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Survey on Predictive Analytics in Workforce Resilience for Dutch 3PL Providers

Thank you for participating in this survey on predictive analytics and workforce resilience in Dutch Third-Party Logistics (3PL) providers. This survey aims to assess how How can predictive analytics can strengthen workforce resilience in Dutch Third-Party Logistics (3PL) providers by addressing current labour shortages in the Netherlands and offering operational flexibility, while considering associated risks to create a flexible yet stable workforce pool? The survey takes approximately 10-15 minutes to complete. All responses are anonymous and will be used for research purposes only.

What is your current role in your organization? *

Operations Manager
HR Manager
Supply Chain Manager
Workforce Planner
Data Analyst
IT Specialist
Logistics Engineer
Other

How many employees does your company have in the Netherlands?*

Small (1-49 employees)
Medium (50-249 employees)
Large (250+ employees)

What is your company's level of predictive analytics adoption for workforce planning? *

Fully implemented
Partially implemented
In pilot/testing phase
Not implemented, but considering
Not implemented and no plans to adopt

How effective has predictive analytics been in addressing workforce shortages in your company?*

1 (Not effective at all)
2 (Slightly effective)
3 (Moderately effective)
4 (Effective)
5 (Highly effective)
6 (Thinking to implement)

Which workforce planning challenges does your company face? *

Sudden labour shortages
High employee turnover
Poor demand forecasting
Inflexible workforce structures
Lack of skilled workforce
Unpredictable seasonal demand
Other

How has predictive analytics improved workforce planning in your company?*

If you are considering implementing predictive analytics, what key improvements do you aim to achieve by implementing predictive analytics? Answer in Others Section

Labour shortage challenges
Reduced need for temporary labour
Increased workforce flexibility
Improved resource allocation
Reduced overtime dependency
No noticeable impact
Not applicable
Other

How effective is predictive analytics in enabling workforce adaptability to fluctuating demand?*

If you are just thinking to implement predictive analytics, how effective could predictive analytics be in improving workforce adaptability to fluctuating demand? In others, write if you are researching it and if you think your company would be interested. Answer in Others Section

1 (Not effective at all)
2 (Slightly effective)
3 (Moderately effective)
4 (Effective)
5 (Highly effective)
Other

Which predictive analytics features does your company use to manage workforce adaptability?*

If you are just thinking to implement, what do you think will work the best for you? Answer in Others Section

AI-driven demand forecasting
Automated workforce scheduling
Real-time workforce monitoring
Workforce skill-matching algorithms
Predictive absenteeism modelling
None of the above
Other

What risks have you encountered in implementing predictive analytics for workforce planning? *

If you are thinking of implementing, what risks are your main concerns? Answer in Others Section

Data accuracy and reliability issues
Employee resistance to adoption
High implementation costs
Compliance and regulatory concerns
Dependence on external AI/data providers
Lack of internal expertise to manage predictive models
Other

How does your company mitigate risks related to predictive analytics adoption? *

If you are thinking of implementing, how currently your company is mitigating labour shorages risks? Answer in Others Section

Continuous staff training
Investing in high-quality data sources
Compliance monitoring and legal assessments
Partnering with AI/data analytics firms
Using hybrid (AI + human judgment) decision models
Other

How has predictive analytics influenced workforce stability (e.g., retention, long-term workforce planning) in your company? *

If you are thinking of implementing, what do you think will be the impact on workforce stability? Answer in Others Section

1 (No impact)
2 (Slight improvement)
3 (Moderate improvement)
4 (Significant improvement)
5 (Major improvement)
Other

What are your company’s future plans regarding predictive analytics in workforce planning? *

Expand current use
Maintain current level
Reduce reliance
Exploring new predictive analytics models
Not applicable
Exploring options

What additional factors should be considered to improve predictive analytics for workforce resilience? *

Thank you for your participation!

This survey is completely confidential, and your responses will only be used for research purposes. If you wish, you may mention your company’s name solely for research purposes, and you are also welcome to provide your contact details if you would like to discuss this topic further or receive insights from the study.

For any further inquiries, feel free to reach out.

Researcher: Andreea Magdalena Drulea

Affiliation: Breda University of Applied Sciences

Program: Logistics Engineering

If you would like to receive study findings or explore this topic further, please contact: [email protected]

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