Poor data and information quality lead to operational and strategic risk in the era of Big Data

Data is an absolutely vital business resource in every organization. While the organizational complexity and the complexity of corporate IT landscapes are ever growing in our globalized economies, the amount of business data is increasing at an even faster speed. Hence, data and the insights created from data become more and more difficult to manage.

Data is very often of poor quality leading to major risks in all parts of an organization, affecting operational efficiency, bottom-line results, customer satisfaction and strategic decision making. In fact, there are so many data and information quality problems that managers cannot solve all problems at the same time and have to select carefully where they focus their efforts on. 

    

How to manage data quality for business value and set priorities for data analytics?

Managers struggle to understand and to measure how data and information quality impacts their business objectives - both financially and non financially. 

This impedes organizations to set the right priorities in their business analytics initiatives, to build believable business cases for these initiatives and to manage information quality for business value.

Our research team at the University of Cambridge has developed an innovative approach, the Total Information Risk Management (TIRM) Process. 

The TIRM process provides companies with a clear, simple and easy to follow process to measure and treat the risks generated by poor data and information quality, which is completely driven by business value.

Video Presentation: How TIRM helps you to manage information insights for business value

Watch this video to learn how the TIRM process helps your company to succeed in managing information risk.

CLICK HERE TO WATCH A VIDEO PRESENTATION

              

Managing Information Risks in Asset Management 

- Experiences from an In-Depth Case Study in the Utility Industry

Alexander Borek, Philip Woodall, Ajith Kumar Parlikad, University of Cambridge, UK 

Mark Godsen, Manx Electricity Authority, Isle of Man

From: The IET Asset Management Conference 2011, Session 3: Modelling, 30 November 2011, London

What other people say about the Total Information Risk Management (TIRM) Process

"One of the most troublesome problems we face in data quality involves crafting and presenting powerful business cases.

Alex and his group appear to be making significant breakthroughs, on at least two fronts. 

First, the notion of risk-based business cases. These add the probabilistic dimension to current state of the art and may prove more powerful in the eyes of decision-makers. 

Second is a well-defined, comprehensive, and repeatable process for assembling the case. 

I’m particularly heartened by the cross-fertilization of data quality with e

stablished methods of quantifying, or at least more fully defining, risks

. 

Finally, it bears mentions that the research encourages us to push our thinking about business cases for data quality further."

Thomas C. Redman, the Data Doc, December 2011. 

Tom Redman was one of the first to extend quality principles to data and information in the late 80s. Tom is the President of the Navesink Consulting Group and a world-leading data quality expert. He is author of the award winning book "Data Driven: Profiting from Your Most Important Business Asset" published by Harvard Business Review Press (Library Journal Best Business Book of 2008). 

"The Total Information Risk Management Process supports practitioners in finding the right path through the jungle of information management. TIRM helps you to sort out that complexity by having a more formal way of managing information risks against business values. It is a step by step approach with useful templates and can be directly applied by every information manager today."          


Andreas Hart, Senior Solution Manager at Microsoft, January 2012.

Andreas Hart is a Solution Manager in the Information Management Team within Microsoft Field IT, currently located in Sydney. He has broad experience gained in the field of Enterprise Information Management over the last 8 years on local (Switzerland), Area (Western Europe) and Global (Shared Services) level at Microsoft.

"The use of a Risk Based Approach to establishing the cost of poor quality is the most innovative development I have seen in data quality management in the last five years! 

Getting across the value of improving data quality has always been one of the hardest things to do in data quality management, and the use of a risk management approach is a significant step up from current approaches.”          


Matthew West, Director at Information Junction, February 2012.

Matthew joined Information Junction in 2008 providing consultancy services in information quality, enterprise architecture, ontology and data modeling. Prior to this he worked for Shell since 1978, and since 1987 on the computing/business interface with a particular interest in Information Management and Data Modelling. Matthew has been active in standards development, in particular in ISO TC184/SC4 - Industrial Data, and is author of a number of books in the data and information management discipline.

          

"When we talk about information quality, we typically just focus on improvement. The whole idea of risk management is a great contribution as it really in a way is resetting the conversation in the information quality discipline around risk and business value rather than improvement itself. 

TIRM is a combination of identifying existing problems and their business impact, but also assigning some probability to potential problems as much as the consequences of the problems. The TIRM process provides a structured approach for accomplishing this."

Professor John Talburt, Director of the Center for Entity Resolution and Information Quality, University of Arkansas at Little Rock, March 2012.

John Talburt is a Professor of Information Science at the University of Arkansas at Little Rock and Acxiom Chair of Information Quality. He is director of the Center for Entity Resolution and Information Quality. Beforehand, he had several leadership roles at Acxiom Corporation. John is advisor to the IAIDQ board of directors and received several awards, such as the 2010 Leadership to the MIT Information Quality Industry Symposium Award. He is author of the book "Entity Resolution and Information Quality" published by Morgan Kaufmann.
          

Research in information science, informing sciences, information quality, and knowledge management already  reached a decades long tradition, however their cross-fertilization with risk assessment and its management is literally novel.  The rigour presented by the TIRM team in gathering, processing, and interpreting empirical data from industrial field studies is ingenious and impressive. 

It introduces comparable rigour in assessing risks related to deficiencies in quality of operational factors in substance and those in form such as information, data, and other elements of knowledge that enables to compute the statistically expected materiality or impact of the risk on business value; hence worth the money spent on consulting. Thus, it opens new venues of thinking and research.

Professor Zbigniew J Gackowski, Department of Computer Information Systems, College of Business Administration, California State University Stanislaus, April 2012.

Zbigniew J. Gackowski has experience in industry, administration, and academia. It bridges his Central European and US experience in Computer Information Systems (Warsaw Polytechnic, University of Michigan [Fulbright Research Scholar], Purdue University [Visiting Associate Professor], Baruch College [Visiting Professor], California State University, Stanislaus [Professor], and the University of Melbourne [Visiting Professor]). He authored the book "Informing for Operations: Framework, Model, and the First Principles" published by the Informing Science Institute.

"A perennial problem facing data quality practitioners has always been how to demonstrate data quality risk to business drivers that stakeholders care deeply about. The TIRM process has helped the profession take a big leap forward in resolving this challenge and the team responsible for TIRM should be commended for their innovation."

Dylan Jones, Founder and Community Leader, Dataqualitypro.com, May 2012.

Dylan Jones is the founder and community leader of dataqualitypro.com, which provides expert data quality resources to more than 5,400 members every day. Dylan has over 20 years experience in data quality and information management. Before founding the community, Dylan was principal consultant and technical expert at Information Quality Solutions Limited and MBT and data quality and migration specialist at Reuters. He is also blogger at the Data Roundtable, which consists of leading data management experts.