Traditional Data Analysis Tools Vs Modern Data Analysis Tools
Some people have a notion that data analysis tools can easily make up for the lack of experienced managers. The theory behind this conception is that analysis tools can solve problems that new managers can’t. Normally speaking, data analysis tools do present a plethora of information regarding any aspect of business operations. Unfortunately these tools cannot do the work by themselves, they can only generate the data. The data generated by such tools can only be analyzed by a skilled and experienced manager who has a good understanding of all the variables. Traditional followers believe that data analysis tools are helpful to managers as it helps them keep track of routine jobs and follow applications such as accounting and finance. Although traditional wisdom underestimates the functionality of analysis tools in reality they can be configured to evaluate a wide range of variables with varying complexities, ranging from the standard size of a ball bearing to the number of engineering changes in an engine design (Collier & Evans, 2008). Individual measurements may be small but collectively they represent a much bigger picture which can help bringing in operational breakthroughs. Clearly, some of these developments may be of great importance to the accounting division. The operations department should also be interested in these developments, as financial prudence is a important venture for every employee. One of the biggest disadvantages of any data analysis tool is that they malfunction when burdened with inaccurate facts. With the passage of time the problem with data analysis tools have worsened has sizes of data sets have grown larger so inaccurate information means bigger errors, as pointed out by John Hermansen (2004). Although all measurements are generally collected in an automated way but there still remains a possibility of error because at some level measurement collectors may make some errors. If the numbers behind the analysis is in error, then the whole investigation may be called into question. Nowadays there are different software available which can help in validating data. Just as quality control is a part of every production process similarly quality control of data collection should also be applied. For those who are still drawing their salary, remember that data analysis tools will never be able to replace experienced managers. Data analysis tools will only provide data but in order to convert those output and align them with corporate objectives to bring out growth the expertise of veteran managers is a must. It is managers who take the final decision, the data helps them to arrive at that decision. Though data analysis tools can mechanize to a great extent of the everyday decision-making in reply to performance metrics, the final authority on taking business tough verdict will at all times dwell with managers.
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