Intelligent Document Processing Readiness Survey

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* 1. How would you best describe your organization? (choose one answer)

Enterprise shared services or GBS

Technology vendor

BPO

Consultant

Other (please specify)

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* 2. How has the pandemic highlighted pain points in your current automation initiatives? (choose one answer)

Insufficient end-to-end process integration

Lacking the technology to enable automated processing

Lacking data in the structured, digital format required to drive automated processing

Lacking robust machine learning and AI to drive more expansive automated processing

Other (please specify)

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* 3. What is limiting your capacity to manage high volumes of document processing? (choose top 3 answer choices?)

Cost of human resources required

Limited working hours (not 24x7)

No access to machine learning models

Low levels of accuracy in human-based manual extraction

Low levels of accuracy in existing OCR solution

Low confidence in automated results requires more human review

Large variety of document types

Other (please specify)

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* 4. How much of your enterprise data do you estimate is currently unstructured? (choose one answer)

<25%

26-50%

51-75%

>75%

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* 5. Do you believe the problem of “unstructured data” is impacting your operational productivity / business effectiveness?

Yes

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* 6. Do you have a strategy in place to address this data problem (i.e., unstructured)?

Yes

If yes, do you have a solution in mind? Please list it

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* 7. Where in your operation is the lack of digitized data most costly? (please describe)

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* 8. What rates of straight through processing are you currently achieving for each of the processes listed below? Please mark as relevant

	<10%	11-30%	31-60%	61-90%	>90%	I don't know/does not apply
Order-to-Cash	Order-to-Cash <10%	Order-to-Cash 11-30%	Order-to-Cash 31-60%	Order-to-Cash 61-90%	Order-to-Cash >90%	Order-to-Cash I don't know/does not apply
Record-to-Report	Record-to-Report <10%	Record-to-Report 11-30%	Record-to-Report 31-60%	Record-to-Report 61-90%	Record-to-Report >90%	Record-to-Report I don't know/does not apply
Procure-to-Pay	Procure-to-Pay <10%	Procure-to-Pay 11-30%	Procure-to-Pay 31-60%	Procure-to-Pay 61-90%	Procure-to-Pay >90%	Procure-to-Pay I don't know/does not apply
Hire-to-Retire	Hire-to-Retire <10%	Hire-to-Retire 11-30%	Hire-to-Retire 31-60%	Hire-to-Retire 61-90%	Hire-to-Retire >90%	Hire-to-Retire I don't know/does not apply
Claims Processing	Claims Processing <10%	Claims Processing 11-30%	Claims Processing 31-60%	Claims Processing 61-90%	Claims Processing >90%	Claims Processing I don't know/does not apply
Financial Spreading	Financial Spreading <10%	Financial Spreading 11-30%	Financial Spreading 31-60%	Financial Spreading 61-90%	Financial Spreading >90%	Financial Spreading I don't know/does not apply
Fraud Detection	Fraud Detection <10%	Fraud Detection 11-30%	Fraud Detection 31-60%	Fraud Detection 61-90%	Fraud Detection >90%	Fraud Detection I don't know/does not apply
[Other/list below]	[Other/list below] <10%	[Other/list below] 11-30%	[Other/list below] 31-60%	[Other/list below] 61-90%	[Other/list below] >90%	[Other/list below] I don't know/does not apply

For 'other' above, please list the process

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* 9. If you currently use an OCR solution, how accurate is it?

100%

Clear

i We adjusted the number you entered based on the slider’s scale.

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* 10. How well are you currently managing data labeling for the purpose of supporting machine learning?

Very well

Quite well

Satisfactory

Struggling somewhat

Very badly

We are not using machine learning

N/A

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* 11. Are your data labeling efforts hampered because you don't have access to skilled resources (e.g., data scientists)?

Yes

N/A

Please feel free to comment:

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* 12. How many document samples do you require to train a production-ready solution?

<100

<1,000

<10,000

<100,000

>100,000

I don't know / N/A

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* 13. Please rank your current solution effectiveness in terms of:

	Highly effective	Relatively effective	Acceptable	Not very effective	Very ineffective	Non-existant
Intelligent document processing	Intelligent document processing Highly effective	Intelligent document processing Relatively effective	Intelligent document processing Acceptable	Intelligent document processing Not very effective	Intelligent document processing Very ineffective	Intelligent document processing Non-existant
Intelligent image processing	Intelligent image processing Highly effective	Intelligent image processing Relatively effective	Intelligent image processing Acceptable	Intelligent image processing Not very effective	Intelligent image processing Very ineffective	Intelligent image processing Non-existant
Predictive analytics	Predictive analytics Highly effective	Predictive analytics Relatively effective	Predictive analytics Acceptable	Predictive analytics Not very effective	Predictive analytics Very ineffective	Predictive analytics Non-existant

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* 14. Is your organization using Deep Learning and GPU computing power in its current automation initiatives?

Yes

I don't know

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* 15. Have you implemented 'fuzzy search' capabilities in your enterprise content-based search engines?

Yes

I don't know

I am not familiar with fuzzy search

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* 16. To what extent are you currently using mobile apps to scan and mine data?

Extensively

Moderately

In a few instances only

Not at all

In which areas do you use mobile scanning?

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* 17. If you are an enterprise GBS/SSO and work with an outsource provider (BPO), how well are they supporting your digital transformation objectives?

Very well

Moderately well

Satisfactory

Not very well

They are doing nothing to support this

We do not outsource

We are not an enterprise GBS/SSO

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* 18. If you are an enterprise GBS/SSO working with a BPO, and IF you are ramping up your in-house automation capability, are you considering bringing some of the work back in-house?

Yes

We do not outsource

We do not have a robust in-house automation capability

We are not an enterprise GBS/SSO