DATA STEWARDSHIP:

THE WHY AND HOW;

THE RIGHT WAY AND THE WRONG WAY

19 October 1998 ITS DR SOP

Introduction

Stewardship of data as a “corporate asset” is becoming more the vogue these days. Unfortunately, the notion of data steward is not well understood today in corporate America. Data stewardship is not a silver bullet; data stewardship is a lot of hard work and requires a substantial corporate commitment. Further data stewardship is but one facet of a larger issue: stewardship of an organization’s information assets. Data stewardship, in and of itself, must be doomed to failure, at least from an enterprise perspective. Without a concept of stewardship in the large in an organization, data stewardship cannot succeed; or if it does manage to “succeed”, with of necessity be a sub-optimizing “success”.

There are at least four key information assets that must be brought under a corporate stewardship umbrella: data, rules, technology, and systems. These fours dimensions of the corporate information asset are, of course, closely inter-related. Data forms the life blood of an information age organization. Rules form the arteries guiding the flow and manipulation of data. Technology forms the skeleton upon which the data and rules are draped. And, systems form the musculature that makes the whole work.

Data: A named unit of facts, propositions, or observations that is treated as a whole for some purpose, but which may have internal components1. Data may be a data element value (the only “atomic” level of data), a data element (a structure of an entity type, a property type, and a value domain1), a record, a file, a database, a data mart, a data warehouse, etc. Data must be under stewardship in order to maintain semantic understanding of data over time and place.

Rules: A specification of a business condition, intent, or requirement. Like data, business rules consist of atomic level elements (statements), as well as structures of these atomic statements (the reader is referred to Mr. Ron Ross’ Data To Knowledge Newsletter and his new book Business Rule Concepts [contact: [email protected]]). These rules and their rule structures exist in any organization; some are embedded in automated systems and some are embedded in manual organizational activities. Rules must be under stewardship in order to keep the entire organization on the same “sheet of music”.

Technology: The automated information processing substructure: computer hardware, operating systems, DBMSs, programming codes, email systems, etc. Technology must be under formal stewardship in order to maintain a corporate awareness of the state-of-practice and innovations in software, methods, and tools – as well as manage their introduction to minimize technological disruptions and achieve effective migrations among successive technologies.

Systems: Business automated applications designed to facilitate the business activities of an organization. Systems must be under stewardship in order to ensure that, in their totality, they effectively support the particular business activities of the organization as well as corporate objectives. Too many systems are developed, deployed, and operated for far too limited purposes, all in the name of meeting budget and schedule constraints that do not allow for effective review, design, or approval from a corporate perspective.

With the larger stewardship issue defined above in summary, the remainder of this article will address the notion of data stewardship in more detail.

1 Data stewardship role types

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Data stewardship is not one role; not one job; not one organization, not one individual. Effective data stewardship requires five levels of data stewardship:

Policy steward, Enterprise steward, Business steward, Project steward, Operational steward

and two levels of data stewardship management:

Technical configuration control committee, Policy board of directors.

These specific roles will be defined and described in some detail below. However, let me say up front that most concepts of data stewardship practiced today are focused on the role of Business steward. This focus has virtually ensured failure of effective data stewardship programs from a corporate or enterprise perspective.

The role types are types for two reasons: 1) they can be hierarchical, 2) one person can serve in multiple roles, particularly in smaller organizations.

1.1 Policy steward

The data policy steward is the most strategically important of all data steward roles. This is the steward that establishes, and enforces, the whole notion of data stewardship. This steward typically will be the CIO or CEO of the organization. If this steward does not establish, by corporate policy, the other four data steward roles correctly, there is little hope that the organization will be able to sustain a viable data stewardship practice, even if it is initially established. The policy steward is NOT a czar! Policies that the policy steward puts forth MUST be corporate policy. That means that, in the absence of a very big stick that can be wielded over a significantly long time, these policies must be established by some consensual process. See the discussion below of the board of directors dimension of the data stewardship endeavor. There is only one policy steward.

1.2 Enterprise steward

The enterprise steward is the lynch pin upon which corporate or enterprise data stewardship depends for ultimate success. The enterprise steward is responsible for all data associated with a business entity (such as customer), or a set of related business entities (such as customer, retail customer, wholesale customer, national customer) 2. There may be more than one enterprise steward, in a hierarchical relationship— which may go down into particular lines of business or functional staffs. For example, the Vice President for Marketing and Sales could be the enterprise steward for “customer”; and, under this enterprise data steward one might find: Director of Retail Accounts (for retail customer), Director for Wholesale Accounts (for wholesale customer), and Director for National Accounts (for national customer) 2. The point is that there is one and only one enterprise level steward for data about any entity of importance to the organization/enterprise. Further, data about any subtype entity are under the purview of a super-type steward, so that common information (meta attributes) about that entity and sub-entities are commonly defined and reused. This entity focus to enterprise data stewardship is absolutely crucial to the ultimate success of enterprise-wide data stewardship.

1.2 Business steward

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The business steward is charged with responsibility for all the data of interest about any entity of interest within a particular line of business or functional staff element. The business steward coordinates all data requirements within the business area . All too often, this coordination is limited to the interests or needs of the particular business area, at the expense of enterprise-wide reuse of business area data. In this case, typically, the business steward participates in defining data requirements that have many dimensions in common with other business areas, without knowing it. This leads to data definitions that are not only redundant but also, very typically, incompatible--at least at the value domain level and identification level (identifiers). For example, scores of ‘customer identifiers’ are defined within business areas of an organization, with the resultant inability to correlate various business perspectives of customers from an organizational or enterprise perspective. The only way out of this confusion of data stewardship at the business stewardship level is to make sure that business stewards are ‘hooked into’ a larger perspective, i.e. that of the enterprise stewards. Thus, the business steward must closely coordinate with the enterprise steward(s) to ensure that data being developed with the business area is compatible with enterprise perspectives. There is one business steward for each business area or functional staff element, although that business steward may very well be supported by stewards for data entity subtypes within the line of business or functional staff element, just as at the corporate or enterprise level.

1.2 Project steward

The project steward is responsible for defining data requirements for a particular application or system development effort. If the project steward is not operating within a larger stewardship environment [namely that of the business steward, who is plugged into the enterprise steward(s)], there can be little hope that data defined and implemented in any development project will have any chance of being compatible with the overall needs of the business area—never mind reusable within the organization or enterprise. There is only one project steward for any particular project.

1.2 Operational steward

The operational steward is responsible for the quality input of data into the organization’s application system and its proper use. These are the data consumers or data readers 3 and data inputers. These are the folks who man the phones and take down information into the organization’s application systems; they had to do it right. These are the folks who analyze and report data as information; they have to do it right. In both of these endeavors, it is clear that rules play a crucial part. There are multiple operational stewards within an organization or enterprise.

2 The larger solution

For any data management mature organization, there must be an effective data stewardship feedback loop to identify data issues and resolve them. Such issues will be either technical in nature or policy in nature. Hence, the data stewardship endeavor in any organization or enterprise will need to have an effective mean for addressing such issues, assuming that the feedback loops are in place and operative.

2.1 Technical control committee

The technical control committee, or configuration control committee, is the group that resolves all technical issues associated with data and its stewardship. This group, ideally, is composed of the enterprise data stewards. It assigns data entities (and associated data elements) to cognizant enterprise

4 4/25/2018 ITS DR SOP stewards. It also addresses and resolves issues of overlapping and redundant data among enterprise stewards. It establishes and certifies organizational or enterprise technical data standards such as value domains, class terms, data naming conventions, and the like.

2.2 Board of directors

The board of directors is the group that establishes and sees to the enforcement the data stewardship policies of the organization or enterprise. The policy steward answers to this group (unless he or she has a VERY big stick that can be wielded over a significantly long time period). This group gives credence to the policies, standards, and direction of the policy steward. Even if the policy steward can wield a big stick, he or she is well advised to formulate every policy steward initiative only with the full formal support of the board of directors.

3 In summary

Five data stewardship roles are required for successful data stewardship in an organization or enterprise: Policy steward, Enterprise steward, Business steward, Project steward, Operational steward. Of these, the two most critical to success are the policy steward and the enterprise steward(s). Without the successful establishment of these two roles, data stewardship from an organizational or enterprise perspective have no real chance of long term success. The success over time of the policy steward essentially hinges upon the establishment of an effect stewardship board of directors; that of the enterprise steward(s) upon the establishment of an effect stewardship technical control committee. Organizations that depend upon a business stewardship approach to managing their data will succeed in the long run only inefficiently and less effectively.

This discourse is on an ideal approach to data stewardship. It is certainly not an easy thing to achieve. The business stewards and their political backers will be disinclined to support any such efforts. However, organizations or enterprises that do not achieve some variation of this nominal model will fail to realize effective application of their data as a corporate asset.

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1 Adapted from ISO/IEC 11179 (Part 1) Specification and Standardization of Data Elements.

2 Larry English, DAMA Presentation, Milwaukee WI, July 1995

3 Robert Seiner, DAMA Presentation, Dallas TX, March 1997

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