AD ALTA
JOURNAL OF INTERDISCIPLINARY RESEARCH
A BUSINESS INTELLIGENCE SOLUTION FOR BUSINESS CONTINUITY AND SAFETY
MANAGEMENT IN PUBLIC UNIVERSITIES
a
ATHANASIOS PODARAS,
b
TOMÁŠ ŽIŽKA,
c
DANA
NEJEDLOVÁ,
d
DAVID KUBÁT
Technical University of Liberec, Faculty of Economics,
Department of Informatics,
Studentská 1402/2, 461 17, Liberec
1, Czech Republic
email:
a
athanasios.podaras@tul.cz,
b
tomas.zizka@tul.cz,
c
dana.nejedlova@tul.cz ,
d
david.kubat@tul.cz
Abstract: The article introduces a modern business intelligence solution for facilitating
business continuity and safety management proactive decisions in public organizations
and units, which is currently tested in a public university for its effectiveness. The
tool’s data dimensions, hierarchies and facts are based on the business continuity
points method which is a modern approach for estimating proactively the recovery
time and predicting the criticality level for individual business functions. From the
constructed dataset, selected safety – related and highly critical business functions are
used to validate the proposed contribution. The same functions are further used for
estimating their availability rates and compare the results with the rates proposed by
the university business continuity experts. The conducted research results indicated
high accuracy when predicting criticality levels as well as computing availability rates
for safety critical functions in the public university. The proposed BI tool facilitates
both online analytical processing operations as well as machine learning activities.
Keywords: availability, business continuity, business continuity points, business
intelligence, machine learning, public university, safety critical business functions,
safety management
1 Introduction
The interruption of modern business operations and especially
those related to safety management is an issue which is
thoroughly discussed and analyzed by experts from the business
sector as well as academic researchers. Business continuity
Management (BCM) is a topic which is strongly related to safety
management. More precisely, the part of an integrated business
continuity management entitled Business Impact Analysis is
defined as “a process that identifies and evaluates the potential
effects (financial, life/safety, regulatory, legal/contractual,
reputation and so forth) of natural and man-made events on
business operations” (Gartner, 2017).
Regardless of the important role of business continuity policies
in the secure and uninterrupted operation of core business
operations within modern organizations, the application of
standard BCM regulations is so far considered to be a hard task.
A study conducted by Urbanec & Urbancova (2014) reveals that
modern organizations are skeptical in terms applying standard
BCM strategies.
In universities, the situation is rather equivalent to other public
organizations. The recent COVID-19 outbreak forced academic
institutions to conduct research and teaching activities online as
a result of the necessary health and safety countermeasures. Such
crisis response activities require high network availability in
order to ensure the uninterrupted operational mode of each
public university to a minimum acceptable level. However,
business functions which are rather ignored during the normal
operational period, during the epidemic period have been treated
as highly important. Distant lectures have been implemented to
ensure that the spread of the epidemic is controlled. Immediate
information distribution via email or the web site of every public
university
regarding
exceptional
regulations
and
countermeasures against the spread of the disease has been
considered as crucial. In general, the importance of ensuring the
continuity and the availability of core IT infrastructure and the
safety of personnel in public organizations, including
universities, throughout the epidemic times has been
undoubtedly realized to a considerable extent.
The current research attempts to highlight the importance of
business intelligence systems towards the formulation of
effective business continuity and safety management policies.
For the needs of the current research a number of university
BCM regulations have been considered. However, the most
complete BCM guide is provided by Columbus College (2018).
Based on the study of different university BCM regulations, it
can be concluded that every academic institution follows BCM
strategies adjusted to its individual needs. As a consequence, it is
not hard to define common recovery priorities for every
academic institutions. Yet, the thorough study of multiple
university and college BCM templates, can facilitate a basic
pattern software based BCM and safety management solution
when data regarding common business functions is utilized.
Due to the above mentioned BCM peculiarities among university
institutions, standard theoretical methodologies and approaches
or even sophisticated software tools that could support
demanding BCM activities and knowledge discovery within the
domain such as the establishment of recovery priorities for
unique business functions, are not available in the literature. The
same holds for other public organizations as well as enterprises
that operate in the private sector.
In order to fill this gap, a standard mathematical method for
classifying individual business functions, entitled business
continuity testing points (or simply business continuity points)
(Podaras et al, 2016) has been recently developed. The method
focuses on estimating the recovery complexity of an individual
business function. This estimation can facilitate the classification
of a business function as critical or non-critical (Podaras, 2018)
with the help of specific mathematical computations and data
mining rules. So far the approach has been based on empirical
lab computations and a dataset that has been constructed by the
research team. In the present study, a real data set from a public
college is used for further validation of the method. Data about
42 critical business functions is gathered, and used for testing the
validity of the BCPTs approach.
For the purposes of the current paper, it is considered necessary
to focus more on highly critical operations and systems which
are crucial for ensuring the safety of the university staff as well
as the students throughout the conducting of routine academic
activities. The study of other university BCM policies (Rowan
University, 2014; Columbus Technical College, 2018; Pace
University, 2020) reveal that strict resumption timeframes and
infrastructure availability are crucial prerequisites for ensuring
the sustainable operation of safety-related processes as well as
safety critical units and systems.
For the above stated reason, 7 safety – related operations have
been chosen out of the 42 functions for which BCM data was
collected, in order to further validate the BCPTs method and
propose a business intelligence solution for BCM based on
dimensions, facts, hierarchies and rules stemming from a
mathematical and strictly validated approach.
Based on the above, the goal of the present article is the proposal
of a business intelligence solution which is aimed to support
decision making with respect to the rapid response to unexpected
disruptions regarding safety – related business operations and
ensure effectiveness in terms of business continuity and safety
management in public organizations and units. The goal is
supported by a number of important research objectives as
follows:
Incorporation of the business continuity points recovery
parameters in order to design a conceptual business
intelligence BCM tool and develop its physical data
warehouse solution to support the proposed mathematical
approach, classify accurately each business function in
terms of recovery priority and compute proactively its
maximum allowed downtime (or maximum recovery time).
Utilization of real business continuity data to test the
validity of the business continuity points as well as the
functionality of the proposed business intelligence tool. In
the present study, data regarding safety –related operations
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