A. K. Saini

Implementing Best Practices in ERP for Small & Medium Enterprises

As the Business Gateway to the world, Enterprise Resource Planning (ERP) changed the very concept of IT & Business. Although ERP systems may seem complex and costly, even small businesses are increasingly finding it necessary to invest in order to remain competitive. This research provides an interesting insight into taking ERP implementation as a project and develops problem driven approach to examine its complex phenomena. The implementation process will be divided into several components which will reflect the nature of ERP projects and makes them distinctive from other systems design methods. This paper also addresses critical issues relating to developing entrepreneurship for sustainable development of small and medium size enterprises(SMEs) for its future extensions and added benefits. It may also be useful for managing other outsourced Information System (IS) projects that have implementation settings similar to ERP.

A Comparative Analysis & Enhancement of NTRU Algorithm for Network Security and Performance Improvement

Security is a vexing, costly and complicated business. A single lapse can be expensive in lost funds, records and reputation. The NTRU algorithm can be used in a variety of applications which involve security across a network. In this research paper, we introduce the general structure of NTRU cryptosystem, its performance analysis and some enhancements of the algorithm. We have also studied the previous algorithms, found out their exact limitations, and developed the NTRU algorithm which is providing a solution to overcome the limitations of these algorithms. In this way we are also increasing the usefulness of NTRU algorithm and its robustness.

An exploratory factor analysis on pragmatic Lean ERP implementation for SMEs

Getting Lean is pragmatic and all about continuous development. In cut throat world of international business scenario where small and medium companies implementing ERP, improvement becomes a condition of survival not something they do when they get time. In most business, the root causes today are the same ones that existed two weeks ago and are the same ones that existed two years ago. With cost pressures mounting, SMEs are facing strong growth headwinds. This paper covers the most important issues related to measurement of modern ERP performance review for setting effective policies for high performance business through better project management and tailoring parameters. This paper tries to explore and prioritize the factors through SPSS 18.0 that influences, controls and empowers the modern ERP implementation particularly for Delhi-NCR based small and medium enterprises (SMEs). Later on, Reliability analysis for each construct conducted to the users utmost guidance..

ERP Redefined: Optimizing Parameters with Lean Six Sigma for Small & Medium Enterprises

Think Globally and Act Locally. Globalization, once the domain for only large companies, is now presenting new markets for the growth of small to mid market companies. ERP can be the road to prosperity for SMEs if one can select steps to implement Lean Six Sigma approach carefully to make the organization proficient and profitable. Besides the analysis of optimizing or tailoring parameters during ERP implementation suggests that even without new module development, small companies may be able to build unique functionality into a standard ERP system to their competitive advantages. While our ancient MRP-centric ERP is largely obsolete, this paper presents an evolving and sustainable Enterprise System approach which will definitely live on by mutating and adapting to a new world of shrinking cycle times, budgets, non-value-added activities and head counts.

A process model for preliminary classification of knowledge sources using dependency graphs and incremental computing concepts

Knowledge extraction from semi-structured or unstructured documents and texts can be handled by various approaches and viewpoints, including theoretical or mathematical constructions and matrix algebra applications to various ontologies and implementation techniques.

Modeling Trust Based Risk Management in Cloud Adoption using Fuzzy Inference System

Cloud has revolutionized the entire landscape of IT usage, storage and maintenance. It has shifted the focus from owning physical IT infrastructure, facility and storage to the use of same in an abstract form with pay per use facility. This has led to economizing the entire IT infrastructure. Clouds various characteristics including on demand pay per use, scalability and flexibility of computing highly depends on cloud service provider which can often lead to low results and serious issues. These issues may include concerns about losses due to non-compliance with the promises made. Hence selection of cloud service provider can play a positive or negative role in establishing an initial trust between the cloud service client and provider. The authors propose a model of Trust based Risk management of cloud adoption which can be used by cloud users. The model provides the functioning of comparing service providers using calculated trust ratings.

Modeling risk management in Cloud Adoption

Cloud Adoption is associated with a number of risks. Modeling risk management in cloud adoption becomes imperative. Cloud adoption risk analysis model (CARA) is designed to guide companies through the process of cloud adoption. It calculates the potential losses on the basis of various risk scenarios. It also guides through cloud service provider selection.

A Data-Driven View of the Evolving IT Infrastructure Technologies and Options

For effective service delivery on any infrastructure and SOA-based environment, data is an essential building block both as inputs as well as in monitoring the output. Data is an integral part of any formation delivery and/or service delivery in an IT-enabled business environment. For the new-age IT infrastructure models with cloud and virtualization technology options and web-based service-delivery models, recording of the characteristic data parameters that define or govern the run-time service delivery environment is crucial both for client businesses and provider organizations to be cost-viable and quality-effective. In this paper, we create a data-driven framework of the new-age IT Infrastructure. Operationally, this framework can be used for IT-user organizations as well as service providers, to track their delivery concerns. Strategically, this framework may serve as a baseline template to plan for a minimal set of parameters recoded as operational data-points from the real-time run-time IT infrastructure operations environment.

Reusable knowledge pattern extraction from peer-to-peer communication elements

Tacit knowledge embedded in various communication elements are highly unstructured, embedded in short message texts, and can be highly contextual thereby rendering generic English language thesaurus-based pattern recognition and extraction mechanisms relatively less useful. However, this embedded tacit knowledge is a significant source of context-specific, technical, problem-solving knowledge. Peer-to-peer communication threads have highly valuable problem-solution knowledge elements embedded in them. If these knowledge elements can be extracted, experiential knowledge in specific domains or technology areas can be significantly enhanced. In this paper, a process model has been designed, with algorithms developed and validated using appropriate examples, for extracting these reusable knowledge patterns from various peer-to-peer communication elements in any organisation or in the social network environment. Using this process model, the knowledge extraction can be partially or completely automated, depending on the context-specificity of the knowledge elements and therefore the requirements of specific thesaurus or term-dictionaries.