By Bob Wall, Senior Consultant
I recently read an interesting article on the web entitled “Ascending the Data Infrastructure Hierarchy: The Five Stages of Data Infrastructure Maturity." 1
In it the author discusses Maslow’s self-actualization psychology2 and the Hierarchy of Needs (further information here) and creating an enduring Data Management Infrastructure. I believe it has implications to achieving data management maturity, which is a fundamental ingredient for MDM success.
As Baseline partner Evan Levy has explained in his MDM presentations, MDM is comprised of both “(Master Data) Management—capabilities to support master subject areas such as Customer, Product or Account—and Master (Data Management), in other words sustaining data management via standards, guidelines, and procedures. This includes the following Data Management functions:
- Data stewardship
- Data architecture, analysis and design
- Database administration
- Data security management
- Data quality improvement
- Reference/master data management
- Metadata management
In trying to better manage these data management functions, reach an optimal level of data management maturity, and support a successful MDM implementation, Maslow’s hierarchy of needs and self-actualization psychology provides some helpful insight. In his epic psychology writing, Maslow organized human need into three broad levels: first, the physiological - air, food and water; then the psychological - safety, love, self-esteem; and finally, self-actualization. His insight was that the higher needs were as much a part of our nature as the lower, indeed were instinctive and biological. Maslow's greatness was in re-imagining what a human being could be.
The following schematic shows Maslow’s Hierarchy of Needs and an analogous Data Management Hierarchy.
We can see the 5 areas of the Data Management Hierarchy, mimicking Maslow’s Hierarchy of Needs, as follows:
Level 1: Tribal – Basic Needs (survival)
At this level, an organization functions from day to day, but without any formal processes or systematic management. Instead, data management is left to the decisions of knowledgeable and skilled individuals.
Level 2: Enforced – Safety Needs (comfort)
As a company advances to the next level of the Data Management Hierarchy, the Enforced stage, it begins to adopt some semblance of governance, which includes documented standard operating procedures and putting in place change controls to better manage workflow within its data environment.
Level 3: Standardized – Psychological Needs
As organizations advance from the Enforced stage to the next level, they reach the Standardized stage, in which, as the name suggests, processes are established to handle various aspects of data management and less importance is placed on individual decision making.
Level 4: Actualized – Self-Actualization
In the Actualized stage, organizations are able to start getting more creative with their data. Data can be extracted from across the enterprise - as well as from outside sources - and combined to create useful information and made actionable to create new knowledge and value added business propositions.
Level 5: Peak Performance Peak Experiences
At last, the organization reaches the height of data management development, where it can devote all its resources to high-level strategic initiatives, rather than administrative issues.
MDM success is directly proportional to how well an organization integrates data management principles and reaches a peak performance/experiences maturity level. Hence we can see the possibilities of the gradual application of Maslow’s Psychology of the Hierarchy of Needs, leading to the ascendance of data management maturity and re-imagining what a successful MDM project could be.
1 John Bostic, Ascending the Data Infrastructure Hierarchy: The Five Stages of Data Infrastructure Management Maturity (Auerbach Publishing, 2007).
2 Abraham Maslow, A Theory of Human Motivation (Psychosomatic Medicine, 1943).
Bob
Wall is a senior consultant with Baseline Consulting. He is an
information technology specialist with 30 years experience in all areas
of data warehouse administration, data architecture, data resource
management, training, and applications systems development, as well as
in corporate management.
Bob,
Fantastic post and an awesome analogy!
What have you found to be the most common level for an organization?
Based on my experiences, I would probably guess Level 2.
Have any of your clients achieved Level 5?
Thanks and Best Regards…
Jim
Posted by: Jim Harris | September 17, 2009 at 09:04 AM
Jim:
Yes, indeed Level 2 seems to be the most prevalent. In today’s economy, self-protection seems to be the norm and so we’ve actually seen people and firms regress a little bit. Baseline does have a couple Level 5 clients that really get it. We like to think they only got to Level 5 after they retained us, but the fact is that solid leadership seems to make all the difference with these particular companies. I’d name them, but then they might get complacent! Thanks for your comment and for being a regular reader of the Baseline blog!
Jill
Posted by: Jill Dyche | September 17, 2009 at 10:52 AM
Bob,
I like the "Capablity Maturity" concept. It is important that Enterprises understand where they are, and where they need to be, in terms of Data Management, Data Governance etc.
What process do you use to measure where an organisation is on the scale?
I developed a "Data Issue Assessment Process" to enable Data Quality Professionals to objectively assess how well (or poorly) an Enterprise is handling common Enterprise wide data issues (See link at foot of post).
The process is flexible, and could be adapted to measure the "Data Management Maturity" of an organisation.
I would be happy to co-operate on the adaptation.
Rgds Ken
http://kenoconnordata.wordpress.com/2009/07/13/process-for-assessing-status-of-common-enterprise-wide-data-issues/
Posted by: Ken O'Connor | September 18, 2009 at 07:05 AM