一种基于移动互联网的扁平化管理平台
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摘要
传统的层次化管理具有层级分明、职责清晰、工作流程严格等特点,来源于对军队管理体系的模仿,被普遍运用于政府机构、生产制造等各个领域;随着组织的规模越来越大,管理者与被管理者的关系随之复杂化,而每个管理者的能力、精力与时间都是有限的,当直接管理的下属人数超过某个限度时,必须增加一个管理层次。随着层次的增多,由于各层之间乃至同一层次的工作人员对信息重要性的认知程度、工作习惯等客观差异,容易导致信息传递及时性的降低;因为相关人员的成长背景、工作经历、知识背景、理解能力等存在客观差异,很容易导致信息在交互的过程中发生"变形",影响信息交互的准确性;再次,在实际工作中非"面对面"的情况下,上级部署的任务对于下级是否能真实的完成,完成质量如何等,如果不能建立便捷的信息交互机制,很难进行监管。针对此类问题,OA(office automation,办公自动化)系统曾经被大面积地采用,但是实践证明,大多数OA只是把传统的层次化管理简单地移植到互联网上,层层汇报、层层审批、层层传阅等客观问题仍然存在,有些部门不管事情多紧急,不管是否要变通,OA系统通不过,一切免谈,加剧了部门官僚现象的发生。与之同时,微信、QQ等即时通讯工具,由于其表现内容的图文并茂(富媒体性)、自主编辑和表达内容(自媒体性)、现场感强、随时能发布(跨时空维度),以及能够让内容即刻抵达受众(点对点、点对面)等主要特征,成为人们日常通联的主要平台,也是承载思想、传递业务、交流工作等的大数据平台,所以,很多单位、部门或个人,已经习惯于在微信和QQ等即时通讯平台上处理工作事务。这种现象实际上蕴藏着很大的风险,主要原因在于:1)平台上产生的数据均被第三方(腾讯等公司)拿走,单位的业务内容成为存放在他人服务器上的数据资源,单位的隐私存在极大的泄露风险,同时,由于数据不在自己手中,单位很难去开采数据资源,挖掘其成为驱动业务、驱动管理的数据潜力;2)微信、QQ等属于社交平台,社会关系复杂、平台内容繁荣多样,业务信息很容易被有意或无意地传播或泄露出去,既影响单位形象,又可能造成负面的经济和社会影响;3)由于平台既有的特征,重要业务信息很容易被稀释,例如,同一群里不同领导发布的任务、业务指导等重要信息,很容易形成相互交叉,导致业务讨论线索混乱,难以形成条理清晰、内容完整、指向明确的信息专题。针对以上问题,以提升管理效能为核心面向,以数据为核心资产,从提升单位内部的信息交互能力和效率出发,设计并研发一种支持业务数据自有和自主分析,依托移动互联网的扁平化管理平台。平台具有专用的数据采集端、发布端、整理和分析后台,在提升了信息交互的及时性、现场性、富媒体和跨时空维度的同时,也能够对数据进行梳理、挖掘和提炼,形成业务进度的追踪与客观分析;同时,为了提升该平台的针对性和实用性,结合张承高速承德段管理处的实际需求,将平台投入应用,并经历了两年多的完善升级,实践证明,平台为管理处发现热点、捕获问题、监控全局等提供了有力的支持,有效提高了全员的凝聚力、战斗力和向心力,有效提高了管理效率。研究结果可为相关单位或研究者在层次化组织机构中实现扁平化信息交互和管理提供借鉴。
The traditional hierarchical management has the characteristics of clear hierarchy,clear responsibilities and strict workflow.It originates from the imitation of military management system and is widely used in various fields such as government agencies,production and manufacturing.At the same time,with the growing size of the organization,the relationship between managers and managed people becomes more complex,and each manager's ability,energy and time are limited.When the number of subordinates directly managed exceeds a certain limit,a management level must be added.With the levels increase,the staff at different levels and even at the same level will easily reduce the timeliness of information transmission because of the objective differences in the degree of recognition of the importance of information,work habits,etc.At the same time,because of the objective differences in the growth background,work experience,knowledge background and understanding ability of the relevant personnel,it is easy to lead to information misunderstanding in the process of interaction,and affects the accuracy of information interactions.Thirdly,in the actual work,it is difficult for a superior to supervise the deployed tasks,whether the subordinates can actually accomplish the tasks and how to accomplish and the quality in the case of non-faceto-face.If we cannot establish a convenient information interaction mechanism,it is difficult to supervise.In response to such problems,OA(Office Automation)systems have been widely used,but the result has proved that most OAs simply transplant the traditional hierarchical management to the Internet.There are still objective problems such as layer-by-layer reporting,layer-by-layer approval,layer-by-layer circulation,and so on.Some departments,no matter how urgent the things are,no matter whether they need to be flexible or not,only depends on the approval result of OA system.Nevertheless,all exemptions aggravate the occurrence of bureaucratic phenomena in departments.At the same time,instant messaging tools such as WeChat and QQ have become the main platform for people's daily interaction because of their main features such as abundant graphics and texts(rich media),self-editing and expressing content(self-media),strong sense of scene,being able to publish contents at any time(spatio-temporal dimension),and being able to immediately reach the audience(point-to-point,point-to-area)and so on.And they also have become the the big data platform that carries ideas,delivers business,communicates work and so on,many units,departments or individuals have been accustomed to handling work affairs on the instant messaging platform such as WeChat and QQ.In fact,this phenomenon contains a lot of risks.The main reasons are as follows:1)the data generated on the platform are taken away by the third party(Tencent and other companies).The business content of the unit becomes the data resources stored on other people's servers.The privacy of the unit has a great risk of leakage.At the same time,because the data is not in its own hands,it is very difficult for the unit to exploit the data resources and make them become driven power of business and management;2)WeChat and QQ belong to social platform,with complex social relations and prosperous and diverse platform content.Business information can easily be disseminated or leaked intentionally or unintentionally,which not only affects the image of the unit,but also may cause huge negative economic and social impact;3)Because of the existing characteristics of the platform,important business information can easily be diluted.For example,important information such as tasks and business guidance issued by differentleaders in the same group can easily cross each other,leading to confusion in business discussion clues,and difficult to form clear,complete and clear information topics.In order to solve the above problems,this paper designs and develops a flat management platform supporting business data self-owned and self-analysis,relying on mobile internet,which aims to improve the management efficiency,make data as the core asset,and enhance the information interaction ability and efficiency within the unit.The platform has a dedicated data acquisition,publishing,collation and analysis backstage,which not only improves the timeliness,on-the-spot,rich media and cross-temporal dimension of information interaction,but also combs,excavates and refines the data to form the tracking and objective analysis of business progress.At the same time,in order to enhance the pertinence and practicability of the platform,this paper considers the real needs from Hebei province expressway Zhang-Cheng Chengde Management Office.The platform has been put into use and improved for more than two years.Practice has proved that the platform provides strong support for the management department in discovering hot spots,capturing problems,monitoring the overall situation,effectively improving the cohesion,combat effectiveness and centripetal force of the whole staff,and effectively improving the management efficiency.This platform provides reference support for concerned units and study to realize flat information interaction and management in hierarchical management.
The traditional hierarchical management has the characteristics of clear hierarchy,clear responsibilities and strict workflow.It originates from the imitation of military management system and is widely used in various fields such as government agencies,production and manufacturing.At the same time,with the growing size of the organization,the relationship between managers and managed people becomes more complex,and each manager's ability,energy and time are limited.When the number of subordinates directly managed exceeds a certain limit,a management level must be added.With the levels increase,the staff at different levels and even at the same level will easily reduce the timeliness of information transmission because of the objective differences in the degree of recognition of the importance of information,work habits,etc.At the same time,because of the objective differences in the growth background,work experience,knowledge background and understanding ability of the relevant personnel,it is easy to lead to information misunderstanding in the process of interaction,and affects the accuracy of information interactions.Thirdly,in the actual work,it is difficult for a superior to supervise the deployed tasks,whether the subordinates can actually accomplish the tasks and how to accomplish and the quality in the case of non-faceto-face.If we cannot establish a convenient information interaction mechanism,it is difficult to supervise.In response to such problems,OA(Office Automation)systems have been widely used,but the result has proved that most OAs simply transplant the traditional hierarchical management to the Internet.There are still objective problems such as layer-by-layer reporting,layer-by-layer approval,layer-by-layer circulation,and so on.Some departments,no matter how urgent the things are,no matter whether they need to be flexible or not,only depends on the approval result of OA system.Nevertheless,all exemptions aggravate the occurrence of bureaucratic phenomena in departments.At the same time,instant messaging tools such as WeChat and QQ have become the main platform for people's daily interaction because of their main features such as abundant graphics and texts(rich media),self-editing and expressing content(self-media),strong sense of scene,being able to publish contents at any time(spatio-temporal dimension),and being able to immediately reach the audience(point-to-point,point-to-area)and so on.And they also have become the the big data platform that carries ideas,delivers business,communicates work and so on,many units,departments or individuals have been accustomed to handling work affairs on the instant messaging platform such as WeChat and QQ.In fact,this phenomenon contains a lot of risks.The main reasons are as follows:1)the data generated on the platform are taken away by the third party(Tencent and other companies).The business content of the unit becomes the data resources stored on other people's servers.The privacy of the unit has a great risk of leakage.At the same time,because the data is not in its own hands,it is very difficult for the unit to exploit the data resources and make them become driven power of business and management;2)WeChat and QQ belong to social platform,with complex social relations and prosperous and diverse platform content.Business information can easily be disseminated or leaked intentionally or unintentionally,which not only affects the image of the unit,but also may cause huge negative economic and social impact;3)Because of the existing characteristics of the platform,important business information can easily be diluted.For example,important information such as tasks and business guidance issued by differentleaders in the same group can easily cross each other,leading to confusion in business discussion clues,and difficult to form clear,complete and clear information topics.In order to solve the above problems,this paper designs and develops a flat management platform supporting business data self-owned and self-analysis,relying on mobile internet,which aims to improve the management efficiency,make data as the core asset,and enhance the information interaction ability and efficiency within the unit.The platform has a dedicated data acquisition,publishing,collation and analysis backstage,which not only improves the timeliness,on-the-spot,rich media and cross-temporal dimension of information interaction,but also combs,excavates and refines the data to form the tracking and objective analysis of business progress.At the same time,in order to enhance the pertinence and practicability of the platform,this paper considers the real needs from Hebei province expressway Zhang-Cheng Chengde Management Office.The platform has been put into use and improved for more than two years.Practice has proved that the platform provides strong support for the management department in discovering hot spots,capturing problems,monitoring the overall situation,effectively improving the cohesion,combat effectiveness and centripetal force of the whole staff,and effectively improving the management efficiency.This platform provides reference support for concerned units and study to realize flat information interaction and management in hierarchical management.
引文
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[10]HE L,RAO P P.Platforms for big data analytics:Trend towards hybrid era[C]//International Conference on Energy,Communication,Data Analytics and Soft Computing(ICECDS).Chennai:[s.n.],2017:3235-3238.
[11]YUAN Tingting.Research on transformation and innovation of the traditional travel agency under the mobile interconnected thinking[J].Service Science and Management,2015,4(5):27-31.
[12]SHAHARE D.Sentiment analysis for the news data based on the social media[C]//International Conference on Intelligent Computing and Control Systems(ICICCS).Madurai:[s.n.],2017:1365-1370.
[13]LI Lei,MA Di,LIU Guanfeng.Social community-oriented social attribute analysis:An empirical study on QQ group data[C]//IEEEInternational Conference on Smart City/SocialCom/SustainCom(SmartCity).Chengdu:[s.n.],2015:457-464.
[14]ZHANG Yuanxing,LI Zhuqi,GAO Chengliang,et al.Mobile social big data:WeChat moments dataset,network applications,and opportunities[J].IEEE Network,2018,32(3):146-153.
[15]敖文萍.企业扁平化管理沟通机制研究---以中核二四公司为例[D].衡阳:南华大学,2018.AO Wenping.Study on the Communication Mechanism of Flat Management of Enterprises---Take the Example of China Nuclear Industry 24Construction CO.,LTD.[D].Hengyang:University of South China,2018.
[16]TIGANOAIA R,CERNIAN A,NICULESCU A.The use of social platforms and personal data protection:An exploratory study[C]//Networking in Education and Research(RoEduNet).Targu Mures:[s.n.],2017:1-5.
[17]HODSON W J,TRAYNOR B.Folk classification of social mediaplatforms:Preliminary finding[C]//International Professional Communication Conference(IPCC).Austin:[s.n.],2016:1-11.
[18]MISRA G,SUCH J M.How socially aware are social media privacy controls[J].Computer,2016,49(3):96-99.
[19]YIN Jian,ZHAO Dongfang.Data confidentiality challenges in big data applications[C]//2015IEEE International Conference on Big Data.Santa Clara:[s.n.],2015:2886-2888.
[20]FATKIEVA R,VOROBIEV V I,LEVONEVSKIY D K.Approach to information security control of complex computer networks[C]//International Conference on Soft Computing and Measurements(SCM).St.Petersburg:[s.n.],2016:71-72.
[21]GUPTA K K,SHUKLA S.Internet of things:Security challenges for next generation networks[C]//International Conference on Innovation and Challenges in Cyber Security(ICICCS-INBUSH).Noida:[s.n.],2016:315-318.
[22]XU Lei,JIANG Chunxiao,WANG Jian,et al.Information security in big data:Privacy and data mining[J].IEEE Access,2014,2(2):1149-1176.
[23]TAI C H,TSENG P J,YU P S,et al.Identity protection in sequential releases of dynamic networks[J].IEEE Transactions on Knowledge and Data Engineering,2014,26(3):635-651.
[24]YANG Guang.The ETC user demand forecast analysis of expressway based on traffic data[C]//2016International Conference on Intelligent Transportation,Big Data&Smart City(ICITBS).Changsha:[s.n.],2016:43-45.
[25]LIU Hesen,GUO Jiahui,YU Wenpeng,et al.The design and implementation of the enterprise level data platform and big data driven applications and analytics[C]//IEEE/PES Transmission and Distribution Conference and Exposition(T&D).Dallas:[s.n.],2016:1-5.
[26]YAN Jihong,MENG Yue,LU Lei.Big-data-driven based intelligent prognostics scheme in industry 4.0environment[C]//Prognostics and System Health Management Conference(PHM-Harbin).Harbin:[s.n.],2017:1-5.
[27]SUN Z C,LU J,LV F.Research and implementation of mobile application security detection combining static and dynamic[C]//International Conference on Measuring Technology and Mechatronics Automation(ICMTMA).Changsha:[s.n.],2018:243-247.
[28]TOBING D H.Mobile tourism application for samosir regency on android platform[C]//International Symposium on Technology Management and Emerging Technologies(ISTMET).Langkawai:[s.n.],2015:249-253.
[29]YIN S,DING S,XIE X C,et al.A review on basic data-driven approaches for industrial process monitoring[J].Transactions on Industrial Electronics,2014,61(11):6418-6428.
[30]TEMBINE H.Data-driven vs model-driven imitative learning[C]//IEEE 6th Data Driven Control and Learning Systems Conference(DDCLS).Chongqing:[s.n.],2017:22-29.
[31]JIAO W Y,CAI B,ZHAO J.Method on PID controller optimization based on the data-driven techniqueb[C]//Chinese Automation Congress(CAC).Jinan:[s.n.],2017:2567-2571.
[32]PANIGRAHI N,PANIGRAHI S S.Processing data acquired by a drone using a GIS:Designing a size-,weight-,and power-constrained system[J].IEEE Consumer Electronics Magazine,2018,7(2):50-54.
[33]杨彦波,刘滨,祁明月.信息可视化研究综述[J].河北科技大学学报,2014,35(1):91-102.YANG Yanbo,LIU Bin,QI Mingyue.Reveiw of information visualization[J].Journal of Hebei University of Science and Technology,2014,35(1):91-102.
[34]SCHROEDER D,KEEFE D F.Visualization-by-Sketching:An artist's interface for creating multivariate time-varying data visualizations[J].IEEE Transactions on Visualization and Computer Graphics,2016,22(1):877-885.
[35]GODFREY P,GRYZ J,LASEK P.Interactive visualization of large data sets[J].IEEE Transactions on Knowledge and Data Engineering,2016,28(8):2142-2157.
[2]FOURCADE M.Economics:The view from below[J].Swiss Journal of Economics and Statistics,2018:10.1186/s41937-017-0019-2.
[3]韩华.论新兴媒体在企业管理中的运用[J].云南社会科学,2014(1):70-73.
[4]魏锦.国企管理对新兴媒体的运用探索[J].经济管理(文摘版),2016(5):53.
[5]MURTHY M N,AJAYSAIKIRAN P.A smart office automation system using raspberry Pi(Model-B)[C]//International Conference on Current Trends Towards Converging Technologies(ICCTCT).Coimbatore:[s.n.],2018:1-5.
[6]KUMAR S,GOYAL R,JACOB P T.Office automation for digital India[C]//International Conference on Emerging Trends and Innovations in Engineering and Technological Research(ICETIETR).Ernakulam:[s.n.],2018:1-6.
[7]LIBAIER D.Enterprise office automation system design and implementation[C]//2015Seventh International Conference on Measuring Technology and Mechatronics Automation.Nanchang:[s.n.],2015:457-461.
[8]腾讯控股有限公司.腾讯2018年一季度财报[R].深圳:腾讯控股有限公司,2018.
[9]PARK K,NGUYEN M C,WON H.Web-based collaborative big data analytics on big data as a service platform[C]//International Conference on Advanced Communication Technology(ICACT).Seoul:[s.n.],2015:564-567.
[10]HE L,RAO P P.Platforms for big data analytics:Trend towards hybrid era[C]//International Conference on Energy,Communication,Data Analytics and Soft Computing(ICECDS).Chennai:[s.n.],2017:3235-3238.
[11]YUAN Tingting.Research on transformation and innovation of the traditional travel agency under the mobile interconnected thinking[J].Service Science and Management,2015,4(5):27-31.
[12]SHAHARE D.Sentiment analysis for the news data based on the social media[C]//International Conference on Intelligent Computing and Control Systems(ICICCS).Madurai:[s.n.],2017:1365-1370.
[13]LI Lei,MA Di,LIU Guanfeng.Social community-oriented social attribute analysis:An empirical study on QQ group data[C]//IEEEInternational Conference on Smart City/SocialCom/SustainCom(SmartCity).Chengdu:[s.n.],2015:457-464.
[14]ZHANG Yuanxing,LI Zhuqi,GAO Chengliang,et al.Mobile social big data:WeChat moments dataset,network applications,and opportunities[J].IEEE Network,2018,32(3):146-153.
[15]敖文萍.企业扁平化管理沟通机制研究---以中核二四公司为例[D].衡阳:南华大学,2018.AO Wenping.Study on the Communication Mechanism of Flat Management of Enterprises---Take the Example of China Nuclear Industry 24Construction CO.,LTD.[D].Hengyang:University of South China,2018.
[16]TIGANOAIA R,CERNIAN A,NICULESCU A.The use of social platforms and personal data protection:An exploratory study[C]//Networking in Education and Research(RoEduNet).Targu Mures:[s.n.],2017:1-5.
[17]HODSON W J,TRAYNOR B.Folk classification of social mediaplatforms:Preliminary finding[C]//International Professional Communication Conference(IPCC).Austin:[s.n.],2016:1-11.
[18]MISRA G,SUCH J M.How socially aware are social media privacy controls[J].Computer,2016,49(3):96-99.
[19]YIN Jian,ZHAO Dongfang.Data confidentiality challenges in big data applications[C]//2015IEEE International Conference on Big Data.Santa Clara:[s.n.],2015:2886-2888.
[20]FATKIEVA R,VOROBIEV V I,LEVONEVSKIY D K.Approach to information security control of complex computer networks[C]//International Conference on Soft Computing and Measurements(SCM).St.Petersburg:[s.n.],2016:71-72.
[21]GUPTA K K,SHUKLA S.Internet of things:Security challenges for next generation networks[C]//International Conference on Innovation and Challenges in Cyber Security(ICICCS-INBUSH).Noida:[s.n.],2016:315-318.
[22]XU Lei,JIANG Chunxiao,WANG Jian,et al.Information security in big data:Privacy and data mining[J].IEEE Access,2014,2(2):1149-1176.
[23]TAI C H,TSENG P J,YU P S,et al.Identity protection in sequential releases of dynamic networks[J].IEEE Transactions on Knowledge and Data Engineering,2014,26(3):635-651.
[24]YANG Guang.The ETC user demand forecast analysis of expressway based on traffic data[C]//2016International Conference on Intelligent Transportation,Big Data&Smart City(ICITBS).Changsha:[s.n.],2016:43-45.
[25]LIU Hesen,GUO Jiahui,YU Wenpeng,et al.The design and implementation of the enterprise level data platform and big data driven applications and analytics[C]//IEEE/PES Transmission and Distribution Conference and Exposition(T&D).Dallas:[s.n.],2016:1-5.
[26]YAN Jihong,MENG Yue,LU Lei.Big-data-driven based intelligent prognostics scheme in industry 4.0environment[C]//Prognostics and System Health Management Conference(PHM-Harbin).Harbin:[s.n.],2017:1-5.
[27]SUN Z C,LU J,LV F.Research and implementation of mobile application security detection combining static and dynamic[C]//International Conference on Measuring Technology and Mechatronics Automation(ICMTMA).Changsha:[s.n.],2018:243-247.
[28]TOBING D H.Mobile tourism application for samosir regency on android platform[C]//International Symposium on Technology Management and Emerging Technologies(ISTMET).Langkawai:[s.n.],2015:249-253.
[29]YIN S,DING S,XIE X C,et al.A review on basic data-driven approaches for industrial process monitoring[J].Transactions on Industrial Electronics,2014,61(11):6418-6428.
[30]TEMBINE H.Data-driven vs model-driven imitative learning[C]//IEEE 6th Data Driven Control and Learning Systems Conference(DDCLS).Chongqing:[s.n.],2017:22-29.
[31]JIAO W Y,CAI B,ZHAO J.Method on PID controller optimization based on the data-driven techniqueb[C]//Chinese Automation Congress(CAC).Jinan:[s.n.],2017:2567-2571.
[32]PANIGRAHI N,PANIGRAHI S S.Processing data acquired by a drone using a GIS:Designing a size-,weight-,and power-constrained system[J].IEEE Consumer Electronics Magazine,2018,7(2):50-54.
[33]杨彦波,刘滨,祁明月.信息可视化研究综述[J].河北科技大学学报,2014,35(1):91-102.YANG Yanbo,LIU Bin,QI Mingyue.Reveiw of information visualization[J].Journal of Hebei University of Science and Technology,2014,35(1):91-102.
[34]SCHROEDER D,KEEFE D F.Visualization-by-Sketching:An artist's interface for creating multivariate time-varying data visualizations[J].IEEE Transactions on Visualization and Computer Graphics,2016,22(1):877-885.
[35]GODFREY P,GRYZ J,LASEK P.Interactive visualization of large data sets[J].IEEE Transactions on Knowledge and Data Engineering,2016,28(8):2142-2157.