A successful management subsystems integration relies
on several requirements fulfillment. The maturity achieved by an implemented
integrated management system (IMS) relates to the compliance by an organization
of several internal key process agents (KPAs), some external factors and the
adoption of the eight excellence management pillars. Some of these KPAs are
more influential for maturity assessment than others so, their adoption may be
more fruitful concerning the maturity increase by an IMS. Some integration
models proposed by European Foundation for Quality Management (EFQM) and ISO
9004 standard have its genesis on quality and that fact may be advantageous but
also presents some disadvantages. Additionally, results suggest that they are
not considered a truly integration referential by the companies.
Portuguese companies managed through an integrated
system have some common features between them. Integrated policies, an IMS
manager presence in the organizational structure and tools, methodologies and
objectives alignment are some of these common features.
As been told earlier, the proposed model is sustained
on two components supported in software concepts (Figure 1). A back-office
component processes the information collected from the front-office component.
To populate the front-office component companies should assess the KPAs
according an agreement Likert scale.
Figure 1: Conceptual model design
Front-office component has a three dimensional nature
as one may see in Figure 3. One dimension relates to the KPAs assessment, other
to the eight excellence management pillars and the final to the external
factors assessment (macroergonomics, life cycle analysis, social accountability
and sustainability) (Figure 2).
Figure 2: Front office component
A simple linear regression model was tested in order
to assess data quality and coherence provided by respondents. A multiple linear
regression model was adopted in order to identify which variables (central
variables) were statistically influencing the latent variable. Pearson
correlation was assessed between statistical non-influential variables and the
central variables. Three variables variation (Q/St10, Q/St23 and Q/St24) are
statistically responsible for 54% of Q/St25 variation. Top management
integrated vision (Q/St10), organizational integration level classification
(Q/St23) and audit typology (Q/St24) explains mostly the Q/St25 (Integration
level characterization) variation. The other variables are related to these
central variables and the Pearson correlation index is presented (Figure 3).
Figure 3: Back office component
Pedro Domingues
PhD Student
Quality and Excellence Research Group
University of Minho
