Score
88. What are the estimated costs of proposed changes?
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89. Should you focus on self-service or sales-supported SaaS?
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90. How frequently do you verify your Self-service strategy?
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91. How do you leverage Data Discovery for self-service analytics?
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92. What are predictive Self-service analytics?
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93. Has automation and self-service allowed for cost savings?
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94. What does losing customers cost your organization?
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95. What disadvantage does this cause for the user?
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96. What is self-service analytics and why is it important?
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97. What users will be impacted?
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Add up total points for this section: _____ = Total points for this section
Divided by: ______ (number of statements answered) = ______ Average score for this section
Transfer your score to the Self-service Index at the beginning of the Self-Assessment.
CRITERION #4: ANALYZE:
INTENT: Analyze causes, assumptions and hypotheses.
In my belief, the answer to this question is clearly defined:
5 Strongly Agree
4 Agree
3 Neutral
2 Disagree
1 Strongly Disagree
1. What are the sources of data from self-service interactions?
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2. What are the best opportunities for value improvement?
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3. Do you drive employee experience and engagement through self-service?
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4. Do you, as a leader, bounce back quickly from setbacks?
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5. Are Self-service changes recognized early enough to be approved through the regular process?
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6. How will you manage IT and self-service data integration?
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7. Were Pareto charts (or similar) used to portray the ‘heavy hitters’ (or key sources of variation)?
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8. Do you have difficulty supporting self-service access to complex data sources?
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9. What are the Self-service design outputs?
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10. Is the process self-service or managed?
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11. What quality tools were used to get through the analyze phase?
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12. What are your key Self-service indicators that you will measure, analyze and track?
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13. Will your solution be self-serviced locally or provisioned in the data center?
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14. What is the cost of poor quality as supported by the team’s analysis?
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15. What are evaluation criteria for the output?
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16. What conclusions were drawn from the team’s data collection and analysis? How did the team reach these conclusions?
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17. Have changes been properly/adequately analyzed for effect?
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18. Are users in your organization currently integrating or blending data from sources using a software solutions self-service data preparation capabilities?
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19. What process improvements will be needed?
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20. Is there any way to speed up the process?
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21. What were the crucial ‘moments of truth’ on the process map?
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22. Was a cause-and-effect diagram used to explore the different types of causes (or sources of variation)?
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23. What are your current levels and trends in key Self-service measures or indicators of product and process performance that are important to and directly serve your customers?
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24. Is data and process analysis, root cause analysis and quantifying the gap/opportunity in place?
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25. How was the detailed process map generated, verified, and validated?
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26. Were any designed experiments used to generate additional insight into the data analysis?
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27. Does your self-service product track data point in time?
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28. How are outputs preserved and protected?
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