Disaster Warning System in the Philippines Through Enterprise Engineering Perspective Paper: Disaster Warning System in the Philippines Through Enterprise Engineering Perspective: A Study on the 2013 Super Typhoon Haiyan Natt Leelawat∗, Anawat Suppasri∗∗, Shuichi Kure∗∗,CarineJ.Yi∗∗, Cherry May R. Mateo∗∗∗, and Fumihiko Imamura∗∗ ∗Department of Industrial Engineering and Management, Graduate School of Decision Science and Technology, Tokyo Institute of Technology 2-12-1-W9-66 Ookayama, Meguro-ku, Tokyo 152-8550, Japan E-mail: [email protected], [email protected] ∗∗International Research Institute of Disaster Science, Tohoku University, Japan ∗∗∗Intitute of Industrial Science, The University of Tokyo, Japan [Received April 30, 2015; accepted October 30, 2015] In this research on disaster warning systems, the In November 2013, Visayas, i.e., the central region of Philippines was selected to be a case study. The Philip- the Philippines, was hit by Super Typhoon Haiyan (known pines was hit by a particularly bad storm in 2013 Su- in the Philippines as Yolanda). The typhoon impacted per Typhoon Haiyan. Here we focused on warning primarily on Leyte and Samar in the Philippines, and on system process management from an enterprise engi- coastal Vietnam and China [3]. Its economic impact alone neering perspective. In understanding warning sys- cost USD 9–17 billion. Its societal impact alone cost ap- tems, it is necessary to know the essence of overall proximately 6,300 deaths [3]. Numerous buildings and processes. The objective of this qualitative study is facilities were destroyed [4, 5]. Tacloban, the capital city to determine the system’s essential components by us- of Leyte, had a long history many past experiences of ing the Design and Engineering Methodology for Or- strong typhoons e.g., in 1897, 1912, 1952, and 1984 [6]. ganizations (DEMO). This involves both assigning re- Paciente states that Typhoon Haiyan “is just a repeat of sponsibility levels and utilizing both traditional means whathashappenedinthepast....”Damagewastheworst, such as broadcast vehicles with speakers and radios however, because so many persons had moved to risky ar- and newer means such as Internet channels to dissemi- eas [6]. On the bright side, no large-scale epidemics broke nate warning information. The findings provide a sim- out after the typhoon [7]. ple model explaining the disaster-related organization Since the Philippines is a country with an island geog- and communication structure. They also contribute a raphy that also is often hit by disastrous weather events practical aspect in the form of suggestions to planners such as typhoons, it should be interesting to see how it and decision makers that may assist them in preparing prepares and provides disaster warnings to its citizens, mitigation plans for projected natural disasters. which is why we chose Typhoon Haiyan and the Philip- pines as a case study. We also wanted to answer the ques- Keywords: business process management, enterprise en- tion of “how the country’s disaster warning system is or- gineering, storm surge, typhoon, warning system ganized and operates in ontological level and what lessons are to be learned from all of this?” We applied enterprise engineering methodology called 1. Introduction Design and Engineering Methodology for Organizations (DEMO). Our research is expected to help simplifying Many countries are encountering larger, severer natu- the disaster warning model explaining the disaster-related ral disasters in this decade than ever before, e.g., the 2011 organization and communication structure. Our insights Great East Japan Earthquake and Tsunami, the 2011 Thai- also suggest practical contributions consisting the lessons land Floods, and the 2013 Super Typhoon Haiyan [1, 2]. learned from large-scale natural disaster studies in devel- Although many countries have prepared and implemented oping and improving disaster management plans, espe- disaster warning systems, especially in urban areas, dis- cially in developing countries. asters may occur anywhere, including relatively less pre- Section 2 presents an overview of enterprise engineer- pared rural and remote areas. The remoteness of such ar- ing, DEMO, and disaster. Section 3 discusses our research eas, e.g., outside of mobile phone coverage, makes dis- design. Section 4 details our analysis, and Section 5 dis- aster warnings a challenge. It is important to understand cusses our work and lists conclusions. and learn these lessons, especially in developing countries having many remote areas. Journal of Disaster Research Vol.10 No.6, 2015 1041 Leelawat, N. et al. 2. Background Concept ertheless, the multi-agency nature of disaster manage- ment may cause communication problems [26]. Ander- 2.1. Enterprise Engineering Overview sen and Spitzberg [27] summarized possible reasons ob- An enterprise is defined as an “intentionally created structing disaster communication, including denying ac- cooperative of human beings with a certain society pur- tual risk, no serious risk-taking, including too many fac- pose” ([8] p. 93). As an interdisciplinary field, enter- tors in response considerations, not obeying authority, prise engineering focuses on investigating the individual not clearly understanding situations, inevitable whole im- aspects of the enterprise, including business processes, the age of the disaster, inapplicable information for all pop- information flow, and the organizational structure [9]. En- ulation, diversion in informal communication, delayed terprise engineering was established as a discipline based speed of information, and inappropriate communication on theories of Fact and Information; Discrete Event in mediam. Responsible agencies should be prepared to Linear Time Automata; Teleology Across Ontology; Per- deal with these problems. Furthermore, because disas- formance in Social Interaction; Performance in Interac- ter management is complex with complex information, tion; Binding (constructional) Essence, Technology, and limited time, limited resources, limited actors, and un- Architecture; Normalized Unification; and Socially In- expected factors, concerned organizations must prepare spired Governance and Management Advancement [8]. sufficient information and communication technology in- Enterprise engineering is considered the third wave fol- frastructures and human resources to meet the demands lowing the data system engineering and information sys- of the situation. Lejano et al. [28] pointed out disaster tem engineering eras [10]. Dietz and Hoogervorst [11] communication problems during Typhoon Haiyan, such proposed such enterprise engineering principles as “Dis- as inadequate “[f]eedback loops for conveying tacit infor- tributed Operational Responsibility,” “Transaction Based mation” (p. 35). Organization,” “Actor Based Modularity,” “Technology Independent Essence,” “Function Construction Alterna- tion,” “Strategy-Operation Alignment,” and “Distributed 3. Research Design Governance Responsibility” ([11], pp. 21–26). 3.1. Data Collection 2.2. Overview of DEMO We conducted semi-structured face-to-face interviews in August 2014 with interviewees including officers from DEMO is an enterprise engineering/business process concerned organizations. They were a weather fore- modeling language developed in the early 1990s for an- caster from the Philippines Atmospheric, Geophysical alyzing and visualization business processes with the and Astronomical Services Administration (PAGASA), objective of understanding the essence of an organiza- an officer-in-charge of PAGASA at Tacloban City, and tion [9]. Unlike other modeling languages, which focus an administrative officer level I of the City Disaster Risk on specific implementation or programming, DEMO can Reduction and Management Office. In addition to data enable communication among managerial people. DEMO from interviews, we considered the documentation from is considered as a pioneer methodology in enterprise engi- research papers and reports, e.g., [29, 30]. neering [8] and has been utilized in a variety of real-world scenarios [12–16]. Disaster management is a suitable context for applying 3.2. Research Methodology this methodology because disaster management is com- According to Perinforma [31], communication levels plex and embedded with various coordination and pro- are classified into four (Table 1): duction – one of the reasons, we decided to use DEMO in this study. Many disaster researches have also applied (1) “social correspondence,” DEMO as a methodology in such areas as floods [17, 18], (2) “cognitive correspondence,” earthquakes and tsunamis [19–21], typhoons and land- (3) “notational correspondence,” slides [22], and warning system process management [23, 24]. (4) “physical interaction” (p. 22). The ontological level is communication in social corre- 2.3. Disaster Communication and Information spondence – the so-called Performa level [31]. The info- Overview logical level is communication in the cognitive correspon- Natural disasters require multi-agency coordination dence – the so-called Informa level [31]. The datalogical and effort [25]. The main responsibility should belong level is communication in the notational correspondence to government agencies due to a country’s laws or poli- – the so-called Forma level [31]. Last of all, the phys- cies [25]. Natural disasters link a number of agencies ical level is communication in physical interaction – the during the disaster management cycle [26]. In exam- so-called Medium level