Business Analysis Techniques

SWOT is the business analysis technique used most commonly by companies and other organisations. SWOT stand for Strengths, Weaknesses, Opportunities and Threats. It is usually set out in quadrants on a single sheet of paper as illustrated in Figure C4. The contents of the SWOT analysis are usually generated by a brainstorming technique (see Section C, 1.8.3). 

Whilst the SWOT technique is most commonly used for business analysis, where potential competitive advantage can be identified from the fit between the company s strengths and upcoming opportunities, it can also be used in creative idea generation. Looking at the Opportunities and Threats in a more divergent rather than an analytical mindset is likely to produce some ideas, which can be exploited in an innovative manner. 

Today it is becoming increasingly clear that this business-as-usual second reaction was as misguided as the panicky initial response had been. For gradually but surely, the gas chromatograph—which soon expanded its scope of effectiveness by the successive introduction of capillary columns, the mass spectrometer, and quantitative head-space analysis techniques—has profoundly changed the perfumer s daily work. 

Toward the end of the Second World War, systems techniques such as fault tree analysis were introduced in order to predict the reliability and performance of military airplanes and missiles. The use of such techniques led to the formalization of the concept of probabilistic risk assessment (PRA). The publication of the Reactor Safety Study (NRC, 1975)—often referred to as the Rasmussen Report after the name of principal author, or by its subtitle WASH 1400—demonstrated the use of such techniques in the fledgling nuclear power business. Although WASH 1400 has since been supplanted by more advanced analysis techniques, the report was groundbreaking in its approach to system safety. 

One of the key internal issues of enterprise systems is the development of ERP techniques that allow the efficient collection and presentation of information that is specific to the user. These data-mining or business intelligence techniques have been actively pursued, and several products are available on the marker such as Microsoft s Data Analysis and Cognos Finance 5. These tools are still rather primitive and this should continue to be one of the most important research areas for next-generation ERP systems. 

Business planning, budgeting, finance, and economic analysis techniques Change management How to effect change... 

Mention has already been made of the continuous improvement processes that are being applied across the industry. These include Quality Assurance progranunes. Training Needs Analysis, Business Excellence techniques and, where appropriate. Business Process Re-engineering. 

In judging the adequacy of provisions you will need to apply the relevant standards, legislation, codes of practice, and other agreed measures for the type of operation, application, and business. These activities are quality assurance activities and may be subdivided into design assurance, procurement assurance, manufacturing assurance, etc. Auditing, planning, analysis, inspection, and test are some of the techniques that may be used. 

Guide to Data Analysis and Quality Control Using CUSUM Techniques. Uses and Value of CUSUM Charts in Business, Industry, Commerce and Public Service , BS 5703-1 2003, British Standards Institute (BSI), London, UK, 2003. 

One approach is to mesh all investigation and root cause analysis activities under one management system for investigation. Such a system must address all four business drivers (1) process and personnel safety, (2) environmental responsibility, (3) quality, and (4) profitability. This approach works well since techniques used for data collection, causal factor analysis, and root cause analysis can be the same regardless of the type of incident. Many companies realize that root causes of a quality or reliability incident may become the root cause of a safety or process safety incident in the future and vice versa. 

In financial matters, a similar technique, ratio analysis, is used to judge whether a company is healthy witli respect to industry standards. In ratio analysis most of die quantities compared are quantities of money, so the ratio of one quantity of money to another quantity of money is, by definition, a new dimensionless ratio (like die Reynolds number or lift coefficient), and these financial ratios can be used to compare businesses in similar industries or businesses (in engineering, such comparison is referred to as dynamic similitude). 

There is, at least in some quarters I think, an over-reliance on the significance of making the numbers which is led by practices developed in the USA. This is particularly the case when the basis for an idea is weak yet there is a kind of clarity of thought brought about by reducing the analysis to mere numbers. Statistical techniques and calculation methods will be discussed later but for the business development function numbers have the power to penetrate raw data and to persuade (or dissuade) if used judiciously. While pernickety exactitude can be a major drawback, a good feel for the numbers is an essential part of the business development skill set. 

The emphasis is on simulation at the atomistic and electronic structural level. Computational techniques in general, and simulation in particular, however, play an important role throughout the whole research, development, and production process [5] (Figure 2). Successful translation of an early research result into a product or process with practical business impact requires that a series of hurdles at scale up, economic analysis, process, and engineering levels all be successfully passed. 

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