People and Skills: A Potential Risk in ICT Infrastructure Management

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1 People and Skills: A Potential Risk in ICT Infrastructure Management Malaya Kumar Nayak 1, Sanghamitra Mohanty 2, Rachna Soni 3 1,2 Dept. of Computer Science & Applications, Utkal University, Bhubaneswar, INDIA 3 Department of Computer Science & Applications, D.A.V. College for Girls, Yamunanagar, INDIA Abstract This paper describes an approach used to reveal dynamics operating in supply of, and demand for, skilled Information and Communications Technology (ICT) employees. The impacts of changing demographics of the work force and society are investigated. The paper is much about what is needed to achieve implementation success as it is about the effective application job allocation strategy. The work force skill projecting model has been proposed which includes the conceptual matrix of IT and domain skills: a space diagram where the various IT and IT related professional could be placed. Through this the managers of ICT infrastructure can decide on the job allocations to human resource of their project in terms of skill cost and skill efficiency of the human resource. Keywords: ICT infrastructure, ICT skills, Human resource, Skill cost, Skill efficiency. 1. Introduction Human resources related to ICT need close monitoring and development if the economic development and social transformation is required. The available national information related to ICT skills, is in most cases, fragmented and piece meal. To develop a reliable and meaningful scenario of human resources for ICT its present status, trends in demand and supply and most importantly the changing pattern of demand for ICT skills should be taken care of. 2. Global and Regional Trends Globalization and increasing diffusion and penetration of ICTs every region are most significant trends that have profound effect not only on the ICT sector but on the region s economy as a whole, as much as on its social fabric. The forces of globalization are leveling the playing field for every country, community and individual. Internet and web technologies are making it possible for buyers of products to locate the most economical source anywhere in the world and likewise for a seller to locate the most lucrative markets for his or her products, without the distortions of a middle man. What applies to physical products applies to services as well, in the sense that the market for most services (if not all) is as much global as it is for physical tangible products. In the emerging globalize and networked world we may be in way approaching Adam Smith s vision of perfect competition. 135

2 This process of globalization and market integration for both products and services sustained by the increased adoption of ICTs has brought the market to the door steps of the producers and service providers, no matter where in the world they are located [1]. The needs for ICT human resources in a country are related to the level of ICT activities in that country. As the world ICT markets are getting more and more globalized and as the region takes an increasingly larger share of the global ICT products and services markets, the global ICT market trends would be as much important for determining the regional ICT manpower needs as would be the developments in the domestic markets of the region[3]. 3. Defining and Classifying ICT Skills In assessing and evaluating the status of and trends in human resources and skills for information and communication technology it is important to clearly define the skills that may be termed as ICT skills. There is no standard international or regional definition and classification for ICT skills, which are universally accepted and used [12]. Various organizations, institutions and individuals concerned with ICTs or with professional human resources management have variously defined ICT skills and occupations. For instance the Bureau of Labour Statistics and the Department of Commerce of the government of Europe and the United States use a classification scheme that includes two main classes of workers: core IT workers and IT related workers [6]. The former consists of four occupations: Computer Scientist, Computer Engineers, Systems Analysts and Computer Programmer. The latter in contrast consists of some 23 occupations which use ICT intensively and are closely related to ICT industry. The ILO 1990 scheme for IT occupation classification ISCO88 has some 390 job categories and uses a different classification scheme for IT related workers [9]. In both of these classification systems it can be observed that ICT skills have been narrowly focused on computer, communication and electronics hardware. This is understandable since these classification schemes were developed at a time when IT had very narrow applicability and software, services and web based technologies had yet to emerge. National Workforce Centre for Emerging Technologies based in USA has used a cluster based classification that comes close to present day realities but leaves out a number of important ICT skill areas such as information security and protection; and the ICT skills at the user end that would inevitably consist of a combination of IT skills with the so called domain skills and industry vertical know how. The work force skill projecting models proposed by Freeman and Aspray [7] has, among others, included the following conceptual matrix of IT and domain skills: a space diagram where the various IT and IT related professional could be placed. Each point on the diagram determines a set mix of ICT and domain Knowledge corresponding to the job responsibilities of the various occupations in the ICT, ICT enabled and user sectors. The ICT skill development policies and strategies at the national and regional level will have to be holistic in order to cover the ICT skill needs of all sections and segments of the nation or the region at their various levels [13]. This would for instance involve looking at skill needs of the ICT industry; IT enabled sectors, IT user sectors and even that of the general public at its most basic level. 136

3 There are three types: A. ICT professional skills in the ICT industry: These encompass the ICT skills needed in the ICT sector itself and could include all ICT industries, hardware manufacturers, ICT service providers, ICT consultants, ICT Researchers and ICT Trainers. These has been further subdivided into 1) Core ICT worker skills 2) Advanced ICT worker skills 3) ICT Researchers and Teachers B. ICT Professional skills in the User sectors C. ICT Users: There are two types of ICT users 1. Advanced user skills (Active Users) 2. Basic user skills 4. Demands for ICT Skills The present day globalized world shortages and surpluses in one part of the globe would influence the demand and supply elsewhere. The web and internet technologies have made most ICT and ICT based jobs location independent. For instance a software engineer in China, India or Malaysia could now be working for a US company without physical relocation to US. Thus for all practical purposes the ICT skills in India or china or elsewhere with good connectivity would be available to anyone in the world [4]. The international companies or other employers, wishing to take advantage of the lower skill costs in the developing world have the following options: 1) Relocate a part of their operations to low cost locations though establishment of fully owned subsidiary companies; set up joint venture companies and acquire local companies in the low cost countries. 2) Offshore work to local companies and institutions in low cost countries. 3) Hire individual professionals located in low cost countries to work remotely. 4) Recruit professionals from the low cost countries and relocate them to home of the employing company. While the fourth option mentioned above has been the traditional method of utilizing qualified low cost manpower from developing countries, the other three options have become common in the recent past. 5. ICT Diffusion and Its Implication on Human Resource Skills ICT diffusion is rapidly taking place in most countries of the region. This implies the need for ICT skills that could keep the ICT industry efficiently running to feed the domestic market. In addition the ICT adoption in the country would alter the pattern of demand for human resource skills in the economy in its entirety. Some skills will become redundant as the ICT is adopted in a particular industry and some others would emerge. As the ICTs penetrate deeper in a country the Human Resource skills in all economic and social sectors would change [7]. This does not refer to ICT skills only but 137

4 to the skills associated with most occupations. This is an important challenge the leaders and policy makers face in this region and indeed in every country of the world. 6. Proposed Model In the proposed model we have assumed that we have n skills and m skilled employees.assuming m<n and applying sensitivity for job allocation such that the remaining n-m skills are allocated according to the managerial decision. The skill costs and skill efficiency are represented through bipartite network Algorithm During the optimization of job allocation we maintain a potential y network and an orientation of G y (denoted by ) which has the property that the edges oriented from E(E1,E2.Em) to S(S1,S2 Sn) form a matching M. Initially, y is 0 everywhere, and all edges are oriented from S to E (so M is empty). In each step, either we modify y so that its value increases, or modify the orientation to obtain a matching with more edges. We maintain the invariant that all the edges of M are tight. We are done if M is a perfect matching. In a general step, let and R E E be the vertices not covered by M (so R S consists of the vertices in S with no incoming edge and R E consists of the vertices in E with no outgoing edge). Let Z be the set of vertices reachable in from R S by a directed path only following edges that are tight. This can be computed by breadth -first search. If R E Z is nonempty, then reverse the orientation of a directed path in from R S to R E. Thus the size of the corresponding matching increases by 1. If R E Z is empty, then let. : = min { c(i,j) y(i) y(j) : i Z S, J E \ Z } Δ is positive because there are no tight edges between and Increase y by Δ on the vertices of and decrease y by Δ on the vertices of Z E. The resulting y is still a potential. The graph G y changes, but it still contains M. We orient the new edges from S to E. By the definition of Δ the set Z of vertices reachable from R S increases (note that the number of tight edges does not necessarily increase). We repeat these steps until M is a perfect matching, in which case it gives a minimum cost assignment. The running time of this version of the method is O(n 4 ): M is augmented n times, and in a phase where M is unchanged, there are at most n potential changes (since Z increases every time). The time needed for a potential change is O(n 2 ). The following notations are used: y= Orientation of graph from E to S. G y = Directed Network M= Weights of different edges. E i = The skilled employees. i=1,2..m. 138

5 S j = The skills. i=1,2 n. c (i,j) = Cost that employee E i receives for doing S j skill. R E = Subset of E. R S = Subset of S. Z= Set of vertices reachable in G y. = Minimized value after row reduce & column reduce. Here two cases are taken firstly in terms of skill cost, then secondly in terms of skill efficiency of the employee Case I: Here using the above algorithm M is taken as the skill cost to get the optimal solution for job allocation to differently skilled employees. Table 1 and Figure 2 represent the data taken. Table 1. Skill Cost Matrix in Rs. Per Thousand Figure 1. Skill Cost Network 139

6 Figure 2. Optimal Solution for Cost The Figure 2 represents the optimal solution for job allocation to different employees. Here E1 and E4 Employees were assumed to be more skilled ones. The optimal skill cost for the total project comes out to be Rs 83 thousand. Optimally S1 and S3 skill jobs are being assigned to only one employee E4 and S2 and S7 skill jobs are being assigned to E Case II: Here the algorithm uses M as skill efficiency of the employee in terms of job completion in monthly hours. Table 2 and Figure 3 represent the data taken. Table2. Skill Efficiency Matrix in Monthly Hours Figure 3. Skill Efficiency Network 140

7 Figure 4. Optimal Solution for Efficiency The Figure 4 represents the optimal solution for job allocation to different employees in terms of skill efficiency. Here E1 and E4 employees were assumed to be more skilled ones. Optimally S1 and S4 skill jobs are being assigned to only one employee E4 and S5 and S7 skill jobs are being assigned to E1 as to in. Bipartite graphs are useful for modeling matching problems. Here we have set E of employees and a set S of skills with not all people suitable for all skilled jobs. The day assumed in the non empirical data is 25 in a month. 7. Conclusions We discussed the problem of human resource allocation considering skill cost and skill performance. We defined two cases using an algorithm to deal with human resource allocation with different optimization goals: one skill cost and skill efficiency. The two cases through the algorithm provide the best tradeoff between skill cost and skill performance. Through this the managers of ICT infrastructure can decide on the job allocations to human resource of their project in terms of skill cost and skill efficiency of the human resource. References [1] Araya, S., Chaparo, J., Orero, A., and Joglar, H., An integrative view of IS/IT and organizational resources and capabilities, Issues in Informing Science and Information Technology, 4, 2007, pp [2] Barton, R., Global IT management: A practical approach, Great Britain: Wiley, [3] Best Management Practice, Service management ITIL (IT Infrastructure library), [4] Bless, C. and Higson-Smith, C., Integrated ICT Management Framework, [5] Cordis, The European technology platforms (ETPs) and the future Internet, Retrieved 17/11/2007 [6] Chernyshev, I., ed., Labour statistics for a market economy: Challenges and solutions in the Transition Countries of Central and Eastern Europe and the Former Soviet Union, Central European University Press, Budapest, [7] Freeman, P. A., and Aspray, W., The Supply of Information Technology Workers in the United states, Washington, D.C.: Computing Research Association, [www.cra.org/reports/wits/cra.wits.html] [8] IT Governance Institute, Aligning COBIT, ITIL and ISO for business benefit: A management briefing from ITGI and OG, [9] ILO, ISCO-88: International Standard Classification of Occupations, International Labour Office, Geneva, 1987 (French and Spanish editions: Russian edition: 1997.), [10] Lucas, Jr. H. C., Information technology: Strategic decision making for managers, USA: John Wiley & Sons,

8 [11] Orange Tree Projects Solutions, [12] Thamhain, H. J., Management of technology: Managing effectively in technology-intensive organisations, USA: John Wiley & Sons, [13] Thiadens, T., Manage IT: Organising IT demand and IT supply, The Netherlands: Springer, [14] Turban, E., Rainer Jr, R. K. and Potter, R., Introduction to information technology (3rd ed.), USA: John Wiley & Sons, [15] Welman, J. C. and Kruger, S. J., Research methodology (2nd ed.), Cape Town: Oxford University Press, Authors Malaya Kumar Nayak is a PhD student in Computer Science at Utkal University and he is working as a Partner with Optimity Ltd, London. He received his M.S. ICT degree from Assumption University of Thailand and MCA degree from Punjab Technical University. He is a Chartered Fellow of the BCS - The Chartered Institute for IT and Senior Member of the IEEE & IEEE Computer Society. He obtained a Chartered Engineer (CEng) from Engineering Council UK and Certified IT Project Manager (CITPM) from Singapore Computer Society. He has published 15 papers in International/national journals /books/conferences. His current research interests are Software Engineering, Security, Project Management and Risk Management. Dr. Sanghamitra Mohanty is a Professor and Head of the Dept. Computer Science & Applications, Utkal University. She has published 136 papers in National and International Journals and Conferences and has guided several Ph.D. scholars. She has obtained 10 Intellectual Property Rights on her research outcomes. Her current research interests are Human Computer Interface, Software Engineering and Knowledge Engineering. Dr. Rachna Soni is an Associate Professor and Head, Dept. of Computer Science & Applications. She did her M. Phil from IIT, Roorkee and Ph.D. from Kururukshetra University, Kurukshetra. She has more than eighteen years teaching experience in the institution of repute. She has published several papers in International/national journal /conferences. Her area of interest includes Software Risk Management, Project Management, Requirement Engineering, Simulation and Component based Software Engineering. 142

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