Transforming Planning Efficiency for a Glasgow-based Packaging Company

McLaren Packaging Ltd, a prominent UK-based packaging company, operates in a highly seasonal industry where careful planning is essential to manage large order quantities and procurement lead times effectively. With the dynamic nature of their business, they faced significant challenges in handling weekly reports from end clients predicting future packaging usage. These reports arrived in various formats, demanding significant time and attention to process manually. This manual effort not only hindered planning efficiency but also left the company vulnerable to surprises caused by unexpected demand fluctuations.

Situation Overview

We found that the client’s manual process of handling diverse weekly reports from various clients was time-consuming and prone to errors. The reports’ inconsistency in formats required extensive manual data entry and transformation, which delayed planning and made the company susceptible to unexpected demand changes.

Objective

The primary goal was to automate the data handling and processing to streamline planning processes, reduce manual effort, and improve data accuracy. The client wished to leverage technology to transform raw data into actionable insights, thereby enhancing decision-making and operational efficiency.

Strategy and Implementation

We implemented a comprehensive solution using SharePoint and Azure services for data transformation and modeling, complemented by Power BI reports and dynamic Excel files. Our strategy included:

1. Developing an Automated System: We created an automated system to streamline the handling of input raw files into a well-defined data model using SharePoint and Azure services.

2. Data Cleansing and Modeling: Utilizing various data cleansing and modeling techniques ensured the accuracy and consistency of the data.

3. Generating Insightful Reports: The established data model was used to generate Power BI reports, providing the client with actionable insights for effective planning and decision-making.

4. Creating Dynamic Excel Files: We developed dynamic Excel files directly linked to the data model, allowing the client to generate custom reports effortlessly and share them with end customers.

Results

The implemented solution brought significant improvements:

– Efficient Planning Processes: Automation reduced manual effort and time spent on processing weekly reports, allowing the client to focus on strategic planning.

– Improved Data Accuracy: Advanced data cleansing and modeling techniques ensured reliable and consistent data, aiding informed decision-making.

– Actionable Insights: Power BI reports provided valuable insights into market trends, demand forecasts, and resource allocation.

– Enhanced Report Generation: Dynamic Excel files linked to the data model streamlined report generation and sharing, enhancing overall efficiency.

– Significant Time Savings: The solution saved the client at least 10 hours per week, enabling resource reallocation to more value-added activities.

Lessons Learned and Conclusion

Throughout the project, we learned the importance of integrating advanced data transformation tools to handle diverse data sources efficiently. The use of Power BI and dynamic Excel files proved crucial in providing actionable insights and streamlining report generation. This project showcased our expertise in leveraging technology to solve complex data handling issues, ultimately improving our client’s planning processes and operations.