Data-Driven Leadership Web Survey

Welcome to the R&G Data-Driven Leadership Web Survey

Thank you for participating in our Data Driven Leadership Web Survey. Your feedback is important. This survey is focused on assessing where you stand on your Data-Driven Journey. Please fill in the form from your own accountability perspective. It will take you approximately 5 minutes to complete the survey. All questions are required.

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* 1. Contact Information

Name *

Organisation *

Role

Email Address

Phone Number

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* 2. What is your scope of accountability?

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* 3. In which SCOR end-to-end process are you active?

Plan: Demand/Supply Planning and Management

Source: Sourcing Stocked, Make-to-Order, and Engineer-to-Order Product

Make: Make-to-Stock, Make-to-Order, and Engineer-to-Order Production Execution

Deliver: Order, Warehouse, Transportation, and Installation Management for Stocked, Make-to-Order, and Engineer-to-Order Product.

Return: Return of Raw Materials and Receipt of Returns of Finished Goods

Other

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* 4. Which KPI's are of importance to your line of business?

Perfect order fulfillment (OTIF)

Price Realisation

Margin Improvement

Capacity/Asset Utilization (OEE)

Variable Cost Productivity

Total Cost-to-serve

Return on Capital Employed (ROCE)

(P2P, O2C) Cash Cycle Reduction (AR,AP, Inventories)

Other (please specify)

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* 5. Our business is considering to invest in (next 2 yrs):

Internet of Things/ sensors industrial purposes

Robotic Process Automation

Process Mining

ERP implementations

Supply chain (AI) Optimisation algorithms

Manufacturing Execution Systems

Business Apps

Real -time data capture

S&OP and Demand sensing solutions

Other (please specify)

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* 6. Which Level of Analytics is currently practised in your Organisation?

Ad-hoc Analytics: Data scientists use different methods and tools to gain insights from current and past data.

Descriptive Analytics: Standard Performance Reporting based on historical and current data.

Prescriptive Analytics: Using quantitative techniques, models and machine learning to specify optimal behavior and actions.

Predictive Analytics: Forecasting and Model based techniques using past data to predict the future.

Autonomous Analytics: Using Artificial Intelligence to create and improve models to learn from data without human analysts.

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* 7. Which situation best describes your Data Journey?

We have a lot of data hidden in systems, but no way to extract insights.

We have dashboards with many KPI's, but decisionmaking is suboptimal.

We have BI and Data science specialists, but have not realized true process improvement.

In our Supply Chain End-to-End visibility and transparency are lacking.

We have implemented cutting edge tools, but have not realized true process improvement.

Other (please specify)

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50% of survey complete.