For more than a decade, ERP projects have represented some of the largest investment initiatives in manufacturing companies globally; yet, many ERP investments do not achieve the expected business results, and on occasion, fail completely. In some cases, C-level executives have even been fired due to the poor results achieved by an ERP implementation. This article describes how executives can reduce their exposure to economic risk, and increase the probability of achieving the desired economic outcome and Return-on-Investment (ROI) of any ERP initiative.
Issues in Forecasting ERP Benefits
Today, when either investing in a new ERP system, or upgrading an existing system, most companies prepare a business case to assess the potential benefits and costs of such a project.
A recent Glomark-Governan research study, conducted in February 2008, indicates that 85% of the ERP business cases prepared today do not include an objective risk analysis. In such an analysis, it is imperative that companies not only weigh the economic costs and benefits, but also identify which risk factors may potentially lead to a project's economic failure.
Forecasting annual economic benefits for an ERP implementation can be challenging. While a myriad of benchmarks are readily available, the ERP research studies available today present such a wide range of results that many companies struggle to identify which values are most realistic and attainable. For example, one renowned research organization indicates that inventory levels can be reduced up to 24% with an ERP implementation, while another research firm states that inventory levels could potentially be reduced as much as 75%.
This discrepancy in potential outcomes can not be ignored when a company's financial health could be in question. To understand why these variances in benchmarking data exist, executives must understand that ERP applications require change management (changes in business processes, resultant training required to facilitate those changes, etc.), often of great magnitude. Even an expected reduction in employees can, if not implemented correctly, drive the expected operational and economic benefits down a path to economic disaster.
"In effectively implementing an ERP system, it is imperative that a company trains its systems users, and understands the process changes necessary to achieve their desired business results," says Olivier Dubious, Systems Director for ICR ChemS, a European manufacturing company. "A lack of training and thorough understanding of the business process changes needed, would lead the ERP implementation process down a path to failure," says Dubious.
Another issue that plagues many manufacturing companies is the inability to utilize the full range of functionality available in their chosen ERP system. The Glomark-Governan ERP Research Study identified that, on average, companies use less than 60% of the features available in their ERP systems. If the business case prepared prior to implementation assumes that all or most of the ERP features will be utilized, the economic projections will not be achieved, as the business case did not account for those features and associated benefits not used and realized, respectively.
The ERP Research Study also found that the range of possible improvements achieved with an ERP implementation vary considerably; and the range between worst and best case results in ERP benchmarks is wider than most people realized in the past.
Therefore, careful consideration and detailed assessment must be applied when selecting benchmarks; as they can easily mislead executives with regard to the expected economic outcome of an ERP project.
Relying solely on benchmarks from research studies is clearly not sufficient to make an accurate and objective assessment of the ROI for an ERP project. There are, however, some models that can assist companies in maximizing the probability of an ERP project's success.
Comprehensive Risk Assessment in ERP Initiatives
There are several risk analysis methods available, but only a Monte Carlo simulation can objectively assess the economic risk that a large investment initiative (e.g. an ERP implementation) can potentially pose. A Monte Carlo simulation generates a statistical analysis that considers the sensitivity of assumptions, and identifies the probability of achieving the anticipated benefits and financial performance being forecasted in a business case. A Monte Carlo simulation helps companies make more objective best, most likely, and worst case estimates, that fall between a narrowed, more probable spread. Focusing upon the potential results that fall within a narrower spectrum (e.g. a +-2 Sigma variance) will help a company pinpoint those benefits which require the most attention and monitoring to ensure success.
"A detailed risk analysis on the forecasted benefits of an ERP is critical to achieve positive operational and economic results," says Gustavo Benitez, a consultant with Deloitte and former IT manager at Vitro, a glass manufacturing company.
This type of economic risk analysis helps an enterprise to not only identify the largest economic benefits, but also to identify those benefits that have the highest level of uncertainty, which may negatively impact the company's bottom line. Conducting this analysis prior to an ERP implementation provides more accurate post-implementation expectations, in addition to determining which assumptions and benefits should be tracked with KPIs to ensure the most positive impact on the company's finances.
While most ERP initiatives generate positive operational and financial results for manufacturing companies, not all benefits and benchmarks identified by research firms apply to every scenario.
The Glomark-Governan ERP Research Study, referenced in this article, identified that the range of possible improvements achieved from an ERP implementation or initiative, do in fact vary considerably from industry to industry; and that the discrepancies between available benchmarks is much wider than most people ever realized in the past.
Economic risk analyses are imperative for identifying those assumptions and benefits that truly minimize risk, and therefore increase the accuracy of the expected ROI for any large investment initiative.
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