Please wait a minute...

Frontiers of Engineering Management

Front. Eng    2017, Vol. 4 Issue (1) : 41-48     https://doi.org/10.15302/J-FEM-2017003
REVIEW ARTICLE |
Intelligent data analytics is here to change engineering management
Jonathan Jingsheng SHI1(), Saixing ZENG2, Xiaohua MENG3
1. College of Engineering, Louisiana State University, Baton Rouge, LA 70803, USA
2. Antai College of Economics & Management, Shanghai Jiao Tong University, Shanghai 200030, China
3. Department of Management Science and Engineering, Soochow University, Suzhou 215006, China
Download: PDF(336 KB)   HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract

A great deal of scientific research in the world aims at discovering the facts about the world so that we understand it better and find solutions to problems. Data enabling technology plays an important role in modern scientific discovery and technologic advancement. The importance of good information was long recognized by prominent leaders such as Sun Tzu and Napoleon. Factual data enables managers to measure, to understand their businesses, and to directly translate that knowledge into improved decision making and performance. This position paper argues that data analytics is ready to change engineering management in the following areas: 1) by making relevant historical data available to the manager at the time when it’s needed; 2) by filtering out actionable intelligence from the ocean of data; and 3) by integrating useful data from multiple sources to support quantitative decision-making. Considering the unique need for engineering management, the paper proposes researchable topics in the two broad areas of data acquisition and data analytics. The purpose of the paper is to provoke discussion from peers and to encourage research activity.

Keywords engineering management      project management      big data      data analytics      planning      execution     
Corresponding Authors: Jonathan Jingsheng SHI   
Online First Date: 21 March 2017    Issue Date: 19 April 2017
 Cite this article:   
Jonathan Jingsheng SHI,Saixing ZENG,Xiaohua MENG. Intelligent data analytics is here to change engineering management[J]. Front. Eng, 2017, 4(1): 41-48.
 URL:  
http://journal.hep.com.cn/fem/EN/10.15302/J-FEM-2017003
http://journal.hep.com.cn/fem/EN/Y2017/V4/I1/41
Service
E-mail this article
E-mail Alert
RSS
Articles by authors
Jonathan Jingsheng SHI
Saixing ZENG
Xiaohua MENG
Fig.1  Ideal project coordination
Fig.2  Unpleasant teamwork scenario
1 Aldridge I (2013). High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems. 2nd ed. Hoboken: John Wiley & Sons
2 Brookes J N (2014). Mankind and mega-projects. Frontiers of Engineering Management, 1(3): 241–245
https://doi.org/10.15302/J-FEM-2014033
3 Barnhart C, Daskin M S, Dietrich B, Kaplan E, Larson R. (2007). “Grand challenges in engineering.” INFORMS – Institute for Operations Research and the Management Sciences. , 2016-10-25
4 Davenport H T, Redman T (2015). Getting advantage from proprietary data. http://blogs.wsj.com/cio/2015/03/11/getting-advantage-from-proprietary-data/, 2016-10-25
5 Davis J, Edgar T, Porter J, Bernaden J, Sarli M (2012). Smart manufacturing, manufacturing intelligence and demand-dynamic performance. Computers & Chemical Engineering, 47: 145–156
https://doi.org/10.1016/j.compchemeng.2012.06.037
6 De los Reyes A (2006). The role of computer-aided drafting, analysis, and design software in structural engineering practice. http://hdl.handle.net/1721.1/35080, 2016-10-25
7 Hinze J (2012). Construction Planning and Scheduling. 4th ed. Upper Saddle River: Prentice Hall
8 Hendrickson C, Au T (2008). Project Management for Construction: Fundamental Concepts for Owners, Engineers, Architects and Builders. Upper Saddle River: Prentice Hall
9 Kang H S, Lee J Y, Choi S S, Kim H, Park J H, Son J Y, Kim B H, Noh S D (2016). Smart manufacturing: past research, present findings, and future directions. International Journal of Precision Engineering and Manufacturing-Green Technology, 3(1): 111–128
10 Lohr S (2012). The age of big data. http://www.nytimes.com/2012/02/12/sunday-review/big-datas-impact-in-the-world.html?_r=0, 2016-10-27
11 Manyika J, Chui M, Brown B, Bughin J, Dobbs R, Roxburgh C, Byers A H. (2011). Big data: the next frontier for innovation, competition, and productivity. http://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/big-data-the-next-frontier-for-innovation, 2016-10-27
12 McAfee A, Brynjolfsson E (2012). Big data: the management revolution. Harvard Business Review, 90(10): 60–68
13 Merrow E W (2011). Industrial Mega-projects: Concepts, Strategies, and Practices for Success. Hoboken: John Wiley & Sons
14 Miller R, Lessard D R (2000). The Strategic Management of Large Engineering Projects: Shaping Institutions, Risks, and Governance. Cambridge: MIT Press
15 Moore G A (2014). In: Marketing and Selling Disruptive Products to Mainstream Customers. Crossing the Chasm. 3rd ed. New York: Harper Collin Publishers
16 Moorthy J, Lahiri R, Biswas N, Ghosh P. (2015). Big data: prospects and challenges. Vikalpa., 40(1): 74–96
17 NAE. (2008). Grand challenges for engineering. , 2016-10-27
18 Rujirayanyong T, Shi J (2006). A project-oriented data warehouse for construction. Automation in Construction, 15(6): 800–807
https://doi.org/10.1016/j.autcon.2005.11.001
19 Siegel E (2013). Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die. Hoboken: John Wiley & Sons
Related articles from Frontiers Journals
[1] Gang FU, Pedro A. Castillo CASTILLO, Vladimir MAHALEC. Impact of crude distillation unit model accuracy on refinery production planning[J]. Front. Eng, 2018, 5(2): 195-201.
[2] Mario VANHOUCKE. Planning projects with scarce resources: Yesterday, today and tomorrow’s research challenges[J]. Front. Eng, 2018, 5(2): 133-149.
[3] Jing LIN, Uday KUMAR. IN2CLOUD: A novel concept for collaborative management of big railway data[J]. Front. Eng, 2017, 4(4): 428-436.
[4] Braulio BRUNAUD, Ignacio E. GROSSMANN. Perspectives in multilevel decision-making in the process industry[J]. Front. Eng, 2017, 4(3): 256-270.
[5] Yongkai ZHOU, Hongfeng CHAI. Research and practice on system engineering management of a mobile payment project[J]. Front. Eng, 2017, 4(2): 127-137.
[6] Takashi KANETA, Shuzo FURUSAKA, Nisi DENG. Overview and problems of BIM implementation in Japan[J]. Front. Eng, 2017, 4(2): 146-155.
[7] Benachir MEDJDOUB, Moulay Larbi CHALAL. Impact of household transitions on domestic energy consumption and its applicability to urban energy planning[J]. Front. Eng, 2017, 4(2): 171-183.
[8] SangHyun LEE. Applying system dynamics to strategic decision making in construction[J]. Front. Eng, 2017, 4(1): 35-40.
[9] Eric SCHEEPBOUWER, Douglas D. GRANSBERG, Carla Lopez del PUERTO. Construction engineering management culture shift: Is the lowest tender offer dead?[J]. Front. Eng, 2017, 4(1): 49-57.
[10] Shu-lin Zhang. Strengthening Project Management to Attain Overseas Blocks with High Potential for Exploration[J]. Front. Eng, 2016, 3(4): 331-337.
[11] Zhen-you Li,Ji-shan He,Meng-jun Wang. Improving Internationally Core Competences Based on the Capabilities of Precise and Accurate Project Management[J]. Front. Eng, 2016, 3(3): 231-238.
[12] Elizabeth A. Cudney,William L. Gillis. Quality Function Deployment Implementation in Construction: A Systematic Literature Review[J]. Front. Eng, 2016, 3(3): 224-230.
[13] David A. Wyrick,Warren Myers. Strategic Project Management to Use the Grand Challenge Scholars Program to Address Urban Infrastructure[J]. Front. Eng, 2016, 3(3): 203-205.
[14] Geert Letens,Kurt Verweire,Peter De Prins. Large Scale Infrastructure Projects: The Art of Project or Change Management?[J]. Front. Eng, 2016, 3(3): 197-202.
[15] Ling-ling Zhang,Ming-hui Zhao,Qiao Wang. Research on Knowledge Sharing and Transfer in Remanufacturing Engineering Management Based on SECI Model[J]. Front. Eng, 2016, 3(2): 136-143.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed