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Kelle O'Neal

Thanks for joining our data conversation! This blog is an opportunity to share the real life challenges, opportunities and approaches to improving the quality and value of data in your organization. We will write about everything data related from translating "data" speak into "business" speak, to governance models, to the real differences among the myriad software tools available. But there's one catch: we all have to agree to toss out the fluff. That's right, no 30,000 foot, theoretical strategies that leave you wondering how to execute and actually improve performance. Visit regularly to learn from peers and partners on how they are managing and improving data, and we hope you'll also share your views and experiences.

About the author >

As Founder and Managing Partner of First San Francisco Partners, Kelle O’Neal manages specialist data governance and data management consulting services to complex organizations that deliver faster time to results. Kelle can be reached at kelle@firstsanfranciscopartners.com or through the First San Francisco Partners website.

Follow First San Francisco Partners on Twitter at @1stSanFrancsico.

Editor's Note: Find more articles and resources in Kelle's BeyeNETWORK Expert Channel. Be sure to visit today!


November 2012 Archives

Why should organizational leaders pay attention to big data and big data management? Why must organizational leaders start identifying and assessing opportunities to capture and analyze big data? How do you unlock the value of big data to help your business?

In order to answer these questions, it is important to first look at a few challenges and roadblocks with the current business environment that all start with people, process or technology.

Most organizations today are faced with increasing data volumes and complexity. Data users are demanding quick access and an easy understanding of the data to address timely and important business questions.

Current data analysis technologies and data management structures are inflexible and no longer work in this new era of big data (e.g. they have reached or exceeded their maximum data volume size). Traditional analytical techniques and data management structures are lacking. When it comes to policies and processes, there is a lack of full clarity on data ownership and responsibility, usage and management. Rules and policies to track data security, privacy, retention, consumption and usage are limited.

And today customers are more knowledgeable and sophisticated. They demand organizations understand all their relationships, transactions and interactions across multiple channels. 

Better information is required to compete in this current environment. High quality data is needed for effective decision making and to take action based upon newly revealed insights. Organizations should consider capturing, managing and analyzing big data to solve these business challenges and gain a competitive advantage in the marketplace.

According to research done by McKinsey Global Institute, big data will become a key basis of innovation, competition, productivity and growth. To aggressively compete and gain value from big data, executives must understand and address the implication of big data to the organization.

How does one derive and measure the value an organization could gain by investing in big data management and big data governance? What are the benefits of big data?

According to research done by McKinsey Global Institute, big data creates value in several ways. Organizations can use big data to achieve competitive advantage by harnessing it to perform more complex analyses, which provide an opportunity to find new insights in the data and content. Big data also enables organizations to be more agile with an ability to answer questions that were previously considered beyond reach. Executives and business stakeholders can now make better management decisions based on facts. Big data also enables executives to have more precise forecasts and adjust business levers accordingly because the organization now has the ability to understand every transaction versus analyzing a particular predefined data set from a traditional data warehouse. The insights from big data can truly help to increase operating margins, drive efficiency improvements and productivity gains, and improve customer satisfaction.

Big data can provide unique insights into customer behavior, satisfaction and preferences, allowing organizations to create specific customer segmentations and tailor products and services precisely to meet those needs. Access to this insightful, timely data allows organizations to identify changes in customer behavior quickly and launch targeted customer retention programs or marketing campaigns by creating specific messages or promotions. Organizations can also tailor new or existing products and services to more quickly and precisely meet customer needs.

Big data can enable organizations to identify new growth opportunities by using data obtained from external sources to improve the development of the next generation of products, drive more innovation and be alerted to alternative and additional supplier solutions. For example, manufacturers are using data obtained from the use of their products via social media data to improve the development of the next generation of products and to create innovative service offerings.

The use of big data is becoming a key way for leading organizations to outdo their peers. Executives and senior leadership need to embrace big data as a valuable and competitive asset.

How is big data adding value to your organization? Share with us your success stories!

Posted November 28, 2012 3:59 PM
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As data volumes and complexities continue to grow and as organizations continue to acquire big data, this massive amount of data will be overwhelming without strong data governance. 

Successfully managing big data often requires skill sets and technologies different than those used to manage "regular" data. It may also require a change in business processes. To ensure there is clarity on data access, integration, usage, management and ownership of big data, companies need to start with a big data governance program. 

Adding a governance framework to big data establishes the organization, policies, processes and standards for effectively managing and ensuring the availability, usability, integrity, consistency, auditability and security of big data. Therefore, it is important to expand the scope and vision of your existing data governance program and organization to include big data or, if one does not exist, to establish a data governance program to support your existing enterprise data and your big data. 

The existing FSFP Data Governance Framework, shown below, can be applied to big data to ensure that companies can truly harness and discover valuable insights from their big data. The framework consists of six component areas, which FSFP employs to help you determine a plan and roadmap for incorporating big data governance into your organization.

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To get started with big data governance, the current data governance group within the company needs to think strategically about how to modify/extend the existing data governance structure, policies and processes to include big data. Based on the data governance framework above, the following are examples of how existing data governance components could be extended:

  • Strategy - Refine the existing data governance vision and mission statements, objectives and guiding principles to include big data as a data type. It is also important to articulate the business value, develop a business case and determine potential ROI, and then develop a roadmap/blueprint on how to implement a big data governance strategy.
  • Organization - Extend the operating model to include big data stakeholders (business steward leads, data stewards, steering committee, etc.). The charter, roles and responsibilities, ownership and accountability are also extended to encompass big data governance.
  • Polices, processes and standards (PPS) - Extend PPS to include big data privacy, security, risk, retention, archiving and regulatory compliance and data classification requirements.
  • Measurements - Extend data quality metrics and key performance indicators to include big data completeness, timeliness, accuracy, etc.
  • Technology - Extend data architecture to include big data and data governance technology such as: No SQL distributed processing engines, distributed file systems, advanced analytics and modeling tools, information lifecycle management (ILM) tools, etc. 
This framework is used as a guide to create a big data governance strategy and to develop a plan to execute the strategy (with an agreed upon starting point and steps) and to define the criteria or metrics for success. 

Organizational leaders must start identifying and assessing opportunities to harness big data. They need to have an understanding of the data assets that should be acquired or integrated as well as their priority. It's important to identify potential value creation opportunities and risk, build up internal capabilities to create data driven organizations and address data issues. 

Most importantly, ensure solid alignment between the business and IT groups. In Forrester's most recent Global Big Data Online Survey, 70% of respondents said that big data is or will be a collaborative effort between business and IT. In addition to organizational alignment, executive sponsorship and buy-in for the project is critical. Leaders must understand the value of big data as well as how to unlock this value. You cannot "do" big data management without big data governance. 

The data governance organization needs to ensure that the business stakeholders can trust the data. To ensure the success of big data governance, it is important to first understand the business stakeholder landscape--their needs and requirements--and then assess the potential changes required. What type of big data do they require? What are the sources? How often should the data be provided? Start with small changes and iterations and build on success rather than taking an all-or-nothing approach. Really know your data--what data is private? Public? Proprietary? And be sure to define big data governance requirements sooner than later. In order to measure the success and value of a big data governance programs, you need to clearly define measurable success criteria and then put processes in place to measure it over time.  

Business users need accurate, clean, timely data about their prospects, customers, competition, etc. to meet business objectives and goals. Without a data governance foundation for small and big data, people often find themselves in a reactive mode when it comes to solving data related issues. big data governance will help ensure business users are getting the data they need while also mitigating the pain points and challenges associated with big data. So when you're not sure where to start with big data, be sure to start with a big data governance strategy and plan.


Posted November 12, 2012 7:26 PM
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