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Topic:

The Data Excellence Management System DEMS “an alternative future”

Abstract:

As trivial as it may sound today, 100 years ago companies from all industries elected electricity experts on their senior management team to guide the assimilation of this new and disruptive technology. Like electricity production and delivery at the turn of the beginning of last century, data is now changing the way business is being done. Today, organizations from all sectors are looking at data from an executive standpoint and exploring how to embrace data governance as a core business function.

As electricity enabled companies to scale their operations, businesses around the globe are trying to harness the volume, velocity and variety of data to maximize their business activities. Nevertheless—as Google, Apple, Facebook, and Alibaba have shown the world—companies must not only incorporate data into various lines of business, but in fact to be successful in increasingly competitive and regulated industries, companies must consider data as the motor force of their corporate value and treat these like an enterprise asset.

Banks, insurances companies and brokerage firms are being strangled. On the one hand they are required to comply with stringent legal requirements. On the other they are confronted by an ever-growing volume, velocity and complexity of data, which enhances their vulnerability to sanctions, security threats and analysis inaccuracies. This “twin tsunami” of legal and technical disruption brings about a series of questions that traditional models for managing risk and compliance requirements cannot answer.

The objective of this session is to present the data excellence management system and methodology as an alternative future to the age of ERP, MDM, and Business Intelligence. In order to succeed in the information age, financial institutions, governments and industries need to align

  • Business,
  • Data,
  • and IT processes into one single direction, and govern data across ERP and BI/DW.

In other words, a global, top-down, collaborative approach to data management is necessary for growth and sustainability.

You will learn at the end of the session:

What is the Data Governance role?

Data Governance (DG) builds upon the natural convergence between MDM, ERP and BI to create a single, fit-for-the-purpose view that emphasizes the enterprise’s global data ecosystem across sources. Data Governance in fact reconciles IT processes and business objectives by specifying the framework for decisions’ rights and accountabilities so as to encourage desirable behavior in the use and correction of data. DG encompasses people, policies, procedures and technologies to enable an organization to leverage data as an enterprise asset. Well-implemented DG should:

  • Ensure data meets business needs,
  • Protect, manage and develop data to lower management costs,
  • Eliminate the profits loss associated with predictable impact,
  • Reduce operational friction and increase consensus,
  • Secure a common approach to data management,
  • Integrate compliance controls of policies, standards, and procedures,
  • Oversee the delivery of data management projects and services.

How does Valorization Enforce Priorities?

The exponential growth of data volume, velocity and complexity is bringing about the question of priority. Since the number of records increases daily, and error reports directly follow the same rate of growth, the question of what data are the most crucial becomes fundamental and requires a new and broader notion of how we define “value.”

Distancing from the conventional wisdom of value as being a monetary unit and cost effectiveness coefficient, value takes on a broader function. It becomes the meeting point between an objective and its actual measure within a system.

In order to establish an efficient and fluid organization, a hierarchy of priorities’ value must be assigned to each resource involved in a desired outcome. This value is to be defined upon consensus and will become the missing link between objectives and transactions.

How to Govern Risk and Compliance by Value?

Using this approach, a risk will essentially become the potential for non-realization of the enterprises value objectives; something that will in turn be valued and governed predicatively. Using this approach and the appropriate system a company will be capable of visually monitoring and evaluating both risk (the faults that drive loss of value) and impact (the amount of value that will be lost) before it actually impacts the business. Govern by value will bring about a revolution in risk and compliance management.

For years financial institutions have collected information on their customers and members—basic demographic, transactions, account activity, loan portfolios and credit cards balances—and used this information as the backbone of decision making. Yet all this insight extracted about the past will be irrelevant as the information age overtakes old management traditions and methods.

Risk, we agree, is about understanding the future, not the past. The information age provides us with an unparalleled playing field for optimizing the value creation of our businesses. We have the intellectual and technical capabilities to adhere to this new paradigm. It is only up to us, the business leaders, to decide if we want to take this initiative ourselves or to wait for another to do it for us. For the many financial institutions that are attempting to repay the technical debt accumulated over a decade of mergers and acquisitions that resulted in the “Ad-Hoc” management of references systems, I am convinced that the Govern by Value approach will prove its “raison d’être.”

Date recorded:

10 May 2016

Recording:

 

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About IQ International Webinars:

An IQ International Webinar is a moderated webinar open to all, designed to serve as discussion platform for the data and information quality community. The webinars are supported and organized by the International Association for Information and Data Quality. IAIDQ seeks to engage experts with experience and expertise in the field of data and information quality.

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