Case studies
AI-driven Inventory Management Optimisation
Combining technology and business brings great opportunities and significant challenges. The story we are about to tell is quite recent and comes from a startup we helped during Session 14 of our flagship programme, Pi School of AI. In this article, we’ll illustrate how using AI-driven Inventory Management Optimisation and Predicting Demand improves operational efficiency and creates competitive advantages.
Empowering Inventory Management with AI
Our journey into AI-driven Inventory Management Optimisation for our e-commerce startup partner transcends mere demand forecasting. We devised a solution that enhances the Gross Margin Return on Inventory Investment (GMROII) and meticulously accounts for product-specific discounts and shipping costs. This holistic approach balances profitability with operational expenses. It showcases Pi School’s skilled approach to applying AI to tackle intricate business challenges effectively. In the challenge, we aimed to digitalise the commercial nexus between industries and retailers through a unique platform. The endeavour focused on streamlining retail inventory and simplifying the replenishment process. In 8 weeks, the Pi School of AI Fellows, guided by senior Machine Learning Scientists and mentored by an industry stakeholder, developed advanced Deep Learning and Statistical Models that effectively address these challenges at scale, employing a combination of LSTMs and constrained optimisation algorithms.
The Critical Role of Stakeholder Engagement
Engaging stakeholders is crucial during the Pi School of AI 8-week programme. We believe in transparent progress, showcasing tangible benefits such as improvements in KPIs that include resource optimisation, operational cost reduction, and impact on profit margins and inventory efficiency. Our solution enhanced inventory management efficiency, underscoring the importance of incorporating technology into daily operations.
Embracing an Iterative Development Process
With more than 100 challenges solved, our experience advocates for a highly iterative approach to developing solutions. This includes performing exploratory data analysis and setting up leaderboards with dedicated performance metrics like Root Mean Squared Error and Mean Absolute Error, as well as tracking business KPIs regularly to indicate progress.
Every phase is optimised for utmost accuracy and effectiveness. Using technologies such as ARIMA and LSTM, in tandem with FastAPI for model interaction, reflects our commitment to experimental and adaptive methodologies.
Your success is our success! The Pi School of AI Programme helps companies become well-positioned to exploit AI for operational optimisation and growth.
Our partner’s success underscores AI’s transformative potential in business processes such as AI-driven Inventory Management Optimisation.
We are poised for future advancements, including integrating sophisticated models like Autoformer and applying distributed learning techniques to refine model training efficiency further.
A new session of Pi School of AI will start in Q2 2024. Are you ready to revolutionise your business with AI? Let’s start!