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1
What percentage of machine learning models (created by you or your colleagues with the intention of being deployed) have actually been deployed?
In your experience, what is the main impediment to model deployment?Other (please specify)
What is your employer type:
2
21 - 40%Decision makers unwilling to approve the change to existing operations
Industry, but non-vendor (working for a company that uses analytics)
3
21 - 40%Privacy / legal issue
Industry, but non-vendor (working for a company that uses analytics)
4
0 - 20%Decision makers unwilling to approve the change to existing operations
Consultant or vendor (working for a company that provides analytics products or services)
5
41 - 60%Decision makers unwilling to approve the change to existing operations
Industry, but non-vendor (working for a company that uses analytics)
6
21 - 40%Technical hurdles in implementing/integrating the model or its scores into existing operations
Consultant or vendor (working for a company that provides analytics products or services)
7
61 - 80%Decision makers unwilling to approve the change to existing operations
Consultant or vendor (working for a company that provides analytics products or services)
8
41 - 60%Privacy / legal issue
Consultant or vendor (working for a company that provides analytics products or services)
9
0 - 20%Decision makers unwilling to approve the change to existing operations
Industry, but non-vendor (working for a company that uses analytics)
10
0 - 20%Model performance not considered strong enough by decision makers
Industry, but non-vendor (working for a company that uses analytics)
11
0 - 20%Model performance not considered strong enough by decision makersOther
12
21 - 40%Technical hurdles in implementing/integrating the model or its scores into existing operations
Industry, but non-vendor (working for a company that uses analytics)
13
81 - 100%Decision makers unwilling to approve the change to existing operations
Consultant or vendor (working for a company that provides analytics products or services)
14
41 - 60%Decision makers unwilling to approve the change to existing operations
Industry, but non-vendor (working for a company that uses analytics)
15
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Consultant or vendor (working for a company that provides analytics products or services)
16
0 - 20%Decision makers unwilling to approve the change to existing operations
Government / non-profit
17
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Consultant or vendor (working for a company that provides analytics products or services)
18
0 - 20%Decision makers unwilling to approve the change to existing operations
Industry, but non-vendor (working for a company that uses analytics)
19
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Government / non-profit
20
0 - 20%Decision makers unwilling to approve the change to existing operations
Government / non-profit
21
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Industry, but non-vendor (working for a company that uses analytics)
22
41 - 60%Model performance not considered strong enough by decision makers
Industry, but non-vendor (working for a company that uses analytics)
23
81 - 100%Decision makers unwilling to approve the change to existing operations
Industry, but non-vendor (working for a company that uses analytics)
24
0 - 20%Decision makers unwilling to approve the change to existing operations
Industry, but non-vendor (working for a company that uses analytics)
25
81 - 100%Privacy / legal issue
Consultant or vendor (working for a company that provides analytics products or services)
26
61 - 80%Technical hurdles in implementing/integrating the model or its scores into existing operations
Consultant or vendor (working for a company that provides analytics products or services)
27
0 - 20%Decision makers unwilling to approve the change to existing operations
Academia / Research
28
0 - 20%Model performance not considered strong enough by decision makers
Industry, but non-vendor (working for a company that uses analytics)
29
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Consultant or vendor (working for a company that provides analytics products or services)
30
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Academia / Research
31
0 - 20%Decision makers unwilling to approve the change to existing operationsOther
32
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Government / non-profit
33
21 - 40%Technical hurdles in implementing/integrating the model or its scores into existing operations
Academia / Research
34
0 - 20%Model performance not considered strong enough by decision makers
Academia / Research
35
21 - 40%Model performance not considered strong enough by decision makers
Consultant or vendor (working for a company that provides analytics products or services)
36
0 - 20%Model performance not considered strong enough by decision makers
Consultant or vendor (working for a company that provides analytics products or services)
37
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Industry, but non-vendor (working for a company that uses analytics)
38
21 - 40%Technical hurdles in implementing/integrating the model or its scores into existing operations
Industry, but non-vendor (working for a company that uses analytics)
39
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Consultant or vendor (working for a company that provides analytics products or services)
40
21 - 40%Model performance not considered strong enough by decision makers
Industry, but non-vendor (working for a company that uses analytics)
41
21 - 40%Model performance not considered strong enough by decision makers
Academia / Research
42
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Academia / Research
43
41 - 60%Technical hurdles in implementing/integrating the model or its scores into existing operations
Consultant or vendor (working for a company that provides analytics products or services)
44
0 - 20%Decision makers unwilling to approve the change to existing operations
Industry, but non-vendor (working for a company that uses analytics)
45
21 - 40%Decision makers unwilling to approve the change to existing operationsStudent
46
0 - 20%Model performance not considered strong enough by decision makers
Consultant or vendor (working for a company that provides analytics products or services)
47
21 - 40%Decision makers unwilling to approve the change to existing operations
Industry, but non-vendor (working for a company that uses analytics)
48
61 - 80%Model performance not considered strong enough by decision makers
Industry, but non-vendor (working for a company that uses analytics)
49
21 - 40%Technical hurdles in implementing/integrating the model or its scores into existing operationsOther
50
0 - 20%Decision makers unwilling to approve the change to existing operations
Industry, but non-vendor (working for a company that uses analytics)
51
0 - 20%Model performance not considered strong enough by decision makers
Industry, but non-vendor (working for a company that uses analytics)
52
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Academia / Research
53
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operationsStudent
54
41 - 60%Decision makers unwilling to approve the change to existing operations
Government / non-profit
55
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Consultant or vendor (working for a company that provides analytics products or services)
56
0 - 20%Model performance not considered strong enough by decision makersStudent
57
0 - 20%Model performance not considered strong enough by decision makers
Industry, but non-vendor (working for a company that uses analytics)
58
0 - 20%Decision makers unwilling to approve the change to existing operations
Industry, but non-vendor (working for a company that uses analytics)
59
0 - 20%Model performance not considered strong enough by decision makers
Industry, but non-vendor (working for a company that uses analytics)
60
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operationsStudent
61
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Academia / Research
62
0 - 20%Model performance not considered strong enough by decision makers
Industry, but non-vendor (working for a company that uses analytics)
63
81 - 100%Technical hurdles in implementing/integrating the model or its scores into existing operations
Consultant or vendor (working for a company that provides analytics products or services)
64
81 - 100%Technical hurdles in implementing/integrating the model or its scores into existing operations
Academia / Research
65
0 - 20%Privacy / legal issue
Industry, but non-vendor (working for a company that uses analytics)
66
0 - 20%Other (please specify)Research purposes
Academia / Research
67
21 - 40%Model performance not considered strong enough by decision makers
Consultant or vendor (working for a company that provides analytics products or services)
68
61 - 80%Model performance not considered strong enough by decision makers
Industry, but non-vendor (working for a company that uses analytics)
69
0 - 20%Other (please specify)
too much hype, deep learning often fails at reality check
Industry, but non-vendor (working for a company that uses analytics)
70
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Industry, but non-vendor (working for a company that uses analytics)
71
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Industry, but non-vendor (working for a company that uses analytics)
72
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Industry, but non-vendor (working for a company that uses analytics)
73
0 - 20%Privacy / legal issue
Industry, but non-vendor (working for a company that uses analytics)
74
0 - 20%Decision makers unwilling to approve the change to existing operations
Consultant or vendor (working for a company that provides analytics products or services)
75
0 - 20%Decision makers unwilling to approve the change to existing operations
Consultant or vendor (working for a company that provides analytics products or services)
76
21 - 40%Other (please specify)Loss of interest
Industry, but non-vendor (working for a company that uses analytics)
77
0 - 20%Decision makers unwilling to approve the change to existing operations
Industry, but non-vendor (working for a company that uses analytics)
78
61 - 80%Decision makers unwilling to approve the change to existing operations
Industry, but non-vendor (working for a company that uses analytics)
79
21 - 40%Model performance not considered strong enough by decision makers
Industry, but non-vendor (working for a company that uses analytics)
80
0 - 20%Decision makers unwilling to approve the change to existing operations
Industry, but non-vendor (working for a company that uses analytics)
81
21 - 40%Decision makers unwilling to approve the change to existing operations
Industry, but non-vendor (working for a company that uses analytics)
82
21 - 40%Decision makers unwilling to approve the change to existing operations
Government / non-profit
83
21 - 40%Decision makers unwilling to approve the change to existing operations
Government / non-profit
84
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Consultant or vendor (working for a company that provides analytics products or services)
85
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Academia / Research
86
61 - 80%Technical hurdles in implementing/integrating the model or its scores into existing operations
Government / non-profit
87
21 - 40%Technical hurdles in implementing/integrating the model or its scores into existing operations
Consultant or vendor (working for a company that provides analytics products or services)
88
0 - 20%Model performance not considered strong enough by decision makers
Industry, but non-vendor (working for a company that uses analytics)
89
0 - 20%Decision makers unwilling to approve the change to existing operations
Industry, but non-vendor (working for a company that uses analytics)
90
41 - 60%Decision makers unwilling to approve the change to existing operations
Industry, but non-vendor (working for a company that uses analytics)
91
21 - 40%Decision makers unwilling to approve the change to existing operations
Industry, but non-vendor (working for a company that uses analytics)
92
0 - 20%Model performance not considered strong enough by decision makers
Industry, but non-vendor (working for a company that uses analytics)
93
0 - 20%Model performance not considered strong enough by decision makers
Industry, but non-vendor (working for a company that uses analytics)
94
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Industry, but non-vendor (working for a company that uses analytics)
95
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operationsOther
96
21 - 40%Decision makers unwilling to approve the change to existing operations
Consultant or vendor (working for a company that provides analytics products or services)
97
0 - 20%Model performance not considered strong enough by decision makers
Industry, but non-vendor (working for a company that uses analytics)
98
81 - 100%Technical hurdles in implementing/integrating the model or its scores into existing operations
Consultant or vendor (working for a company that provides analytics products or services)
99
0 - 20%Technical hurdles in implementing/integrating the model or its scores into existing operations
Industry, but non-vendor (working for a company that uses analytics)
100
81 - 100%Technical hurdles in implementing/integrating the model or its scores into existing operations
Consultant or vendor (working for a company that provides analytics products or services)