Despite artificial intelligence being in development for many years, its integration into daily operations has revolutionized business organizations in the last decade. This is mainly due to three factors.
The high storage capacity of these systems, the abundance of available data, and the processing power of data. These elements allow for the use of highly powerful and effective algorithms, resulting in evaluated outcomes. The system learns and improves future results based on established parameters.
The application of artificial intelligence has an impact on the entire value chain of a company, especially in supply chain management, and significantly improves the decision-making process.
By achieving improvements not only in the physical flow of materials and products but also in the flow of information and money, significant productivity gains are made throughout the chain, resulting in enhanced customer service and reduced of errors.
The supply chain generates data during its activities or processes. These data can be stored and fed back into the system to provide information to AI systems, which will deliver better results in the future.
What is Ai?
Artificial intelligence is defined as the ability of certain systems to emulate human intelligence, incorporating the following competencies: perception, logical reasoning, problem-solving, and planning. These systems are designed to think and learn through tools and algorithms.
With these qualities, these systems are capable of assisting humans in making decisions and executing actions accordingly. In summary, AI imitates intelligent human behavior through computational processes.
Optimizing the supply chain in the retail sector through AI
The logistics and supply chain process is a critical area for retailers due to the large number of operations and resources involved in the process. Therefore, improving operational margins at each link in the supply chain directly impacts business outcomes.
To enhance process efficiency, reduce operational costs, maximize operational margins, and improve service quality, it is essential to optimize inventory and resource planning (human, material, and financial) and automate business processes.
Tools based on advanced analytics and artificial intelligence can more accurately predict future demand, simulate potential scenarios, and recommend the best decision at any given moment.
How to optimize the retail supply chain with AI?
"There are several links in the retail supply chain where measures can be taken to improve efficiency. From the factory to the warehouse, including transportation, storage, and distribution centers, processes can be optimized and decisions automated."
Manufacturing
In the factory, during the manufacturing process, companies have to make complex decisions on a daily basis, such as production volume, given the limitation of resources. Inventory levels and the performance of production and supply lines must always be taken into account.
AI can plan production based on predictive and prescriptive analysis, optimizing this process considering forecasts, inventory levels, production locations, production times and costs, delivery deadlines and costs, etc., to plan production optimally.
Logistics
One of the biggest challenges for distribution operators is to make deliveries in an optimal time and at the lowest cost possible without compromising service quality.
Fluctuating demand, high fuel costs, and low profit margins make resource planning a critical factor in determining the profitability of deliveries.
Optimized planning that takes into account transportation mode, load, and distribution route is essential to increase inbound, outbound, and reverse logistics margins.
Distribution Center
Having a comprehensive view of the process, from order receipt in the warehouse to preparation (picking) and delivery to various destinations, is essential.
Efficient order management, supported by effective warehouse labor planning, can optimize operations at this link of the supply chain.
Predictive analysis and machine learning are helpful for optimizing inventory management. They predict order volumes and lifecycles to ensure optimal service levels at all times.
Retail
Retail is a key component in supply chain planning. Retail activity data can be used to forecast future demand, which affects retail planning and management, as well as manufacturing and logistics.
Various analytical techniques can be utilized to plan and manage different store resources, such as store space, products (inventory management, replenishment), and employees (schedules and tasks).
Optimizing inventory management and replenishment ensures a steady product supply, avoiding sales losses and excess inventory. It is essential for cost reduction and profit maximization, increasing product availability, and improving merchandise distribution in retail.
Effective personnel management is crucial to reducing costs, as labor expenses can account for up to 40% of total retail costs at the end of the month. Frontline staff significantly influence customer purchasing decisions.
Artificial intelligence systems can predict retail visitor volume at any given time, allowing employee schedules and tasks to be tailored to customer visits.
This translates to maintaining the right amount of staff in the right place at the right time to serve customers and increase conversion rates.
The adoption of advanced data analytics-based solutions is unlikely to slow down in the coming years, especially in the retail sector. In fact, over 3/4 of retail companies plan to invest in these technological solutions in the next 3 years.
Optima Retail has consolidated its position as one of the best retail maintenance companies thanks to its commitment to quality, its deep knowledge of the sector, its innovative approach, its comprehensive solutions and its personalized customer service. By choosing Optima Retail, Retail companies not only ensure efficient maintenance, but also ensure a strategic partnership that drives long-term success in a market as dynamic as Retail.