ISO 8000 — the Emerging Standard for Data Quality
July 2009: Originally published in IDQ Newsletter Vol 5 Issue 3
Dr. Matthew West
Over the last 3 years, work has been progressing on ISO 8000. This work has been undertaken in ISO TC184/SC4, the ISO subcommittee that looks after industrial data, and in particular engineering data. However, it has been recognised from the start that this standard could have a much wider usage.
The early concern that prompted the development of ISO 8000 was the quality of data exchanged between organizations, and in particular the quality of master data used to integrate the supply chain. So the early parts of the standard to be developed have focused on this area.
The standards are:
- ISO 8000-110 – Master data syntax and semantics. Specifies general, syntax, semantic encoding and data specification requirements for master data messages between organizations and systems. The focus of ISO/TS 8000-110:2008 is on requirements that can be checked by computer. This has been published as a Technical Specification, and is being progressed to a full ISO standard.
- ISO 8000-120 – Master data provenance. Describes requirements for representation and exchange of information about provenance of master data and master data sets. This is being published as a Technical Specification.
- ISO 8000-130 – Master data accuracy. Describes requirements for the capture and exchange of data accuracy information and a conceptual model for data accuracy information in the form of representations and warranties of data accuracy. This is being published as a Technical Specification.
- ISO 8000-140 – Master data completeness. Specifies requirements for representation and exchange of information about assertions of completeness of master data. This is being published as a Technical Specification.
Each of these standards is very simple; the core content covers just a few pages in each case. A particular feature of these standards is the desire that compliance should be verifiable by computer.
These standards also have a clear and limited intended use, which is the exchange of Master Data between organizations, and they are designed to ensure that the recipient of the data should have the information he needs to determine whether the data is fit for purpose.
Controversy over Quality Management of Data
In the meantime there has been much more controversy over the issue of quality management of data, and whether the standard should be for data quality and/or information quality.
This debate has revealed major differences between participants in what data and information are. It also revealed fears that ISO 8000 could become a certifier's delight in the way that ISO 9000 has been seen by many.
There are also many who have seen that the scope of ISO 8000 could easily exceed that of the committee that is developing it, and there are those that would wish to restrict it to product data and other engineering data.
Within this environment I have been making proposals, based on the work I did in Shell over many years, that:
- Quality is about being fit for purpose. This means that you need to know what use the data is going to be put to before you can assess its quality.
- Data is used to support decision-making. Poor quality information can lead to poor decisions that have cost consequences. There are also costs to improve the quality of the information to meet the needs of the decisions it supports.
- Data is a product, and its quality can be managed using classical quality management principles, and by establishing a quality management system as set out in ISO 9001 (Figure 1)
Figure 1: Data is a product and its quality can be managed
- There are information quality characteristics that are independent of the data. What distinguishes information from other products is that there are certain properties that determine its quality that are independent of what the data is about (see Figure 2 on the next page).
- Where information is passed between organizations, this should be based upon agreed specifications, just like any other product.
Figure 2: Information Quality Characteristics are Independent of what the Data is about
- In practice, everything we do in IT and information management is about delivering information quality. This means we can judge what we do by how it helps deliver quality information. In particular, much of enterprise architecture is needed to support the quality management process for information.
- Information management maturity provides a simple, quick, and cheap way to assess where an organization is in managing information quality (Figure 3). Self certification is sufficient.
What this approach to data and information quality recognises is that for any organization, it is itself the largest customer for the information it produces, and that the quality of the information it uses is a major contributor to its performance, and in particular to performance improvement.
If this approach to data and information quality management is included within the ISO 8000 family of standards it will be useful to any medium to large organization that is looking to improve its business performance by improving the quality of the information it uses itself, or provides to its customers as part of its products.
It will not be a burden that is added to existing tasks, but will be a path to business improvement with benefits both from the elimination of waste, and improvements in business performance. The Information Management Maturity Framework will enable organizations to assess their current position, and prioritize next steps for improvement.
Get Involved. If you wish to get involved with the development of ISO 8000, it is easy to participate, since most of the work is done be e-mail and telephone conferences. Registering with the e-mail exploders for ISO 8000 can be done via the SC4 Online website at: www.tc184-sc4.org
You can also find working documents there for the standard in the WG13 folder.
Finally, you can contact me for more information.
When we begin to develop our information quality initiatives, it’s important to promote the project internally within the organization, and make it easier for our colleagues to understand the project’s value. After all, business people and executives hold the purse strings, and we need their support to expand our data quality efforts into enterprise-wide programs.
Editor’s note: The IAIDQ is an organization in cooperation with ISO (International Organization for Standartization).
© 2009 Matthew West
About the Author
Dr. Matthew West is a Director of Information Junction, which he joined in 2008. Prior to this, he joined Shell in 1978, and since 1987 has focused on the computing/business interface with a particular interest in Information Management, Master and Reference Data, and Data Modelling. He was also responsible for the development of Shell’s Downstream Data Model.
He is a key technical contributor to ISO 15926 – “Lifecycle integration of process plant data including oil and gas production facilities” and is participating in the development of ISO 8000 – Data and Information Quality. Matthew is also a Visiting Professor in the Keyworth Institute at the University of Leeds.
He can be reached via email at matthew [dot] west [AT] informationjunction [dot] co [dot] uk. More information can be found at www.matthew–west.org.uk