Disambiguation - Definition and Examples in Language Studies

Disambiguation s in Language Studies In linguistics, the process of determining which sense of a word is being used in a particular context. In computational linguistics, this discriminative process is called word-sense disambiguation (WSD). Examples and Observations: It so happens that our communication, in different languages alike, allows the same word form to be used to mean different things in individual communicative transactions. The consequence is that one has to figure out, in a particular transaction, the intended meaning of a given word among its potentially associated senses. While the ambiguities arising from such multiple form-meaning associations are at the lexical level, they often have to be resolved by means of a larger context from the discourse embedding the word. Hence the different senses of the word service could only be told apart if one could look beyond the word itself, as in contrasting the players service at Wimbledon with the waiters service in Sheraton. This process of identifying word meanings in a discourse is generally known as word sense disambiguation (WSD).(Oi Yee Kwong, New Perspectives on Computational and Cognitive Strategies for Word Sense Disambiguation. Springer, 2013) Lexical Disambiguation and Word-Sense Disambiguation (WSD) Lexical disambiguation in its broadest definition is nothing less than determining the meaning of every word in context, which appears to be a largely unconscious process in people. As a computational problem, it is often described as AI-complete, that is, a problem whose solution presupposes a solution to complete natural-language understanding or common-sense reasoning (Ide and VÃ ©ronis 1998).In the field of computational linguistics, the problem is generally called word sense disambiguation (WSD) and is defined as the problem of computationally determining which sense of a word is activated by the use of the word in a particular context. WSD is essentially a task of classification: word senses are the classes, the context provides the evidence, and each occurrence of a word is assigned to one or more of its possible classes based on the evidence. This is the traditional and common characterization of WSD that sees it as an explicit process of disambiguation with respect to a fix ed inventory of word senses. Words are assumed to have a finite and discrete set of senses from a dictionary, a lexical knowledge base, or an ontology (in the latter, senses correspond to concepts that a word lexicalizes). Application-specific inventories can also be used. For instance, in a machine translation (MT) setting, one can treat word translations as word senses, an approach that is becoming increasingly feasible because of the availability of large multi-lingual parallel corpora that can serve as training data. The fixed inventory of traditional WSD reduces the complexity of the problem, but alternative fields exist . . ..(Eneko Agirre and Philip Edmonds, Introduction. Word Sense Disambiguation: Algorithms and Applications. Springer, 2007) Homonymy and Disambiguation Lexical disambiguation is well suited particularly for cases of homonymy, for instance, an occurrence of bass must be mapped onto either of the lexical items bass1 or bass2, depending on the intended meaning. Lexical disambiguation implies a cognitive choice and is a task that inhibits comprehension processes. It should be distinguished from processes that lead to a differentiation of word senses. The former task is accomplished fairly reliably also without much contextual information while the latter is not (cf. Veronis 1998, 2001). It has also been shown that homonymous words, which require disambiguation, slow down lexical access, while polysemous words, which activate a multiplicity of word senses, speed up lexical access (Rodd e.a. 2002).However, both the productive modification of semantic values and the straightforward choice between lexically different items have in common that they require additional non-lexical information.(Peter Bosch, Productivity, Polysemy, and Predicate Indexicality. Logic, Language, and Computation: 6th International Tbilisi Symposium on Logic, Language, and Computation, ed. by Balder D. ten Cate and Henk W. Zeevat. Springer, 2007) Lexical Category Disambiguation and the Principle of Likelihood Corley and Crocker (2000) present a broad-coverage model of lexical category disambiguation based on the Principle of Likelihood. Specifically, they suggest that for a sentence consisting of words w0 . . . wn, the sentence processor adopts the most likely part-of-speech sequence t0 . . . tn. More specifically, their model exploits two simple probabilities: (i) the conditional probability of word wi given a particular part of speech ti, and (ii) the probability of ti given the previous part of speech ti-1. As each word of the sentence is encountered, the system assigns it that part-of-speech ti, which maximizes the product of these two probabilities. This model capitalizes on the insight that many syntactic ambiguities have a lexical basis (MacDonald et al., 1994), as in (3): (3) The warehouse prices/makes are cheaper than the rest. These sentences are temporarily ambiguous between a reading in which prices or makes is the main verb or part of a compound noun. After being trained on a large corpus, the model predicts the most likely part of speech for prices, correctly accounting for the fact that people understand price as a noun but makes as a verb (see Crocker Corley, 2002, and references cited therein). Not only does the model account for a range of disambiguation preferences rooted in lexical category ambiguity, it also explains why, in general, people are highly accurate in resolving such ambiguities.(Matthew W. Crocker, Rational Models of Comprehension: Addressing the Performance Paradox. Twenty-First Century Psycholinguistics: Four Cornerstones, ed. by Anne Cutler. Lawrence Erlbaum, 2005) Also Known As: lexical disambiguation

Organisational factors Essay Example

Organisational factors Essay Example Organisational factors Essay Organisational factors Essay Purpose: To study and find out the organisational factors which play a significant role in the successful implementation of ERP and finally find out the relation between the factors which helps us in narrow down the factors so that we can get the most influenced factor to concentrate upon. It’s quite difficult for the company to take care of all the factors, so our next aim to find the major factor(s) which have more criticality over the others. Methods: During research project we collected the data from Primary and Secondary source.We prepared around 16 questions and get them answered from the employees and managers of the company who are currently using ERP. Apart from it we interviewed some top management level people for the detailed knowledge and its importance. Findings: After getting the results we found that we can group these factors into three groups according to the impact over the other. Introduction Enterprise Resource Planning (ERP) systems are adopted by many or ganisations to meet various challenges of information flow and competition. ERP systems help to make the key business processes to be automated and integrated in an organization.ERP systems help in timely flow of the information which can help in making efficient strategic decisions. Following pattern is followed, the related literature is reviewed. Then, hypothesis and objective is presented followed by research methodology used for study. Next, observation, findings and analysis are discussed. Finally, conclusion and suggestions are given. Literature Review 2. 1 ERP implementation success Several factors may affect ERP implementation in organizations. These factors include, lack of top management support (Supramaniam and Kuppusamy, 2011; Shah et al. , 2011; Finney and Corbett, 2007; Bhatti, 2005; Wong et al. 2005), business requirement gap (Shah et al. , 2011; Wong et al. , 2005), user involvement (Francoise et al. , 2009; Rasmy et al. , 2005) and vendor support (Al-Mashari et al. , 2006; Thavapragasam, 2003), communication and co-ordination which may cause ERP implementation failure. ERP systems always require changes in work flows which need organizational alignment which requires top management support. Top management commitment and support is noted as a critical factor which has a positive effect (i. e. positively related) on the success of ERP implementation success (Rasmy et al. 2005; Supramaniam and Kuppusamy, 2011, Shanks and Light, 1999; Shah et al. , 2011). Finney and Corbett (2007) also stated that top management support has the 1st most critical success factors regarding ERP success in his research. 2. 2 Organisational factors influencing successful ERP implementation Determining factors that are positioned behind a successful ERP system implementation has been a key research question in previous research. Implementation of an ERP system is a complex process including a great many factors and conditions which can potentially influence successful mplementation. These factors might have a positive effect on the ERP implementation project outcome, whereas the lack of these conditions could create trouble through ERP implementation. Many researchers have recognized that there are many factors that could be critical to the successful implementation of ERP. For example, [36] Somers and Nelson (2004) recognized that there are 22 critical success factors including Top management support, Education on new business processes, User training on software, On the hand, [1] Al-Mashari et al. 2003) found out that thre are 12 critical ERP factors such as ERP selection, project management, training and education, business process management, cultural and structural change management while [39] Umble et al. (2003) divided the factors into 10 categories including Commitment by top management, Clear understanding of strategic goals, Excellent implementation project management, Great implementation team, Successfully coping with technical issues , Organizational commitment to change, Data accuracy, Extensive education and training, Focused performance measures, and Multi-site issues resolved.Based on [12] Dezdar and Sulaimans (2009) work the factors can be grouped into 17 categories which subsequently can be re-organized into three main categories; organizational, project and system. [53] Dezdar (2010) found organizational factors to be quite instrumental in determining the ERP implementation success. This research focus on the following aspects of the organizational factors, i. e. Top management support, Organizational size , cooperation and coordination ,ERP training and education, and role of business vision and mission . These factors are discussed in detail in the following paragraphs. . 2. 1 Top management Top management support, has been emphasized, as a crucial factor in successful ERP implementation by many ([1] Al-Mashari et al. , 2003; [39] Umble et al. , 2003; [47] Zhang et al. , 2005). [29] Ngai et al. (2008), discussed that top management support, plays a significant role in the ERP implementation success because ERP are normally done on a large-scale and require extensive resources. Top management support has two major aspects or factors in ERP implementation projects: providing the necessary resources and providing leadership.Even the survey done for this project has shown the same results that management plays a very critical role in successful ERP implementation. 2. 2. 2 Training and education As mentioned earlier ERP is a complex system thus adequate training and education must be provided so that the users to use them effectively and efficiently ([8] Correa and Cruz, 2005; [47] Zhang et al. , 2005; [3] Bradley, 2008) and with ease. Training and education would enhance the users level of knowledge, understanding and efficiency, thus increasing individual performance and subsequently organizational performance. [27] Nah et al. 2003) stated that sufficient training can increase the pr obability of success of ERP system implementation, while inappropriate or no training can hinder its success greatly. Adequate training and education may also help the organization to build positive feelings towards the system. More important it may help ERP users to adjust to the organizational change-taking place with the implementation of the system. In addition, training increases ease of use, user acceptance and reduces user resistance, which, in turn, enhances the likelihood of ERP systems use and success ([3] Bradley, 2008). 2. 2. 3 Business mission:In order to successfully run a business, an entrepreneur needs a clear vision as to where the business is going. In other words, a business needs to know what its purpose is and where it is going. A mission statement is the perfect tool to develop in order to define a new businesss purpose, activities, and values . A mission statement should act as a lighthouse. If a company loses track of itself, it will be able to look back on t heir mission statement and be reminded of their overall purpose. In general, a mission statement should inform your workers and customers what the business is all about and where it is headed.A mission statement helps p a business to create a culture that is integrated with its overall purpose For purposes of this study, two notions, i. e. organizational mission and goals from the strategic management literature, are used to describe business vision. That said, many organizations in fact adopt ERP to meet their organizational objectives (business vision) ([8], [9] Davenport, 1998, 2000; [5] Bingi et al. , 1999). Sadly, it has been observed so far that many organizations fail to articulate their IT implementation strategy vis-a-vis overall business vision ([24] Keen, 1993; [10] Deloitte Consulting, 2000 According to [9]Davenport (2000), companies with a desire to implement ERP must be clear about their strategic intent before going for such an exercise. He quotes: In the same categor y of things that need to be settled beforehand if youre going to get value from an [ERP] is the notion of strategic clarity certainty as to what business the company is in [ ] ([9] Davenport, 2000, p. 47). 2. 2. 4 Organisation Size The journal â€Å"The impact of organization size on enterprise resource planning (ERP) implementations in the US manufacturing sector† clearly states that organisation’s size plays a very important role in successful ERP implementation.The greater the size more the need to use standardized ERP for proper information flow. In the research done, it has been found out the organizations having branches ;gt;10 are implementing ERP package. 2. 2. 5 Employee resistance The research document â€Å"Resistance to change and ERP implementation success: the moderating role of change management initiative†. It clearly states that employee resistance plays a very important role in success of ERP. Even the research conducted stated the same result s. 2. 2. 6 Standardization of single packageThe research document â€Å"Understanding the Impact of ERP Standardization on Business Process Performance† states that standardization on a single ERP package contribute greatly in success of ERP implementation. Even the study conducted also showed the same results. 2. 2. 7 Connectivity across different companies The research document â€Å"Issues in multinational ERP implementation† try to state that connectivity across the organization play significant role in ERP implementation. This research carried out even stated the same results. 2. 2. 8 Range of branches: ERP implementation is beneficial when the organisations have wide range of branches.Various studies has been conducted which tried to state that only companies which has wide range of branches usually go for ERP implementation as it has more benefits in terms of information flow and resource allocation. Research Objective: â€Å"Our objective is to find out that o rganisational factors play a significant role in successful ERP implementation. † The relationship between each factor and the success of the ERP implementation is analysed in this research. The research analyses the data and information taken from various companies. Hypothesis: Null Hypothesis (H0):Organisational factors does not play significant role in successful ERP implementation. Alternate Hypothesis (Ha): Organisational factors play significant role in successful ERP implementation. Methodology: The methodology which we used in finding the survey data is from Primary and Secondary source both. We first examine the existing literature on critical success factors of ERP implementation (Secondary Data) and then assess the company perception on the criticality of these factors (Primary Data). The questionnaires were distributed to selected managers and employees of companies adopting ERP systems.We also gathered some data by taking interview of the Top management of some pr estigious company. This approach helps us in finding out various factors from practical scenario which really helps in the success of the ERP implementation. Few companies from where we gather the data are:– TCS, Ford, LnT, Renault, Daimler, Microsoft, Motherson Sumi Systems, John deer, Tyco, NCR Co. India Pvt. Ltd. , Yamaha motors Pvt. Ltd. , Infosys, and some experienced and knowledgably faculties of prestigious B-Schools e. g. IMT Hyderabad. Later we find the criticality of every factor by: Factor Analysis and Regression.We took 100 samples but only 54 relevant responses were found out. Number of sample questions in each survey are 16, some questions are objective type which can be answered on the likert scale and some are descriptive type because we are interviewing or gathering the data from the top management and employees of the company about the major factors and their importance. Therefore, we presented the mixed types of questions. While doing the project we come ac ross few limitations of the research: Firstly, the ERP implementation success dimensions were measured using subjective and perceptual measures.This was due to the difficulty in securing the related factual data from the participating organizations. Secondly, there can be some biasness in giving the data, as the companies who are currently in use of ERP and spend so much will give the biased information. The questionnaire is attached in annexure with all the responses from the industry i. e. primary source. Results: Linear  Regression  Results| The  REG  Procedure Model:  Linear_Regression_Model Dependent  Variable:  Success  in  implementation(Benefi  Success  in  implementation(Benefit  perception+Increase  in  satisfaction  level)| | Number of Observations Read| 52|Number of Observations Used| 52| | Analysis of Variance| Source| DF| Sum of Squares| Mean Square| F Value| Pr  ;gt;  F| Model| 8| 44. 19446| 5. 52431| 6. 46| ;lt;. 0001| Corrected To tal| 51| 80. 98077|   |   |   | Error| 43| 36. 78631| 0. 85550|   |   | | Root MSE| 0. 92493| R-Square| 0. 5457| Dependent Mean| 5. 51923| Adj R-Sq| 0. 4612| CoeffVar| 16. 75831|   |   | | - - - Note:  Model  is  not  full  rank. Least-squares  solutions  for  the  parameters  are  not  unique.Some  statistics  will  be  misleading. A  reported  DF  of  0  or  B  means  that  the  estimate  is  biased. | - Note:  The  following  parameters  have  been  set  to  0,  since  the  variables  are  a  linear  combination  of  other  variables  as  shown. | Top Management Influence =| 4 * Intercept| | | | Parameter Estimates| Variable| Label| DF| Parameter Estimate| Standard Error| t  Value| Pr  gt;  |t|| Intercept| Intercept| B| 3. 28844| 1. 89106| 1. 74| 0. 0892| Standardization of Single Packag| Standardization of Single Package| 1| 0. 10219| 0. 08832| 1. 16| 0. 537| Top M anagement Influence|   | 0| 0| . | . | . | Connectivity across different co| Connectivity across different companies| 1| 0. 19473| 0. 08456| 2. 30| 0. 0262| Organizational Size|   | 1| -0. 23147| 0. 19982| -1. 16| 0. 2531| Range of branches|   | 1| 0. 29018| 0. 11756| 2. 47| 0. 0176| Less degree of employee resistan| Less degree of employee resistance| 1| -0. 22751| 0. 17244| -1. 32| 0. 1940| Coperation and Cordination|   | 1| 0. 65358| 0. 24454| 2. 67| 0. 0106| Role of Business mission and vis| Role of Business mission and vision| 1| -0. 38776| 0. 23768| -1. 63| 0. 101| Training and Development|   | 1| 0. 35042| 0. 19639| 1. 78| 0. 0814| | Correlation of Estimates| Variable| Label| Intercept| Standardization of Single Packag| Connectivity across different co| Organizational Size| Range of branches| Less degree of employee resistan| Coperation and Cordination| Role of Business mission and vis| Training and Development| Intercept| Intercept| 1. 0000| -0. 2150| -0. 3886| -0. 7468| 0. 2264| -0. 4380| -0. 4969| -0. 5696| -0. 4536| Standardization of Single Packag| Standardization of Single Package| -0. 2150| 1. 0000| 0. 2258| 0. 1309| 0. 0552| 0. 0616| -0. 1327| 0. 2571| -0. 917| Connectivity across different co| Connectivity across different companies| -0. 3886| 0. 2258| 1. 0000| 0. 2307| 0. 1232| 0. 4621| -0. 0188| -0. 0187| 0. 3353| Organizational Size|   | -0. 7468| 0. 1309| 0. 2307| 1. 0000| -0. 1477| 0. 0832| 0. 3870| 0. 1966| 0. 2829| Range of branches|   | 0. 2264| 0. 0552| 0. 1232| -0. 1477| 1. 0000| -0. 1528| -0. 1183| -0. 4683| -0. 2168| Less degree of employee resistan| Less degree of employee resistance| -0. 4380| 0. 0616| 0. 4621| 0. 0832| -0. 1528| 1. 0000| -0. 0598| 0. 3169| 0. 3236| Coperation and Cordination|   | -0. 4969| -0. 1327| -0. 0188| 0. 3870| -0. 183| -0. 0598| 1. 0000| 0. 0296| -0. 1252| Role of Business mission and vis| Role of Business mission and vision| -0. 5696| 0. 2571| -0. 0187| 0. 1966| -0. 4683| 0. 3169| 0. 0296 | 1. 0000| 0. 0922| Training and Development|   | -0. 4536| -0. 1917| 0. 3353| 0. 2829| -0. 2168| 0. 3236| -0. 1252| 0. 0922| 1. 0000| | | Factor  Analysis  Results| The  FACTOR  Procedure| | Input Data Type| Raw Data| Number of Records Read| 52| Number of Records Used| 52| N for Significance Tests| 52| | | Generated  by  the  SAS  System  (Local,  W32_VSHOME)  on  February  24,  2013  at  7:27:27  PM| | | Factor  Analysis  Results| The  FACTOR  ProcedureInitial  Factor  Method:  Principal  Components Prior  Communality  Estimates:  ONE  Ã‚  Ã‚  Ã‚  | | Eigenvalues of the Correlation Matrix: Total = 8 Average = 0. 88888889| | Eigenvalue| Difference| Proportion| Cumulative| 1| 2. 11694553| 0. 24953625| 0. 2646| 0. 2646| 2| 1. 86740928| 0. 50755333| 0. 2334| 0. 4980| 3| 1. 35985595| 0. 49497679| 0. 1700| 0. 6680| 4| 0. 86487917| 0. 32219842| 0. 1081| 0. 7761| 5| 0. 54268075| 0. 02774770| 0. 0678| 0. 8440| 6| 0. 51493305| 0. 0 7920770| 0. 0644| 0. 9083| 7| 0. 43572535| 0. 13815443| 0. 0545| 0. 9628| 8| 0. 29757092| 0. 29757092| 0. 0372| 1. 0000| 9| 0. 00000000|   | 0. 0000| 1. 0000| 3  factors  will  be  retained  by  the  MINEIGEN  criterion| Factor  Pattern| |   | Factor1| Factor2| Factor3| Standardization of Single Packag| Standardization of Single Package| 0. 69014| -0. 26162| -0. 23207| Top Management Influence|   | 0. 00000| 0. 00000| 0. 00000| Connectivity across different co| Connectivity across different companies| -0. 49203| 0. 54147| -0. 48463| Organizational Size|   | -0. 55073| -0. 48025| 0. 33725| Range of branches|   | 0. 20013| 0. 34213| 0. 80756| Less degree of employee resistan| Less degree of employee resistance| 0. 17237| -0. 68893| 0. 30760| Coperation and Cordination|   | 0. 7166| 0. 28393| -0. 13602| Role of Business mission and vis| Role of Business mission and vision| -0. 17059| 0. 74207| 0. 43129| Training and Development|   | 0. 73842| 0. 22839| 0 . 07819| | Variance Explained by Each Factor| Factor1| Factor2| Factor3| 2. 1169455| 1. 8674093| 1. 3598560| | Final Communality Estimates: Total = 5. 344211| Standardization of Single Packag| Top Management Influence| Connectivity across different co| Organizational Size| Range of branches| Less degree of employee resistan| Coperation and Cordination| Role of Business mission and vis| Training and Development| 0. 59859241| 0. 0000000| 0. 77015031| 0. 64768308| 0. 80925749| 0. 59896039| 0. 55025088| 0. 76578116| 0. 60353504| | | Generated  by  the  SAS  System  (Local,  W32_VSHOME)  on  February  24,  2013  at  7:27:27  PM| | | | | | | Findings: * The Regression equation is as follows: Success in Implementation = 3. 28844 + 0. 10219 * (Standardization of single package) + 0. 19473 * (Connectivity across different companies) 0. 23147 * (Organizational Size) + 0. 29018 * (Range of Branches) 0. 22751 * (less degree of employee resistance) + 0. 65358 * (Coope ration and Coordination) 0. 38776 * (Role of Business vision and Mission) 0. 35042 * (Training and Development) * R Square Value = 0. 5457 * Significance: 1. Corporation and Coordination, range of branches and connectivity across different companies has t-value ;gt; 2. 2. Standardization of single package and Training ;amp; Development have positive t-values but less than 2. 3. Organizational Size, Less Degree of Employee Resistance and Role of Business Mission and Vision have negative t-value. * In Factor Analysis, the organisational factors as 9 independent variables can be grouped into 3 factors: * Factor1 (Infrastructural and Structural factor)Standardization of single Package Organisational Size Cooperation and Coordination Training and Development * Factor2 (Organizational cultural factor) Connectivity across different companies Less degree of Employee resistance Role of Business Vision and Mission * Factor3 (Size factor) Range of Branches Discussion: Following is the interpr etation from the regression results: * The Organizational factors that have t-value greater than 2 will have significant positive impact on the successful implementation of ERP. These factors are: 1. Connectivity across different companiesFor the Organization to implement ERP successfully it should develop and maintain proper and high connectivity across different companies. 2. Range of Branches The organization which has large range of branches is more likely to be successful in ERP implementation. 3. Co-operation and Co-ordination There must be good cooperation and coordination among the employees working in the organisation as it is very crucial factor for the success of ERP * The Organizational factors that has positive t-value less than 2 will have positive impact on the successful implementation of ERP but not very significant. These factors are: . Standardization of single package All the different functional areas of company like HR, Finance, Marketing, and Sales and distrib ution should be standardize on single ERP package for successful implementation. 2. Training and Development The employees of the company should be given proper training on ERP modules for it to be successful in future. * The Organizational factors that have negative t-value will have negative impact on the successful implementation of ERP. These factors are: 1. Organisational Size If the organization size is small the ERP can be implemented quickly as compared to large. 2.Less Degree of Employee Resistance From our results, we found that the Less Degree of Employee Resistance factor will not contribute more for the successful ERP implementation. 3. Business Vision and Mission From our results, we found that the Business Vision and Mission factor will not contribute more for the successful ERP implementation. * Top Management influence is present everywhere the ERP was implemented. This shows that it is the most critical factor for the successful implementation of ERP. The R square value â€Å"0. 5457† shows that these independent variables are covering about 54% of variation in the output i. . , successful implementation of ERP. When we run the factor analysis we were able to group these 9 independent variables into three factors and these factors contributed about 66% of deviation. 1. The first factor which is the most important factor is having the independent variables as follows: * Standardization of single Package * Organisational Size * Cooperation and Coordination * Training and Development These independent variables show the common element of infrastructure and working structure of the organization. So, the first factor is named as Infrastructural and Structural factor. . The second factor which is the next crucial factor is having the independent variables as follows: * Connectivity across different companies * Less degree of Employee resistance * Role of Business Vision and Mission These independent variables show the common element of organ izational culture. So, the second factor is named as Organizational cultural factor. 3. The third factor is the next crucial factor having only one independent variable as: * Range of Branches This independent variable has the element as size of the organization. So, this factor is named as Size factor.From the correlation matrix we found high correlation among the independent variables that are in the same factor group which confirms our parity of results. Conclusion : The companies which have high connectivity across different companies, high range of branches, high cooperation and coordination among employees, and good training facilities are most likely to effect the successful ERP implementation. From our findings we found that the top management influence was an important and critical factor for success of ERP in companies. Recommendations:For the company to successfully implement ERP it should invest heavily in Training ;amp; Development facilities. It should encourage high c ooperation and coordination among employees. Because the organization cannot concentrate on 9 organizational factors and work upon that. So, we divided the 9 organizational factors into 3 factor groups and the company can choose one of the factor groups that can be Infrastructural and Structural factor. Simultaneously, it can work on the independent variables that are present in this factor to enhance the probability of success of ERP implementation.Sources : sciencedirect. com/science/article/pii/S0378720601001343ttp://fico-forum. com/? p=147 https://dspace. lboro. ac. uk/dspace-jspui/handle/2134/8091 researchersworld. com/vol2/issue2/Paper_07. pdf