DMAIC Project: Reducing Lead Time in Delivery Planning

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There are many stakeholders around the process to be improved, who influence the success of the work. Before the project, there was no data on this problem. A data reporting system had to be built to move the project forward.

Baseline (Define)

It was raised at the sales Lean events that confirmation of delivery time is not always received by the customer in the desired time. The process to be improved is the production planning process. The internal customer is Customer Service and the external customer is the buying customer.

Tavoitteena on, että tuotannonsuunnittelu saisi toimitusajan annettua Customer Servicelle (CS) <24h:ssa.

Process performance at the beginning (Measure)

The data showed that the average planning lead time was 37 hours. There was also a lot of variation. From less than an hour to several hundred hours. The assumption was that not all planning takes place in less than 24 hours. The data showed that the lead time and variation were higher than we had expected. As a result, those involved in the process became even more interested in finding out why.

Improvement measures (Analyze & Improve)

Root causes and solutions:

• Interdepartmental information flow -> Team board and vertical meetings.
• Product approvals by the lead designer -> Substitutes can also approve.
• CS has no container models -> Production Planning provides CS with container models, layouts and pallet dimensions.
• Batching of orders -> Orders are confirmed in the order of arrival.
• Waiting for customer to be created -> Create customer before entering order
• Waiting for customer data from Sales -> Out of Control Action Plan (OCAP) / new Spin-off project
• Waiting for raw material data from procurement -> OCAP / new Spin-off project

The biggest challenges were the constant changes at the factory, which affected the project's completion. Also, the number of order lines has been high during the project compared to the order line numbers in the historical data.

Lean Six Sigma tools used:

• MR Chart, Capability Analysis, Kruskal-Wallis Test, Box Plot Test, Standard Deviations Test, Before/After I-MR Chart
• Soft skills: data-driven improvement. Increased understanding that data is used to improve processes, not to blame people.

Results (Control)

Results:

• The lead time for order confirmations decreased by 20.5% (31.7h -> 25.2h).
• The variation in order confirmations decreased by 44.4% (68 -> 37.8)
• Results are maintained through daily monitoring.
• OCAP and team meetings
• Lots of ideas for improvement for the future. (Spin-off projects)

Lessons Learned:

• The data must be easily accessible during the project. (In your own hands.)
• An easier topic/process could have been chosen as a training project.
• The process should be in a stable state during the process.

Although the process improved considerably, the target was not met. This was due to factors outside the process area. To overcome them, new improvement projects are planned to be launched in different departments:

• Ensuring the necessary customer information for orders
• Improving access to raw material data

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This project was a Black Belt training project, which the participant did as part of the training and received a Black Belt certificate at the end of the project.

If you are interested in learning how to improve your processes using Lean and Six Sigma, and obtaining a certificate at the same time, check out the different options at the link: Lean Six Sigma trainings.

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