Demand forecasting is a critical aspect of supply chain management that predicts future demand for a product or service. Accurate demand forecasting helps organizations to optimize their inventory levels, improve production planning, and ensure organization’s satisfaction by avoiding stockouts or overstocking.
However, demand planning can be challenging due to various factors, such as seasonality, changing customer preferences, and unforeseen events like pandemics or war. One of the biggest challenges of demand planning is the accuracy of the forecast. If the forecast is inaccurate, it can lead to overstocking or stockouts, both of which can be costly for businesses.
To overcome these challenges organizations must adopt an integrated approach combining data analytics, and market intelligence. By leveraging advanced forecasting techniques such as Machine Learning companies can gain deeper insights into customer behaviour and market trends, and make more informed decisions about production, inventory, and pricing.
Coral Innovations, responsible for the replenishment of non-fuel goods at the retail stations in Greece, under the brands SHELL and AVIN, asked WITSIDE for a solution that would:
>Enhance operations’ efficiency by reducing excess inventory and preventing stockouts
>Increase forecast accuracy to help make more informed decisions
>Automate preparation of purchase orders to suppliers
>Integrate with the company’s ERP and other legacy applications
>Provide insights on trends and correlations between products that cannot be tracked manually
Coral Innovations manages a large-scale supplier channel consisting of more than 100 suppliers working regularly and can place an order anytime (24/7/365) via the online portal products which include 1800 active SKUs. During the last year, the company served more than 16000 orders, thus increasing warehouse activities (pickups, etc.) by up to 80% compared to last year. Moreover, the size of the consumer basket increased by 50%, and the SKU store deliveries went up to 65%, implying a significant year-over-year development for Coral.
To address those challenges, WITSIDE leveraged a global leader in Sales & Ops Planning (Forecast Pro) as well as one of the most well-known Data-Driven Transformation Platforms, Alteryx. The objective was to enable frequent data updates, seamless communication between systems and constant collaboration between S&OP users. By combining machine learning, advanced time series forecasting and regression analysis WITSIDE processed hundreds of SKUs, promotional activities and critical calendar events (such as new product or store launches, the pandemic, etc.) to accurately forecast demand. Then, additional business rules were embedded (such as order fulfilment lead times, procurement policies, etc.) to automate the transformation of those forecasts into Purchase Orders and their submission to each vendor!
“After adopting the demand planning and forecasting solution, our operations have witnessed a remarkable increase in efficiency, coupled with a significant reduction in excess inventory and zero stockouts. The improved forecast accuracy has empowered us to make well-informed decisions, leading to a noticeable improvement in profitability”.
Stella Fine, Operations & Logistics Executive at Coral Innovations
Upon the launch of this new S&OP solution, Coral has already reported the following benefits:
>Forecast Improvement in all SKUs
By combining machine learning, advanced time series forecasting and regression analysis to analyze historical data and market trends, Coral can forecast future demand more accurately, reducing the risk of overstocking or stockouts.
Accurate forecasting allows the company to meet customer demand more effectively, resulting in increased sales and revenue.
>Reduced Costs & Risks
With better inventory management and optimization Coral can reduce costs associated with inventory & stockouts and mitigate the associated risks.
>Better collaboration & internal communication between the company’s departments:
The solution facilitates collaboration between Supply Chain, Sales and Marketing teams allowing for better information sharing and coordination.
>Time efficiency and decision effectiveness
Faster and automated data processing saves more than 25% of the effort in S&OP tasks (compared to the existing process). This saving allows for transitioning focus to more critical tasks and data-driven decision making.
The new S&OP process can be adjusted to support Coral’s development in terms of new product launches, new store openings or relocation, increase in product portfolio, new partnerships/vendors, increased warehouse activity and deliveries, etc.