[vc_section full_width=”stretch_row” css=”.vc_custom_1532085157436{margin-top: 0px !important;margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;background-color: #ffffff !important;}”][vc_row full_width=”stretch_row” css=”.vc_custom_1764240543096{margin-top: 0px !important;margin-bottom: 0px !important;padding-top: 40px !important;padding-bottom: 10px !important;}”][vc_column css=”.vc_custom_1661508335532{margin-top: 20px !important;margin-bottom: 20px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”][vc_column_text css=”.vc_custom_1764240954993{margin-bottom: 35px !important;}” el_class=”text-block”]
Manufacturing Analytics Provided Insights to Spot Business Process Improvement Opportunities
[/vc_column_text][vc_column_text css=”.vc_custom_1764240649433{margin-top: 0px !important;margin-bottom: 10px !important;}” el_class=”text-block”]Established in 1997, the client is a world leader in developing and commercializing first-or-best-in-class therapies for rare genetic diseases. Headquartered in California, US, the client has operations spread across 20+ countries and has 2500+ employees worldwide.
Background
The client had implemented analytics solutions that provided visibility into actual and historical data on finance, supply chain, and purchasing business processes. However, these solutions did not provide visibility into manufacturing data to enable the manufacturing team to identify bottlenecks and improve processes. Due to this, the manufacturing team faced several challenges such as:[/vc_column_text][rt_list_style list_style=”seven” list_content=”
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- Lack of visibility into production quantity, percentage produced on time/late, percentage scrap, etc
- Difficulty in obtaining insight into planned cost vs. actual cost, cost variance and percentage variance, and cost elements
- Difficulty in measuring planned vs. actual material and resource usage, material and resource usage variance, and percentage variance
- Limited visibility into material type, resource, and operation
- No measurement of batch aging and batch cycle time
- Cumbersome to get the count of the number of open work orders by order status
- Lack of trustworthy data for inventory balances, aging, and inventory expiration days
[/rt_list_style][vc_column_text css=”.vc_custom_1764240624957{margin-top: 0px !important;margin-bottom: 10px !important;}” el_class=”text-block”]As a result of the above, there was substantial difficulty and delays in answering the following common questions to support management decisions: [/vc_column_text][rt_list_style list_style=”seven” list_content=”
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- What is the impact on production quantity if a planned replenishment is delayed by a month?
- Feasibility of increasing production quantity if actual demand is X% more than forecast for one of the near-term periods?
- What cost elements to target to reduce production cost by 5%?
- How is the timeliness of transactions on the floor?
- How accurate are our planned order quantities vs actual material requirements?
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Solution
DiLytics partnered with the client to implement a solution based on Oracle Manufacturing Analytics. The solution was implemented across the following phases:[/vc_column_text][rt_list_style list_style=”seven” list_css=”.vc_custom_1764240708914{margin-bottom: 20px !important;padding-left: 35px !important;}” list_extra_class=”text-block”]
- Phase I: Oracle Manufacturing Analytics was installed, setup, configured, and out-of-the-box data was loaded from Oracle E-Business Suite (EBS) and Oracle Advanced Supply Chain Planning (ASCP).
- Phase II: Out-of-the-box Discovery and Requirements Gathering – capture business requirements for the use of Manufacturing Analytics by the manufacturing team. Detailed design, development, and testing of Oracle Manufacturing Analytics to implement and deploy the product based on users’ business requirements.
- Phase III: Subsequent rollouts to address requirements not implemented in Phase II.
[/rt_list_style][vc_column_text css=”.vc_custom_1764240723859{margin-bottom: 10px !important;}” el_class=”text-block”]The solution enabled the analytical insights in the following areas for the client: [/vc_column_text][rt_list_style list_style=”seven” list_css=”.vc_custom_1764241031056{margin-bottom: 35px !important;padding-left: 35px !important;}” list_extra_class=”text-block”]
- Production Batch Transactions
- Indented BOM (Bill of Material)
- Material Usage Variance
- Material Transactions
- Where Used
- Routing Details
- Material Aging
- Scrap
- Inventory Expiration
- Inventory Adjustments
- Real-Time Inventory
- Zero Stock
- Stock Outs
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Business Benefits
[/vc_column_text][vc_column_text css=”.vc_custom_1764240788244{margin-bottom: 10px !important;}” el_class=”text-block”]The client achieved several improvements across manufacturing operations, including:[/vc_column_text][rt_list_style list_style=”seven” list_css=”.vc_custom_1764241052171{margin-bottom: 35px !important;padding-left: 35px !important;}” list_extra_class=”text-block”]
- Availability of insights to manufacturing supervisors and executives to spot business process improvement opportunities due to visibility into additional areas not captured currently or correctly
- Visibility into the latest production data on shared dashboards for all stakeholders in the manufacturing process
- Alignment of multiple organization functions along with consistent definitions and calculations for metrics and data points
- Enablement of manufacturing supervisors to redirect their efforts efficiently towards optimizing production operations
- Ability to respond to changes in manufacturing operations for executives and supervisors with the availability of automatic alerts on conditions and criteria defined
- Savings in manual effort spent by manufacturing supervisors in deriving manufacturing reports
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Technical Stack
[/vc_column_text][vc_column_text css=”.vc_custom_1764240875444{margin-bottom: 0px !important;}” el_class=”text-block”]Source Systems: Oracle ASCP, Oracle EBS
Data Integration Tool: Informatica
Data Warehouse: Oracle Business Analytics Warehouse
Reporting Tool: Oracle Analytics[/vc_column_text][/vc_column][/vc_row][/vc_section][vc_row full_width=”stretch_row” equal_height=”yes” content_placement=”middle” css=”.vc_custom_1764240897746{margin-top: 0px !important;margin-bottom: 0px !important;padding-top: 35px !important;padding-bottom: 75px !important;background-color: #ffffff !important;background-position: center !important;background-repeat: no-repeat !important;background-size: cover !important;}”][vc_column width=”1/3″ css=”.vc_custom_1531997568277{margin-top: 0px !important;margin-bottom: 10px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”][/vc_column][vc_column width=”1/3″][vc_column_text css=”” el_class=”text-block”]
DiLytics Delivers
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