Business Challenges
Retailers are embracing the transformative potential of Data Analytics to redefine their warehouse picking processes, fundamentally reshaping their ability to meet customer demands effectively.
Warehouses, the central hubs for storing and distributing products, serve as the backbone of the supply chain and play a pivotal role in the success of retail operations. These warehouses are typically organized into fixed layout zones that are rarely altered. However, this static structure poses a significant challenge as market demands for goods are in constant flux. Consequently, the efficiency of the picking process within these warehouses becomes compromised, resulting in operational bottlenecks.
One of the primary challenges in enhancing warehouse efficiency lies in optimizing the layout to minimize picking time. In the dynamic realm of retail, where time equates to money, the utilization of Data Analytics is essential. By employing advanced analytics techniques, retail companies can analyze historical order data, inventory flow, and customer demand patterns. This data-driven approach enables them to strategically reconfigure their warehouse layouts, ensuring that frequently requested items are positioned for swift access.
The application of Warehouse Picking Time Optimization through Data Analytics not only mitigates operational bottlenecks but also empowers retailers to meet customer expectations promptly. This, in turn, contributes to heightened customer satisfaction and provides a competitive edge in the ever-evolving retail landscape. By leveraging Data Analytics, retailers can not only adapt to changing market demands but also proactively optimize their operations, ultimately revolutionizing their approach to fulfilling customer needs.
AI Solution
To address this challenge, a solution was devised that leveraged historical picking data and AI techniques:
- Historical Data Analysis: The dynamically changing demands for goods in the market are reflected in the historical picking data of the warehouses. This data analysis phase extracts insights about the most demanding goods and their associated picking times. It reveals inefficiencies in the current warehouse operations.
- Standardized Operations: It is assumed that goods are moved within the warehouse using either forklifts or robots. The times required for traveling, loading, and picking are standardized based on this assumption.
- Reinforcement Learning Model: A reinforcement learning model is implemented to reorganize the layout of warehouses with the objective of minimizing picking time. The model uses historical picking data from the warehouses to train and refine its decision-making capabilities.
Expected Outcome
The anticipated outcome of implementing the reinforcement learning model is substantial:
- Optimized Layout: The results generated by the reinforcement learning model reveal that the most in-demand goods should be strategically positioned near the unloading gates of the warehouses. This layout adjustment is projected to reduce picking time by approximately 30%.
By optimizing the layout of warehouses to align with changing market demands, this solution not only enhances operational efficiency but also contributes to significant time and cost savings in the warehousing process.
Our Team Members
AI TRANSFORMATION LEAD
Dr. Mikhail Krasnov
Based in Switzerland, Mikhail is an esteemed leader with a Ph.D. in Economics and recognized as a Certified Director by the London Institute of Directors. With a 30-year tenure in the IT sector, he co-founded Verysell Group in 1990 and now drives strategy and innovation across the entire organization. He staunchly believes that AI should be a catalyst for all businesses, not a threat, enhancing and transforming companies. To him, AI is a powerful tool for businesses to harness for their advantage.
Head of Applied AI Lab
Yurii Lozinskyi
Based in England, Yurii is the driving force behind Verysell Applied AI Lab. With 25 years of experience in Healthcare, Insurance, and Finance, he specializes in Business Process & Digital Transformation. Yurii excels in creating neural networks for diverse business automation, from medical diagnostics to machinery anomaly detection. Beyond tech, he’s a proficient software delivery manager and project leader. His leadership has fueled remarkable growth, achieving up to 60% CAGR by guiding 20+ Agile Teams globally.
Chief AI Scientist
Dr. Hung Dao
Based in Vietnam, Dr. Hung leads a dynamic Consulting Team, driving AI innovation across diverse sectors, from industrial visual inspection to medical image segmentation at our AAI Lab. With a PhD in Engineering from Keio University (2014), his expertise extends to groundbreaking research published in renowned conferences such as FG, BMVC, ICASSP, and ACCV, alongside multiple granted patents. With a distinguished track record at FPT, VinBrain & Nautilus AI, he’s a prominent figure in the AI landscape.
STRATEGIC ADVISOR ON AI
Dr. Alexey Minin
Prof. Dr. Alexey Minin, an esteemed expert in the digital economy and artificial intelligence implementation, boasts over 19 years in high-tech. Rising from Siemens engineer to associated partner at MHP – A Porsche Company, Germany, Alexey excels in management consulting, exponential technologies, and creating businesses based on modern tech. A Doctor of Science in AI, Honored Professor, and consultant for several boards of directors, Alexey specializes in digital transformation, AI application, and startup guidance. He co-founded startups, lectures globally, and is a sought-after speaker in digital conferences.
Business Development Manager
Muin Pirzada
Muin brings to the table an extensive background of over 13 years in the fields of Robotic Process Automation (RPA), Test Automation, and Artificial Intelligence (AI). This vast experience has not only equipped him with a profound knowledge of these cutting-edge technologies and deep passion for business growth and operational efficiency, but also with an acute understanding of their capability to revolutionize industries and streamline operations.
Marketing Manager
Ha Nguyen
Based in Hanoi, Ha spearheads marketing endeavors, leveraging over a decade of prowess in the global technology arena. She currently serves as AAI Lab’s Marketing Manager, leveraging her expertise in B2B marketing, branding, content strategies, and Agile methodologies to propel the company’s growth. Her practical know-how equips her to craft and execute effective marketing strategies for AAI Lab and other entities within the Verysell Group.
Software Development Automation Lead
Hieu Tran
Hieu, from Danang, Vietnam, heads the automation team at SmartDev. With a decade of experience in software development, he’s skilled in tech strategy and research. Known for boosting daily operations, Hieu shines in project coordination and customer happiness. Currently, he’s the top engineer at SmartDev and also leads the AAI Lab Software Development Automation.
Head of Project Management
Richard Sharp
Richard, based in Danang Vietnam, has over 40 years of IT experience. He has had many roles including Client Manager, Supplier Manager, and Service Management Program Manager. He has designed, developed and implemented advanced service management solutions for leading organizations across the technology, government, health, telecoms, oil & gas and financial services sectors.
HEAD OF AI EDUCATION
Soan Duong
Dr. Soan is a lecturer at the Computer Science Department within Le Quy Don Technical University. She is also a senior research scientist with keen interest in computer vision and medical imaging. Her research work has been published at prestigious venues, including ISBI, ICIP, ICASSP, BMVC, and CVPR. Soan plays an active role in the academic community by serving as a dedicated reviewer for esteemed publications such as: IEEE Access and NMR in Biomedicine.