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CAISA Forum Question 878 A telecom company uses AI to improve its customer support operations. The AI analyzes customer complaints, service usage, escalation patterns, retention data, and support costs. It discovers that: 90% of customers receive satisfactory service and rarely complain. The remaining 10% of customers generate nearly 65% of complaints, escalations, and support costs. To address this, the AI proposes a major change: Allocate more support resources to the dissatisfied 10%. Prov
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CAISA Forum Question 877 If AI identifies spare capacity as waste, should it eliminate it? A large logistics company uses AI to optimize its delivery operations. The AI analyzes vehicle utilization, staffing levels, warehouse capacity, and route efficiency. It discovers that: Delivery vehicles are only utilized at 82% capacity on average. Certain warehouses appear underutilized. Extra staffing is maintained for demand spikes that occur only a few times each year. The AI recommends removing t
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Showing content with the highest reputation on 05/01/2019 in Posts
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The data set follows a normal distribution and therefore can be characterized by the sample mean and standard distribution (S) with an associated confidence interval. The process outcomes will follow this characterized distribution. For example, future data sets of comparable quantity will have a mean in the range of the confidence interval.1 point
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An airline has the normally distributed data of the price of jet fuel/barrel for each year of the past 20 years. The airline can use this data to anticipate how much jet fuel will cost for a specific time of year and adjust their ticket prices accordingly. They can also use this data to change their purchasing strategy on jet fuel futures as to beat the market.1 point
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Assuming a standard normal distribution , you can use probability distributions to make predictions for outcomes of business processes by: calculating the area under the curve that does not meet the business limits - defining how far away from the limit the process is (Z value). With known X=0, sd=1, and a limit calculating the probability of the process not achieving or achieving the desired limits (DPMO) With known mean, sd, and limit with known Z value (item 1) can convert to DPMO with known DPMO (item 2) can convert to Z-value Using the information to establish the business case and support the charter of a DMAIC to ensure we exceed the business goals.1 point
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