Читать книгу Data Philanthropy A Complete Guide - 2020 Edition - Gerardus Blokdyk - Страница 9
ОглавлениеCRITERION #3: MEASURE:
INTENT: Gather the correct data. Measure the current performance and evolution of the situation.
In my belief, the answer to this question is clearly defined:
5 Strongly Agree
4 Agree
3 Neutral
2 Disagree
1 Strongly Disagree
1. Among the Data philanthropy product and service cost to be estimated, which is considered hardest to estimate?
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2. How will measures be used to manage and adapt?
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3. Are there any easy-to-implement alternatives to Data philanthropy? Sometimes other solutions are available that do not require the cost implications of a full-blown project?
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4. What happens if cost savings do not materialize?
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5. Do you have an issue in getting priority?
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6. Why do you expend time and effort to implement measurement, for whom?
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7. Are the Data philanthropy benefits worth its costs?
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8. How will success or failure be measured?
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9. Are there measurements based on task performance?
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10. What tests verify requirements?
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11. What are the Data philanthropy investment costs?
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12. How much does it cost?
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13. What are hidden Data philanthropy quality costs?
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14. Are you aware of what could cause a problem?
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15. Which measures and indicators matter?
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16. How can a Data philanthropy test verify your ideas or assumptions?
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17. Are you able to realize any cost savings?
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18. Is the cost worth the Data philanthropy effort ?
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19. How do you stay flexible and focused to recognize larger Data philanthropy results?
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20. How do you aggregate measures across priorities?
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21. Who pays the cost?
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22. What details are required of the Data philanthropy cost structure?
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23. Do you verify that corrective actions were taken?
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24. What causes mismanagement?
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25. Who is involved in verifying compliance?
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26. Are indirect costs charged to the Data philanthropy program?
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27. What do people want to verify?
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28. What measurements are possible, practicable and meaningful?
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29. What are the types and number of measures to use?
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30. Does the Data philanthropy task fit the client’s priorities?
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31. How will you measure success?
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32. How frequently do you track Data philanthropy measures?
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33. What do you measure and why?
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34. How do you measure variability?
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35. How can you reduce the costs of obtaining inputs?
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36. Are actual costs in line with budgeted costs?
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37. How will effects be measured?
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38. What are allowable costs?
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39. How do you prevent mis-estimating cost?
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40. What are your key Data philanthropy organizational performance measures, including key short and longer-term financial measures?
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41. What is the cost of rework?
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42. What are your customers expectations and measures?
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43. How will you measure your Data philanthropy effectiveness?
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44. Does a Data philanthropy quantification method exist?
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45. Will Data philanthropy have an impact on current business continuity, disaster recovery processes and/or infrastructure?
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46. What does your operating model cost?
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47. How can you measure Data philanthropy in a systematic way?
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48. What disadvantage does this cause for the user?
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49. What does a Test Case verify?
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50. How will your organization measure success?
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51. Is there an opportunity to verify requirements?
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52. Are the measurements objective?
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53. How are costs allocated?
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54. What are the costs of delaying Data philanthropy action?
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55. How do you verify and develop ideas and innovations?
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56. What potential environmental factors impact the Data philanthropy effort?
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57. What does losing customers cost your organization?
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58. How frequently do you verify your Data philanthropy strategy?
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59. How sensitive must the Data philanthropy strategy be to cost?
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60. What could cause delays in the schedule?
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61. How is the value delivered by Data philanthropy being measured?
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62. What causes extra work or rework?
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63. Do the benefits outweigh the costs?
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64. How are measurements made?
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65. What are the operational costs after Data philanthropy deployment?
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66. What causes investor action?
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67. What evidence is there and what is measured?
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68. Are supply costs steady or fluctuating?
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69. What are the Data philanthropy key cost drivers?
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70. Are Data philanthropy vulnerabilities categorized and prioritized?
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71. The approach of traditional Data philanthropy works for detail complexity but is focused on a systematic approach rather than an understanding of the nature of systems themselves, what approach will permit your organization to deal with the kind of unpredictable emergent behaviors that dynamic complexity can introduce?
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72. What could cause you to change course?
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73. What is measured? Why?
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74. What harm might be caused?
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75. At what cost?
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76. How is progress measured?
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77. Where is it measured?
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78. How are you verifying it?
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79. How will costs be allocated?
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80. How can you reduce costs?
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81. What are your primary costs, revenues, assets?
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82. How will the Data philanthropy data be analyzed?
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83. How do your measurements capture actionable Data philanthropy information for use in exceeding your customers expectations and securing your customers engagement?
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84. When a disaster occurs, who gets priority?
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85. What is your decision requirements diagram?
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86. What does verifying compliance entail?
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87. What drives O&M cost?
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88. Do you effectively measure and reward individual and team performance?
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89. What are the costs and benefits?
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90. What are the current costs of the Data philanthropy process?
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91. What are the estimated costs of proposed changes?
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92. How long to keep data and how to manage retention costs?
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93. What can be used to verify compliance?
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94. Why do the measurements/indicators matter?
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95. Which Data philanthropy impacts are significant?
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96. What are you verifying?
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97. What is your Data philanthropy quality cost segregation study?
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98. Have design-to-cost goals been established?
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99. What is the total fixed cost?
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100. How do you verify performance?
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101. What is an unallowable cost?
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102. Are you taking your company in the direction of better and revenue or cheaper and cost?
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103. Is the solution cost-effective?
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104. Do you have any cost Data philanthropy limitation requirements?
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105. What are the costs?
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106. How do you measure efficient delivery of Data philanthropy services?
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107. When are costs are incurred?
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108. How do you verify if Data philanthropy is built right?
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109. What relevant entities could be measured?
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110. How is performance measured?
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111. How do you verify your resources?
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112. What measurements are being captured?
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113. How do you verify Data philanthropy completeness and accuracy?
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114. How do you quantify and qualify impacts?
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115. How do you focus on what is right -not who is right?
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116. How can you measure the performance?
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117. Do you have a flow diagram of what happens?
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118. What is the root cause(s) of the problem?
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119. How do you control the overall costs of your work processes?
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120. How to cause the change?
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121. What methods are feasible and acceptable to estimate the impact of reforms?
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122. What is the total cost related to deploying Data philanthropy, including any consulting or professional services?
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123. Who should receive measurement reports?
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124. Are the units of measure consistent?
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125. Is a follow-up focused external Data philanthropy review required?
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126. Did you tackle the cause or the symptom?
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127. Have you included everything in your Data philanthropy cost models?
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128. What are the strategic priorities for this year?
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129. What would it cost to replace your technology?
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130. Where can you go to verify the info?
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131. What users will be impacted?
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132. Are missed Data philanthropy opportunities costing your organization money?
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133. How can you manage cost down?
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134. Are there competing Data philanthropy priorities?
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135. What are predictive Data philanthropy analytics?
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136. Where is the cost?
