Case study -
This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.
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To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. When you are ready to answer a question, click the Question button to return to the question.
Company Overview -
Company Overview. Company Structure
Contoso Compressor Ltd. is a large global manufacturer with 12,000 employees. Contoso Compressor produces, installs, and services large B2B and small B2C gas and air compressors.
They have manufacturing plants and service centers in:
North America (Canada, US, Mexico) Territories
• US – 600 Service Technicians, 60 Call Center Agents, 30 Dispatchers
• Canada – 300 Service Technicians, 30 Call Center Agents, 15 Dispatchers
• Mexico – 200 Service Technicians, 20 Call Center Agents, 10 Dispatchers
Europe Territories -
• Germany – 200 Service Technicians, 20 Call Center Agents, 10 Dispatchers
• France – 150 Service Technicians, 15 Call Center Agents, 7 Dispatchers
• Italy – 100 Service Technicians, 10 Call Center Agents, 5 Dispatchers
South America Territories -
• Brazil – 200 Service Technicians, 20 Call Center Agents, 10 Dispatchers
• Argentina – 100 Service Technicians, 10 Call Center Agents, 5 Dispatchers
India Territories -
• Mumbai – 100 Service Technicians, 10 Call Center Agents, 5 Dispatchers
• Chennai – 150 Service Technicians, 15 Call Center Agents, 7 Dispatchers Contoso
Contoso Compressor sales channels include direct and via distributors.
Contoso Compressor service and installation channels include direct and via service partners.
Company Overview. Existing Systems
Existing systems:
• SAP for ERP
• Siebel for Sales and Customer Service
• Home grown for Field Service and Installations
Dynamics 365 has been selected for Sales, Customer Service, and Field Service.
Azure IoT and Azure Machine Learning have been selected for Connected Field Service.
Sales and Service Overview -
Sales and Service Overview. B2B Sales and Service Overview
Sales -
• 70% of total Sales & Service Revenue
• 20% new sales revenue is through distributors
Installations -
• Variety of large compressors
• Scheduled with Dispatch when equipment has been shipped
• Take a crew of 2-3 technicians
Service -
• 95% of service calls handled by Contoso Call Center
• All calls come to a regional service center
• Break Fix
• Planned/Preventive Maintenance
• Both Break Fix and Planned/Preventive Maintenance Work Orders require 1 technician
• Planned/Preventive Maintenance
◦ Requires a detailed Inspection prior to restart of equipment
Sales and Service Overview. B2C Sales and Service Overview
Sales -
• 30% of total Sales & Service Revenue
• 100% of new Sales revenue from distributors
No Installation -
Service -
• 95% of all service issues handled by partners/distributors
• Service calls to Contoso Call Center are routed to a partner/distributor for service
• Only 1% of all Service Revenue
Sales and Service Overview. Business Goals
Contoso Compressor desires to double both their Sales and Service Revenue over the next 5 years.
To achieve this, they have developed the following goals as part of implementing a new CRM Sales, Service, and Field Service application:
1. New Acquisitions
2. Partner/Distribution network expansion for B2B and B2C
3. New B2B Service Offerings
4. Increase Customer Satisfaction/NPS
Current Challenges -
Current Challenges. Call Center -
• Siloed systems
• Disconnected from other regions
• Poor Return tracking
• Poor partner visibility
Current Challenges. Work Order Management
• No visibility to truck stock
• No task breakdown on Work Orders
• Poor reconciliation to partners/distributors
Current Challenges. Resource Management
• No crew capability for installs
• No visibility across regions
Current Challenges. Contract/Agreement Management
• Service is often given away due to poor entitlement tracking
• No tickler system for renewals
Current Challenges. Asset Management
• No sub-asset tracking
• No work Order history
• No visibility to detailed location tracking
• No ability to connect to IoT
Current Challenges. Mobile Technician Capability
• No offline mode
• Inspections are done manually
• No quoting, signature, or job summary/print capability
Current Challenges. Scheduling -
• Lack of status updates from technicians
• Manual crew scheduling for installs
• No ability to estimate travel time
• No filter capability to search for the best technician
Desired Functionality -
Desired Functionality. Call Center
• Customer 360 capability with Knowledge Base
• Visibility to Partner/Distributor information
• Portal capability for customer visibility to Knowledge, equipment owned, open work orders and cases
Desired Functionality. Work Order management
• Defined Work Order Tasks
• Inventory tracking
• Digital Inspections with Branch Logic and Reporting
• Integration to ERP for proper pricing and invoicing
Desired Functionality. Inspections
• Conditional logic for Gas Compressor pressure reading failure
◦ By looking at the reading, a technician can see if it's in the red, indicating failure. If fail, must shut down, clean or replace pressure valve
• Impromptu Inspections – the ability to create inspections at a customer site on assets without a work order while working on another work order at the customer site.
• Inspection results are critical to review with the customer after the inspection is performed
Desired Functionality. Resource Management
• Flexible Work Hours
• Crews, equipment tracking as resources for scheduling
• Skills with proficiency levels
• Drip Scheduling for planned maintenance jobs
Desired Functionality. Asset Management
• Track Asset sub-components
• Connected Service for new equipment
• Azure Machine Learning to offer a new chargeable service for machine uptime
• Capture defined asset readings to feed the Azure Machine Learning model
• Many internal assets are used on jobs. We need to be able to schedule those assets with a technician on a job.
◦ We also perform our own maintenance on internal assets
◦ These would not be needed for RS
Desired Functionality. Contract/Agreement Management
• Generate Planned Maintenance jobs 3 months in advance for capacity planning
• Tickler system to notify customers of expirations
• Track covered equipment and related entitlements
Desired Functionality. Mobile Technician Capability
• Offline
• Digitized Inspections
• Geo-fencing for no-touch arrival and departure
• "Uber-like" functionality, notifying customers when a technician will be arriving
• Remote Assist functionality to quickly get junior technicians in the field and increasing first time fix rate
Desired Functionality. Scheduling
• Schedule Boards visible to each region
• Assign resources based on skills and proficiency
• Visibility to access resources from other regions
• Drip Scheduling for inspection jobs
• Scheduling optimization for small jobs
• Automated crew assignment for installation jobs
Desired Functionality. Returns Management
• RMA's
◦ Tied to Customer Service
◦ Track open Returns to reduce part/asset leakage & charge for not returned items
◦ The biggest issue we face today is that we can't track an item that a customer has returned
• RTV
◦ Ability to send in-warranty parts back to vendor for credit or exchange
Desired Functionality. IoT -
• IoT devices will be place on all new and existing equipment.
• Devices will measure compressor temperature and motor pressure of the equipment.
• Azure Machine Learning is desired to predict failure based on trends of compressor temperature and pressure readings.
• Currently, there is no way to capture backflow pressure because it can only be measured during the onsite inspection by a technician.
• Contoso Compressor would like to capture that value and feed it back to the machine-learning algorithm to better measure performance and predict failure.
You are the lead consultant on a Dynamics 365 Field Service implementation for Contoso Compressor. You are designing the RMA and RTV process with the customer.
While there are many benefits associated with this process, you need to advise the customer on where they might be able to find the biggest cost savings based on their requirements.
What should you recommend?
LnP
2 months agoMrEz
6 months agoMrEz
6 months ago