Critical Failure Factor (CFF) Models

An alternative to examining critical success factors is to devise critical failure models, examples of which are discussed in this section. The rationale for this approach, according to Momoh et al. (2010), is that it provides organisations with the reality of the problems that do occur and the potential consequences regarding human and financial resources.

In identifying CSFs, the authors propose that these focus on the actions an organisation is advised to carry out to avoid failure and that CFFs incite a more urgent focus, since they provide direct description of the failure that ensues if all the CSFs are not appropriately implemented. Nine critical failure factors (table 2.3) were identified by means of an in-depth review of published research from 1999 to 2007, conducted by Momoh et al. (2010) and a description of each one from a live perspective.

The factors were identified in large organisations and SMEs;109 studies in all, with 18 conducted in developing countries, 36 in USA and 13 in UK.

The studies were conducted across multiple industries, so that Momoh states that failure factors should be a considerable concern to all organisation types, and that the reliability and validity of the study is very high owing to the multiple approach; manufacturing was identified as the highest implementer of ERP. The authors are critical of some of the studies owing to the lack of depth apparent in the research; they also state that more in-depth study is required on each factor as well as the methodology to resolve it.

The ERP implementation in a large Chinese manufacturing group of 14 companies was the subject of a study on CFFs by Pan et al. (2011); 37 failure risk factors were identified. The study focused specifically on post ERP implementation, rather on any risk factors that would cause ERP implementation failure. The risks were rated and seven suggested as most serious of the CFFs, all of which were related to the organisational or people characteristics, rather than the technology (table 2.4). An ‘exhaustive’ literature review was conducted that identified 40 potential risks and formed the basis of two questionnaire surveys, to gather the different perspectives of ICT users and experts, to provide an operational view, and business managers, to capture the managerial and strategic opinion.

The findings of this study may not all be generalisable to western developed organisations, for instance the loss of knowledge is likely to be more critical in the eastern nations owing to their lack of knowledge management systems, exacerbated by the cultural aspect of not sharing knowledge, and it being at highest levels in senior managers, which infers that when such individuals leave an organisation there is a significant drop in organisational knowledge; this factor aligns with findings by Zhang (2003).

The findings of this research tend to complement rather than duplicate Momoh et al. (2010); there is less attention to the technical and financial issues, although technical aspects of the seven CFFs align such ERP system failing to generate suitable materials and generation of MPS, as a consequence of data quality.

Table 2.3: Critical Failure Factors Adapted from data: Momoh et al. (2010) No Critical Failure Factor No of

Studies

Description of Failure (examples)

1 Excessive customisation 13 Increases implementation from months to years, confuses users, software and user specifications change, high cost implications, restructure organisation’s business processes to fit software.

2 Dilemma of internal integration

8 Inflexibility in software forces of firms to change business processes to fit software if end to end process design is not utilised. Many failures.

3 Poor understanding of business implications and requirements,

7 Organisation not organized in a manner that enables all benefits to be experienced, organisation not ready for integration, departments with own agendas, conflicting objectives

4 Lack of change management

12 Failure to recognise the impact that the change would have on entire organisation, lack of communication with employees, cultural lack of readiness, inadequate user training so do not know how to use and maintain, unplanned cost

Poor data quality 9 Inaccurate, incomplete data and lack of timely data provision has substantial business and social consequences, data misfits when organisational requirements and ERP package do not align

Misalignment of IT with business

3 Changes in environment not taken into account, since rare for technology and business needs to match, approach is not dynamic to accommodate

Hidden costs 3 Underestimate hidden costs particularly those for training and data conversion, as well as consulting cost and the perception of project end date

Limited training 4 Managers and users cannot use functionality, do not understand the objectives of the ERP implementation

Lack of top management support

5 Complex organisational issues not addressed, technology regarded as the solution, managers cannot adapt to change,

Table 2.4: Critical Post ERP Implementation Factors (Pan et al. ,2011) No Critical Risk Factor Relative Score 1 Lose critical IT or ERP expert 164.4

2 MPS generated by the ERP system is inappropriate 132.3 3 Operational staff unwilling to use the ERP system 129.5 4 Loss of accumulated organisational ERP knowledge over time 127.8 5 Not enough technical support from ERP vendors 127.3 6 ERP system fails to generate the appropriate material 127.2 7 Seamless Integration between ERP modules not accomplished 123.8

A study of CFF by Hawari and Heeks (2009) and conducted in Jordan, found that failure to close specific gaps represented a significant CFF; its methodology was based on comparing the specific factors in the organisation before and after ERP system implementation. The assumptions and requirements that comprised the original system design, as compared with the organisational reality, were not addressed during implementation and caused failure. The seven gaps identified between the assumptions made and the existing organisational features

before implementation, were categorised according to how likely they were to cause failure; four were found to be very likely, those of objectives and values, staffing and skills, technology and process, in decreasing order of importance. Information and management systems and structures gaps were less likely to cause failure and other resources rated as possibly influencing failure. An example of a gap description is that of technology, in which the infrastructure that existed was far more basic that was assumed. Post implementation, the gaps in each factor had changed little, some not at all, particularly the highly rated failure factor of objectives and values, with staffing a skills reducing marginally.

The CFF model that results is the design-reality gap model, which the researchers suggest to mitigate failure risk and to focus attention on the interventions to move away from failure, by highlighting the gaps and then designing actions to minimise them. The authors apprise the issue that, as a developing county, these factors may be exacerbated by the culture, again making reference to Hofstede et al. (2010), and demonstrating similarity to Chinese studies, such as Pang et al (2011) and Zhang (2003). For instance, the authors discuss uncertainty avoidance manifested in resistance/fear of changes in job design, and suggest that closing gaps relating to a specific related failure factor may be more of a challenge than anticipated. It would appear therefore that issues that seem to be specifically related to developing countries may be generalisable over those eastern countries, in a similar manner that ‘best practice’ appears so in developed countries.