Artificial Intelligence For IT Operations A Complete Guide - 2020 Edition. Gerardus Blokdyk

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      77. What are the operational costs after Artificial Intelligence for IT Operations deployment?

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      78. When should you bother with diagrams?

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      79. When a disaster occurs, who gets priority?

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      80. How do you measure efficient delivery of Artificial Intelligence for IT Operations services?

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      81. How do you verify your resources?

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      82. Are Artificial Intelligence for IT Operations vulnerabilities categorized and prioritized?

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      83. How long to keep data and how to manage retention costs?

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      84. Is the solution cost-effective?

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      85. Does the Artificial Intelligence for IT Operations task fit the client’s priorities?

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      86. Have you included everything in your Artificial Intelligence for IT Operations cost models?

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      87. Do you effectively measure and reward individual and team performance?

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      88. How are measurements made?

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      89. How do you measure success?

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      90. What are you verifying?

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      91. How do you verify if Artificial Intelligence for IT Operations is built right?

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      92. At what cost?

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      93. What does your operating model cost?

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      94. How can you manage cost down?

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      95. How will effects be measured?

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      96. Have you made assumptions about the shape of the future, particularly its impact on your customers and competitors?

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      97. What is the root cause(s) of the problem?

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      98. What are the costs of reform?

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      99. How do you verify the authenticity of the data and information used?

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      100. What are allowable costs?

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      101. Among the Artificial Intelligence for IT Operations product and service cost to be estimated, which is considered hardest to estimate?

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      102. Do you have an issue in getting priority?

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      103. How do you prevent mis-estimating cost?

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      104. Has a cost center been established?

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      105. What drives O&M cost?

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      106. What tests verify requirements?

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      107. How do you measure variability?

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      108. What measurements are possible, practicable and meaningful?

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      109. What would be a real cause for concern?

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      110. How will success or failure be measured?

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      111. Who should receive measurement reports?

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      112. What is the cost of rework?

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      113. What are the costs?

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      114. What users will be impacted?

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      115. How can a Artificial Intelligence for IT Operations test verify your ideas or assumptions?

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      116. Where is the cost?

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      117. What happens if cost savings do not materialize?

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      118. What is measured? Why?

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