Wilsonart Enhances Supply Chain Optimization with AWS and PREDICTif Solutions Partnership
Keeping ahead of demand with advanced analytics and machine learning
By Usman Aslam (Principal AWS Solutions Architect)
In the ever-evolving landscape of manufacturing and distribution, companies must constantly adapt to shifting demands and emerging technologies.
Wilsonart, a prominent name in engineered surfaces, has embraced this challenge head-on by leveraging machine learning, data analytics, and the power of Amazon Web Services (AWS) to optimize their supply chain operations.
By collaborating with PREDICTif, an Advanced-Tier AWS Consulting Partner, Wilsonart has successfully harnessed historical data to gain invaluable insights, enabling them to enhance warehouse efficiency, production optimization, and customer satisfaction.
The Evolution of Surface Materials
Gone are the days when laminate simply conjured memories of outdated kitchens and peeling countertops.
Today, Wilsonart stands as a leader in manufacturing and distributing innovative engineered surfaces. Their extensive range of products caters to diverse markets including office spaces, education institutions, healthcare facilities, residential areas, hospitality venues, and retail environments.
However, to stay competitive in a rapidly evolving market, Wilsonart recognized the necessity of embracing digital transformation to streamline their operations and accurately predict demand.
Striving for Operational Excellence
Efficient distribution has been the hallmark of Wilsonart’s competitive advantage. With a network of regional warehouses spread across nearly 20 markets, they have successfully delivered a wide array of products while upholding high service fulfillment standards.
Yet, as their product offerings and consumer base continue to expand, the complexities of optimizing their day-to-day operations with only two manufacturing centers became apparent. Reacting to market fluctuations was no longer a sustainable strategy.
Furthermore, the lack of resilient integration among customer business information, sales data, and product insights hindered informed decision-making.
Manual data collection over the years resulted in fragmented information, failing to capture the dynamic nature of demand behavior.
Partnering with PREDICTif and Embracing the Cloud
To proactively shape their strategies, Wilsonart needed to tap into years of historical data, which were scattered and lacked integration.
Recognizing the benefits of cloud infrastructure over traditional on-premises systems, Wilsonart turned to Amazon Web Services (AWS) for a scalable and flexible solution.
Consulting with experts from PREDICTif, they found that AWS offered the robustness and accessibility required to drive their digital transformation.
By harnessing machine learning and data analytics tools from AWS, PREDICTif established a cloud-based environment capable of ingesting and processing historical sales data.
This transformation saved Wilsonart both time and resources while ensuring the scalability needed to adapt to changing demands.
Stabilizing Models and Driving Insights
Despite dealing with moderately to extremely sparse data, Wilsonart and PREDICTif were determined to stabilize model learning and prediction accuracy.
They carefully selected the least sparse data from each warehouse and used it for training. Additionally, they imputed missing values using the median demand for each product variant over the training period.
Through AWS’s machine learning tools, PREDICTif constructed a model capable of providing accurate demand predictions based on historical data.
This model became a pivotal resource in identifying fast-moving and high-value products, enabling Wilsonart to proactively optimize their production process and resource allocation.
Results and Future Prospects
Aggregating historical sales data and business insights on a centralized AWS platform empowered Wilsonart to pinpoint key products and predict demand trends.
The machine learning model, enriched by their business intelligence capabilities, now serves as a predictive guide, allowing the company to anticipate market behavior and adjust their strategies accordingly.
These insights have far-reaching implications, enabling them to optimize production processes while considering factors like product attributes, labor availability, and economic dynamics.
Carl A., a representative from Wilsonart, expressed his enthusiasm for the newfound insights:
“This is such great information. We can now see how we can combine warehouses to fulfill orders sooner. We could even point to a client’s spiky purchase behavior.”
This kind of impact wouldn’t have been possible without the expertise of an experienced APN Partner like PREDICTif, who not only developed the forecasting model but also facilitated the seamless integration of Wilsonart’s AWS environment.
This, in turn, freed up their IT team for other critical projects.
A Clear Path Ahead
As part of their ongoing commitment to innovation, Wilsonart has exciting projects on the horizon. Their plans include the implementation of a recommendation engine using Amazon SageMaker, Amazon Personalize, and AWS Glue.
This forward-looking initiative aims to enhance the customer experience on Wilsonart’s global eCommerce platform, further solidifying their position as a technology-driven leader in the engineered surfaces industry.
In conclusion, Wilsonart’s journey exemplifies the power of harnessing historical data, machine learning, and cloud infrastructure to optimize supply chain operations.
By partnering with PREDICTif and leveraging the capabilities of Amazon Web Services, Wilsonart has unlocked new avenues for growth, efficiency, and customer satisfaction in a rapidly evolving market.
About the Author
Usman Aslam stands as a seasoned Principal Solutions Architect, boasting over 16 years of experience within the technology domain. His remarkable journey includes achieving all 12 AWS certifications, a testament to his unwavering commitment and profound expertise. With an extensive background spanning Amazon Web Services (AWS), Capgemini, and Emerson, Usman has refined his skills in crafting resilient cloud solutions. He has been at the forefront of steering application migration and modernization onto the AWS platform. Usman’s leadership is a driving force behind the seamless transition and modernization of systems from on-premises environments to the Cloud. Notably, Usman has earned the trust of both enterprises and startups, owing to his exceptional skill set and adept leadership, rendering him an invaluable asset in their respective journeys to the cloud.
