


Benchmark Assessment Framework
Welcome to the world's most comprehensive online benchmarking assessment for enterprise data & analytics teams. The assessment consists of 12 categories and 44 subcategories, listed below.
Three-quarters of the 250 questions are scored, the rest are non-scored. The results of the scored questions are displayed in the online report. To view results from non-scored questions and apply custom filters and cohorts, you need to schedule a private benchmark workshop.
The majority of the scored questions are best practice statements that respondents evaluate using a 6-point Likert based on degree of agreement. Non-scored questions are single choice, multi-choice, or open-ended.
Each industry-based assessment has a set of custom filters and a section of about a dozen non-scored questions geared explicitly to that industry. 95% of the assessment is generic.
Categories and Subcategories
A. Business & Culture
1. Executives
2. Business Users
3. Organization
4. Business Systems
F. Business Intelligence
25. Casual Users
26. Dashboards
27. Business Intelligence Tools
G. Data Analysis
B. Operating Model
5. Data & Analytics Team
6. Enterprise Alignment
7. Community
8. Training
9. Support
C. Development
10. Project Management
11. Solution Development
12. DataOps
13. Data Pipelines
D. Data Governance
14. Program
15. Roles
16. Processes
17. Reporting & ANalytics Governance
18. Policies & Guidelines
19. Controls
E. Data Management
20. Data Quality
21. Metadata
22. Data Integration
23. Data Architecture
24. Data
28. Data Analyst Skills
29. Data Analyst Activity
30. Data Analysis Tools
H. Data Science
31. Data Scientist Skills
32. Data Science Program
33. Model Development
34. Model Deployment
I. Value
35. Impact
36. Innovation
37. Strategic Alignment
J. Non-Scored Questions
38. Reporting Structures
39. Staffing
40. Supported Users
41. Budget
42. Technology Infrastructure
K. Industry Questions
L. Open-Ended Questions
Sample Questions
Scored Questions
Likert Scale. All scored questions have a 6-point answer set with values for each answer. Values are averaged to determine overall, category, and subcategory scores.
H. Data Science
171. Domain Knowledge. Our data scientists have strong business knowledge in the domain they support.
173. Efficiency. Our data scientists spend more time creating and managing models than finding and preparing data.
Non-Scored Questions
Multiple Choice. All non-scored questions are multiple choice, with unique answers for all questions.
W. Organization Structure
217. Data Silos. How many business units work independently of the enterprise data analytics team?
0, 1-2, 3-5, 6-10, 11-20, 21+
Y. Budget
189. Production Models. How many analytical models are currently in production in your organization?
<1, 1-3, 4-10, 11-25, 26-100, 100+
193. Deployment Time. On average, how long does it take a machine learning engineer to deploy an approved model into production?
<1 week, <1 month, <3 months, <6 months, <12 months, 12+ months
227. Increase/Decrease. To what degree did the budget for your enterprise data and enterprise analytics increase or decrease from the prior year?
Increased a lot (10%+), Increased some (1-9%), etc.
228. Percentage of Revenue. What percentage of corporate revenues is the annual budget for the enterprise data and analytics program?
<1%, <2%, 3-5%, 6-10%, 11%+
Assignments
Key:
Suggested Primary Respondent
Suggested Primary Reviewer
A. Business & Culture
1. Executives
2. Business Users
3. Organization
4. Business Systems
Program Head
All
F. Business Intelligence
BI Director
All
25. Casual Users
26. Dashboards
27. Business Intelligence Tools
G. Data Analysis
B. Operating Model
5. Data & Analytics Team
6. Enterprise Alignment
7. Community
8. Training
9. Support
Program Head
All
C. Development
10. Project Management
11. Solution Development
12. DataOps
13. Data Pipelines
Head of BI, Data Management, or Application Development
All
D. Data Governance
28. Data Analyst Skills
29. Data Analyst Activity
30. Data Analysis Tools
Director of Analytics
All
H. Data Science
31. Data Scientist Skills
32. Data Science Program
33. Model Development
34. Model Deployment
Data Science Director
All
I. Value
35. Impact
36. Innovation
37. Strategic Alignment
Program Head
All
14. Program
15. Roles
16. Processes
17. Reporting & ANalytics Governance
18. Policies & Guidelines
19. Controls
Head of Data Governance
All
J. Non-Scored Questions
38. Reporting Structures
39. Staffing
40. Supported Users
41. Budget
42. Technology Infrastructure
Program Head
All
E. Data Management
20. Data Quality
21. Metadata
22. Data Integration
23. Data Architecture
24. Data
Head of Data Management
All
K. Industry Questions
Program Head
All
L. Open-Ended Questions
Program Head
All