Geng Wang Case ABCs of Spend Analysis
Why are data analysis skills and thinking so important to spend analysis? Can’t software applications be used to generate the information needed automatically? Data analysis skill is important to decision making. We cannot understand why the company isn’t doing well but keeps very high productivity without data – perhaps the total cost for operating the robots are too high, perhaps the number of workers is too big, perhaps the demand for the products are too limited these days. We need the data to find out the reason. For example, we can compare the historical data of amount of workers to get the conclusion that numbers are so big now. We may dig out the fact that the expense of operating robots is too high in the proportion of the total cost. We need various skills to analysis the data from various aspects.For example, we may ignore the fact that even the expense of operating robots is high, but robots has helped the company avoid millions of dollars fine of polluting the environment. So analysis skills are important, we have to think from all aspects. Software can generate routine data analysis from time to time, but we cannot get intelligent analysis when we face something new. Even the goal of the company is to simply make money – which might means “ROI, cash flow, net profit”(from the book “the goal”), we may still find numerous ways to improve every part by different data analysis. For example, on the book’s example, the advertising category has the highest number of suppliers, followed by small-dollar suppliers, energy, security, general contracting. At first blush, the figure for advertising seems high to Susan. However, business units will often use local suppliers, such as radio and newspapers, to provide advertising services. Software cannot think like this, but people can. How might a structured process such as Six Sigma methodology be useful here? Companies can often gain a...
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