2015 - Healthcare

Informatica World 2015 – Healthcare














Informatica World 2015 - Healthcare

Informatica World 2015 – Healthcare


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What is the Best Way to Implement an MDM solution? One Bite at a Time

You know that old saying, “What’s the best way to eat an elephant?” “One bite at a time.”


Best Way to Implement an MDM solution? One Bite at a Time

Much like the daunting task of eating an elephant, implementing an MDM solution can seem staggering. Many times, the implementation team gets mired in the details, wanting to create a solution that is the answer to everyone’s problems and as a result never gets started due to the overwhelming nature of the undertaking. After many successful MDM implementations – I’d like to recommend the following approach to eating your elephant:

  •  Clearly establish the business problem you are trying to solve

According to the Gartner Group, “MDM is a business-driven, technology-enabled environment and program.” It is really important to remember that the reason you are working on an MDM project is to satisfy a specific business need aligned with the overall business strategy. Once aligned – it is easier to show value to the organization when it is successfully implemented.

For instance – if you want to reduce readmission costs for a specific segment of your member population, this could have an impact on several potential business goals in the payer market including improving customer satisfaction and lowering cost of care for specific populations. Improving customer satisfaction is a pretty big elephant – but focusing down on reducing readmission costs is much more manageable. And it will impact two of your business ! Sutter Health has taken this approach and is releasing new use cases every 90 days.

  •  Understand and document your current state

Now that you know what problem you are attempting to solve – you will need to understand the current level of maturity of your current approach and the resources it will take to implement your solution. You will need to consider your available resources, understand the amount of time and money it may take to implement a solution, and obtain visibility into where your organization stands currently in regards to the .

Using the readmission example – you are going to need to identify where readmission data is available. How often is this data updated? What is the quality of the data? How difficult is it to get access to the data? Who are the resources that are responsible for readmission data? Are they distracted by many competing requests? What are some of the data sources that could impact readmission rates that are not currently part of your data sources? For instance – understanding the living arrangement of the member prior to discharge can have an impact on readmission rates (members living alone have a much higher readmission rate than those living with others). If you can identify a household through social media data, you can better predict who will be going home alone.

  • Clearly define success

There is business adage (much like eating an elephant!) that says “you can’t manage what you can’t measure.” Before you implement your MDM solution – you need to identify what metrics are most important and show success. These should align with the goals you set in #1 (which should align with the goals of the business). You should also identify specific business outcomes that metrics can apply to.

What would be a reasonable measure of success for reduction of readmission rates?

  • Moving from a 15% readmission rate to an 8% readmission rate?
  • Moving from a 15% readmission rate to a 10% readmission rate? In what amount of time?
  • Perhaps moving from a 15% readmission rate to a 13% readmission rate in a year after implementation?
  1. Build a governance hierarchy

According to Gartner Group, “Governance is about decision making and ensuring that you have an authority framework that takes decisions and is able to measure the execution of those decisions.” An effective governance program requires a well-defined hierarchy, headed by a sponsor — someone in a position of authority who carries the necessary weight and cross-departmental authority to make MDM governance a reality. How can you find out how mature your organization is from a data governance perspective? There are several vendors and websites that can help with that including: www.governyourdata.com .

You need to be able to make assessments about the quality of the source data, the data lineage (where and how the data that is feeding your MDM solution has been modified) for compliance reporting requirements, as well as establishing a process for support of your data quality. There are 10 data governance insights from UPMC here.

Now – what is the smallest bite you can define for your organization? By laying out your business priorities, identifying your current state, creating a measurable goal and a method for governing – you have put clear boundaries on what you are trying to accomplish. Once you’ve established your credibility on your ability to finish your first bite successfully, the next bite will be easier!

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CIOs: Being an Effective Data Custodian

Data and Information becoming a key corporate asset

Data and Information

Data and Information Becoming a Key Corporate Asset

According to Barbara Wixom at MIT CISR, “In a digital economy, data and the information it produces is one of a company’s most important assets”. (“Recognizing data as an enterprise asset”, Barbara Wixom, MIT CISR, 3 March 2015). Barbara goes onto suggest that businesses increasingly “need to take an enterprise view of data. They should understand and govern data as a corporate asset, even when data management remains distributed”.

CIOs are not the enterprise data steward


CIOs are Not the Enterprise Data Steward

Given that data is a corporate asset, you might expect this would be an area for the CIO’s leadership. However, I heard differently when I recently met with two different groups of CIOs. Regardless of whether the CIOs were public sector or private sector, they told me that they did not want to be the owner of enterprise data. One CIO succinctly put it this way, “we are not data stewards. Governance has to be done by the business—IT is merely the custodians of their data”. These CIOs claim that the reason that the business must own business data and must determine how that data should be managed is because only the business understands the business context around the data.

Given this, the CIOs that I talked to said that IT should not manage data but “should make sure that what the business needs done gets done with data”. CIOs, therefore, own the processes and technology for ensuring data is secured and available when and where the business needs it. Debbie Lew from ISACA put it this way, “IT does not own the data. IT facilitates data”.

So if the management of data is distributed what is the role of the CIO in being a good data custodian?

COBIT 5 provides some concrete suggestions that are worth taking a look at. According to COBIT, IT should make sure information and data owners are established and that they are able to make decisions about data definition, data classification, data security and control, and data integrity. Additionally, IT needs to ensure that the information system provides the “knowledge required to support all staff in their work activities.”

IT must create facilities so knowledge can be used

This means IT organizations need to create facilities so that knowledge can be used, shared and updated. Part of doing this task well involves ensuring the reliable availability of useful information. This should involve keeping the ratio of erroneous or unavailable information to a minimum. Measuring performance here requires looking at the percent of reports that are not delivered on time and the percent of reports containing inaccuracies. These obviously need to be kept to a minimum. Clearly, this function is enabled by backup systems, applications, data and documentation. These should be worked according to a defined schedule that meets business requirements.

To establish a level of data accuracy, that is acceptable to business users, starts by building and maintaining an enterprise data dictionary that includes details about the data definition, data ownership, appropriate data security, and data retention and destruction requirements. This involves identifying the data outputs from the source and mapping data storage, location, retrieval and recoverability. It needs to ensure from a design perspective, appropriate redundancy, recovery and backup are built into the enterprise data architecture.


IT Must Enable Compliance and Security

IT must enable compliance and security

COBIT 5 stresses the importance of data and information compliance and security. Information needs to be “properly secured, stored, transmitted or destroyed.”  This starts with effective security and controls over information systems. To do this, procedures need to be defined and implemented to ensure the integrity and consistency of information stored in databases, data warehouses and data archives. All users need to be uniquely identifiable and have access rights in accordance with their business role. And for business compliance, all business transactions need to be retained for governance and compliance reasons.  According to COBIT 5, IT organizations are chartered to ensuring the following four elements are established:

  • Clear information ownership
  • Timely, correct information
  • Clear enterprise architecture and efficiency
  • Compliance and security

There needs to be a common set of information requirements


There Needs to be a Common Set of Information Requirements

But how are these objectives achieved? Effective information governance requires that the business and IT have a strong working relationship. It, also, requires that information requirements are established. Getting timely and correct information often starts by improving how data is managed. Instead of manually moving data or creating layer over layer of spaghetti code integration, enterprises need to standardize a data architecture that creates a single integration layer among all data sources.

This integration layer increasingly needs to support new sources of data too and be able to do so at the speed of business. Business users want trustworthy data. An expert on data integration “maintains that at least 20 percent of all raw data is incorrect. Inaccurate data leads data users to question the information their systems provide.”  The data system needs to automatically and proactively fix data issues like addresses, missing data and data format problems. And once this has been accomplished, it needs to go after redundancies in customers and transactions. With multiple IT-managed transaction systems, it is easy to misstate both customers and customer transactions. It is also possible to miss potential business opportunities. All of these are required to get accurate data.

Data needs to be systematically protection


Data Needs to be Systematically Protection

Additionally, data need to be systematically protected. This means that user access to data needs to be managed systematically across all IT-managed systems. Typical data integrations move data between applications without protecting the source data systems’ rules. A data security issue at any point in the IT system can expose all data. At the same time, enterprises need to control exactly what data are moved in test environments and product environments. Enterprises must also ensure that a common set of security governance rules are established and maintained across the entire enterprise, including data being exchanged with partners, employees and contractors using data outside of the enterprise firewall.

Parting remarks

Clearly, COBIT 5 suggests that CIOs cannot completely divorce themselves from data governance. Yes, CIOs are data custodians but there are clear and specific tasks that the CIO and their staff must uniquely take on. Otherwise, a good foundation for data governance cannot be established.

Related Blogs

Good Corporate Governance Is Built Upon Good Information and Data Governance

Twitter: @MylesSuer

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Regulation Ready: People, Processes and Technology, oh my!

Regulation Ready

Regulation Ready

Data Governance, the art of being Regulation Ready is about a lot of things, but one thing is clear. It’s NOT just about the technology. You ever been in one of those meetings, probably more than a few, where committees and virtual teams discuss the latest corporate initiatives? You know, those meetings where you want to dip your face in lava and run into the ocean? Because at the end of the meeting, everyone goes back to their day jobs and nothing changes.

Now comes a new law or regulation from the governing body du jour. There are common threads to each and every regulation related to data. Laws like HIPAA even had entire sections dedicated to the types of filing cabinets required in the office to protect healthcare data. And the same is true of regulations like BCBS 239, CCAR reporting and Solvency II. The laws ask; what are you reporting, how did you get that data, where has it been, what does this data mean and who has touched it. Virtually all of the regulations dealing with data have those elements.

So it behooves an organization to be Regulation Ready. This means those committees and virtual teams need to be driving cultural and process change. It’s not just about the technology; it’s as much about people and processes. Every role in the organization, from the developer to the business executive should embed the concepts of data governance in their daily work. From the time a developer or architect builds a new system, they need to document and define everything and every piece of data. It reminds me of days writing code and remembering to comment each code block. And the business executive likewise is sharing business rules and definition from the top so they can be integrated into the systems that eventually have to report on it.

Finally, the processes that support a data governance program are augmented by the technology. It may seem to suffice, that systems are documented in spreadsheets and documents, but those are more and more error prone and in the end not reliable in audit.

Informatica is the market leader in data management infrastructure to be Regulation Ready. This means, everything, from data movement and quality to definitions and security. Because at the end of the day, once you have the people culturally integrated, and the processes supporting the data workload, a centralized, high performance and feature rich technology needs to be in place to complete the trifecta. Informatica is pleased to offer the industry this leading technology as part of a comprehensive data governance foundation.

Informatica will be sharing this vision at the upcoming Annual FIMA 2015 Conference in Boston from March 30 to April 1. Come and visit Informatica at FIMA 2015 in Booth #3.

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IT Leadership Group Discusses Governance and Analytics

business leaders

IT Leadership Group Discusses Governance and Analytics

I recently got to talk to several senior IT leaders about their views on information governance and analytics. Participating were a telecom company, a government transportation entity, a consulting company, and a major retailer. Each shared openly in what was a free flow of ideas.

The CEO and Corporate Culture is critical to driving a fact based culture

I started this discussion by sharing the COBIT Information Life Cycle. Everyone agreed that the starting point for information governance needs to be business strategy and business processes. However, this caused an extremely interesting discussion about enterprise analytics readiness. Most said that they are in the midst of leading the proverbial horse to water—in this case the horse is the business. The CIO in the group said that he personally is all about the data and making factual decisions. But his business is not really there yet. I asked everyone at this point about the importance of culture and the CEO. Everyone agreed that the CEO is incredibly important in driving a fact based culture. Apparent, people like the new CEO of Target are in the vanguard and not the mainstream yet.

KPIs need to be business drivers

The above CIO said that too many of his managers are operationally, day-to-day focused and don’t understand the value of analytics or of predictive analytics. This CIO said that he needs to teach the business to think analytically and to understand how analytics can help drive the business as well as how to use Key Performance Indicators (KPIs). The enterprise architect in the group shared at this point that he had previously worked for a major healthcare organization. When organization was asked to determine a list of KPIs, they came back 168 KPIs. Obviously, this could not work so he explained to the business that an effective KPI must be a “driver of performance”. He stressed to the healthcare organization’s leadership the importance of having less KPIs and of having those that get produced being around business capabilities and performance drivers.

IT needs increasingly to understand their customers business models

I shared at this point that I visited a major Italian bank a few years ago. The key leadership had high definition displays that would roll by an analytic every five minutes. Everyone laughed at the absurdity of having so many KPIs. But with this said, everyone felt that they needed to get business buy in because only the business can derive the value from acting upon the data. According to this group of IT leaders, this causing them more and more to understand their customer’s business models.

Others said that they were trying to create an omni-channel view of customers. The retailer wanted to get more predictive. While Theodore Levitt said the job of marketing is to create and keep a customer. This retailer is focused on keeping and bringing back more often the customer. They want to give customers offers that use customer data that to increase sales. Much like what I described recently was happening at 58.com, eBay, and Facebook.

Most say they have limited governance maturity

We talked about where people are in their governance maturity. Even though, I wanted to gloss over this topic, the group wanted to spend time here and compare notes between each other. Most said that they were at stage 2 or 3 in in a five stage governance maturity process. One CIO said, gee does anyone ever at level 5. Like analytics, governance was being pushed forward by IT rather than the business. Nevertheless, everyone said that they are working to get data stewards defined for each business function.  At this point, I asked about the elements that COBIT 5 suggests go into good governance. I shared that it should include the following four elements: 1) clear information ownership; 2) timely, correct information; 3) clear enterprise architecture and efficiency; and 4) compliance and security. Everyone felt the definition was fine but wanted specifics with each element. I referred them and you to my recent article in COBIT Focus.

CIO says they are the custodians of data only

At this point, one of the CIOs said something incredibly insightful. We are not data stewards. This has to be done by the business—IT is the custodians of the data. More specifically, we should not manage data but we should make sure what the business needs done gets done with data. Everyone agreed with this point and even reused the term, data custodians several times during the next few minutes.  Debbie Lew of COBIT said just last week the same thing. According to her, “IT does not own the data. They facilitate the data”. From here, the discussion moved to security and data privacy. The retailer in the group was extremely concerned about privacy and felt that they needed masking and other data level technologies to ensure a breach minimally impacts their customers. At this point, another IT leader in the group said that it is the job of IT leadership to make sure the business does the right things in security and compliance. I shared here that one my CIO friends had said that “the CIOs at the retailers with breaches weren’t stupid—it is just hard to sell the business impact”. The CIO in the group said, we need to do risk assessments—also a big thing for COBIT 5–that get the business to say we have to invest to protect. “It is IT’s job to adequately explain the business risk”.

Is mobility a driver of better governance and analytics?

Several shared towards the end of the evening that mobility is an increasing impetus for better information governance and analytics.  Mobility is driving business users and business customers to demand better information and thereby, better governance of information. Many said that a starting point for providing better information is data mastering. These attendees felt as well that data governance involves helping the business determine its relevant business capabilities and business processes. It seems that these should come naturally, but once again, IT for these organizations seems to be pushing the business across the finish line.

Additional Materials

Solution Page:

Corporate Governance

Data Security

Governance Maturity Assessment Tool

Blogs and Articles:

Good Corporate Governance Is Built Upon Good Information and Data Governance

Using COBIT 5 to Deliver Information and Data Governance





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Building an Impactful Data Governance – One Step at a Time

Let’s face it, building a Data Governance program is no overnight task.  As one CDO puts it:  ”data governance is a marathon, not a sprint”.  Why? Because data governance is a complex business function that encompasses technology, people and process, all of which have to work together effectively to ensure the success of the initiative.  Because of the scope of the program, Data Governance often calls for participants from different business units within an organization, and it can be disruptive at first.

Why bother then?  Given that data governance is complex, disruptive, and could potentially introduce additional cost to a company?  Well, the drivers for data governance can vary for different organizations.  Let’s take a close look at some of the motivations behind data governance program.

For companies in heavily regulated industries, establishing a formal data governance program is a mandate.  When a company is not compliant, consequences can be severe. Penalties could include hefty fines, brand damage, loss in revenue, and even potential jail time for the person who is held accountable for being noncompliance. In order to meet the on-going regulatory requirements, adhere to data security policies and standards, companies need to rely on clean, connected and trusted data to enable transparency, auditability in their reporting to meet mandatory requirements and answer critical questions from auditors.  Without a dedicated data governance program in place, the compliance initiative could become an on-going nightmare for companies in the regulated industry.

A data governance program can also be established to support customer centricity initiative. To make effective cross-sells and ups-sells to your customers and grow your business,  you need clear visibility into customer purchasing behaviors across multiple shopping channels and touch points. Customer’s shopping behaviors and their attributes are captured by the data, therefore, to gain thorough understanding of your customers and boost your sales, a holistic Data Governance program is essential.

Other reasons for companies to start a data governance program include improving efficiency and reducing operational cost, supporting better analytics and driving more innovations. As long as it’s a business critical area and data is at the core of the process, and the business case is loud and sound, then there is a compelling reason for launching a data governance program.

Now that we have identified the drivers for data governance, how do we start?  This rather loaded question really gets into the details of the implementation. A few critical elements come to consideration including: identifying and establishing various task forces such as steering committee, data governance team and business sponsors; identifying roles and responsibilities for the stakeholders involved in the program; defining metrics for tracking the results.  And soon you will find that on top of everything, communications, communications and more communications is probably the most important tactic of all for driving the initial success of the program.

A rule of thumb?  Start small, take one-step at a time and focus on producing something tangible.

Sounds easy, right? Think this is easy?!Well, let’s hear what the real-world practitioners have to say. Join us at this Informatica webinar to hear Michael Wodzinski, Director of Information Architecture, Lisa Bemis, Director of Master Data, Fabian Torres, Director of Project Management from Houghton Mifflin Harcourt, global leader in publishing, as well as David Lyle, VP of product strategy from Informatica to discuss how to implement  a successful data governance practice that brings business impact to an enterprise organization.

If you are currently kicking the tires on setting up data governance practice in your organization,  I’d like to invite you to visit a member-only website dedicated to Data Governance:  http://governyourdata.com/. This site currently has over 1,000 members and is designed to foster open communications on everything data governance. There you will find conversations on best practices, methodologies, frame works, tools and metrics.  I would also encourage you to take a data governance maturity assessment to see where you currently stand on the data governance maturity curve, and compare the result against industry benchmark.  More than 200 members have taken the assessment to gain better understanding of their current data governance program,  so why not give it a shot?



Data Governance is a journey, likely a never-ending one.  We wish you best of the luck on this effort and a joyful ride! We love to hear your stories.

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