The retail sector generates 121 million tonnes of food waste worldwide every year, which poses both environmental and financial challenges for companies. Inadequate planning of resources and supply of goods, as well as inefficient supply chains, worsen operating margins and reduce profitability per unit area. Slowly rotating products and unoptimised inventories lead to significant financial losses and wasted resources. Circly offers an advanced AI solution to optimise these processes, benefiting both the environment and finances.
Shelf metre optimisation and conservation of valuable resources
Circly has created a solution to enable retail companies to be environmentally friendly and sustainable while improving profit margins. Utilizing Circly’s predictive AI (artifical intelligence) solution, the high level of accuracy of sales predictions enable precise planning of resources, resulting in increased shelf availability, reducing excess inventories, stock-outs and food waste.
Keywords
- Supply Chain optimization for retail companies
- Standardization of data structure and transmission
- Sales forecasting through AI
- Waste reduction and financial upsides
- Finance savings
Challenges of supply chain optimisation in retail
Circly's challenge was to optimize and enhance the retail company's existing supply chain planning process. Prior methods consisted of manual efforts, analyzing sales figures through Excel files and statistical planning of future demands and required resources. Due to this manual approach, human resources and product planning was not optimally predicted resulting in inefficiencies, causing negative impacts to financials.
Implementation of the AI solution to increase efficiency in retail
After analyzing the existing system and its processes, suitable machine learning concepts were selected, implemented and trained with existing data. The data is composed of internal and external regressors that influence demand and forecasting. Internal factors include sales data and product groups, while external factors include weather data or public holidays. The challenge was to also address COVID-19 impacts and extract useful information from it. During the implementation of the system, Circly encountered several efficiency gaps, which were addressed and corrected.
Circly's first aim was to implement consistent data structures and transfer, enabling the models to simplify and optimize sales forecasting. In doing so many manual processes were partially automated, while considering employee concerns. The implementation of a fully automated AI system is a gradual process, as the trust in this technology needs to be gained and the new process logic has to be understood. However, the ultimate goal is to implement a fully automated interface to the existing system. This will optimize resource planning, minimize food waste and workload distribution of personnel through standardized processes.
Results of AI-supported retail optimisation
Environment
1. Reduction of food waste
2. Saving resources due to the ability to plan
3. more sustainable supply chain management
Personnel
1. Use of a more standardised system
2. Efficiency increase
3. Reduction of redundant work processes
Company
1. Avoidance of stock shortages or excess stock
2. Area optimisation for higher sales per metre
3. Saving finances by reducing procurement errors
4. Improving the stability of the supply chain
For further information, please contact contact@circly.at or use our contact form https://www.circly.at/en/contact to book an appointment.
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