In our previous blogs, we discussed the transformative capabilities of AI in demand forecasting and planning for the retail and CPG industries, as well as the data science and ethical considerations behind it. Now, in this final installment of our series, we'll explore how businesses can maximize their margins by integrating, adopting, and executing AI-powered solutions.
Benefits of AI in Demand Forecasting and Inventory Planning
As Forbes points out, AI has the potential to benefit demand forecasting and inventory planning in five ways:
- Improved accuracy. AI can analyze vast amounts of data to identify patterns and predict future demand more accurately than traditional methods.
- Faster analysis. AI can process data more quickly than humans, enabling businesses to make decisions in real-time.
- More comprehensive analysis. AI can analyze multiple data sources simultaneously, including structured and unstructured data, to provide a more complete view of demand and inventory.
- Reduced human error and bias. By automating mundane tasks, AI not only minimizes the risk of data entry errors but also mitigates individual biases that can skew product demand predictions, instead providing a balanced perspective based on objective data and actual demand trends.
- Cost-effectiveness and improved revenue. AI-optimized inventory effectively works on two fronts: it lowers inventory costs by curtailing the risk of excess stock and boosts potential revenue by reducing the chance of lost sales, thereby circumventing the ironic predicament businesses often face of simultaneous out-of-stock and surplus inventory scenarios.
Three Keys to Making AI Work for You
To fully realize the benefits of AI, businesses need to ensure they have the right integration, adoption, and execution strategies in place.
Integration. AI systems need to be integrated with existing systems and data sources to ensure seamless data flow and enable accurate predictions. This may involve developing APIs and other integration tools to connect disparate systems.
Adoption. To ensure successful adoption of AI systems, businesses need to educate their employees on how to use them effectively. This may involve providing training and support to help employees understand how AI can benefit their workflows and improve their decision-making processes.
Execution. Successful execution of AI systems requires ongoing monitoring and fine-tuning to ensure optimal performance. Businesses must be prepared to continuously evaluate their AI systems and adjust as necessary to ensure accurate predictions and maximize margins.
Perceived Business Concerns with AI Adoption
Despite the potential benefits of AI, some businesses may be hesitant to adopt these technologies due to perceived concerns, such as fear of job loss, privacy concerns, and uncertainty about the reliability of AI predictions.
One common fear among employees is that AI will replace their jobs. However, research shows that while AI may automate certain tasks, it is unlikely to replace entire jobs. According to a study by the World Economic Forum (WEF), while AI is expected to displace some jobs, it is also expected to create new jobs and transform existing ones. The WEF's Future of Jobs Report states that by 2025, AI and automation will lead to a net increase of 12 million jobs globally. Rather than replacing humans, AI is expected to augment human capabilities and improve productivity, allowing employees to focus on higher-level tasks that require creativity and critical thinking.
Business leaders can assuage these fears by providing employees with the necessary training and support to effectively integrate AI into their workflows. By involving employees in the AI adoption process and demonstrating the benefits of these technologies, businesses can help employees feel more comfortable with AI and view it as a tool that can enhance their work rather than a threat to their job security.
Another concern with AI adoption is privacy. As AI systems analyze vast amounts of data, businesses must ensure that they are protecting customer and employee privacy. This may involve developing strong data security policies and protocols and obtaining the necessary consent from customers and employees for data collection and use.
Finally, businesses may be hesitant to adopt AI due to uncertainty about the reliability of AI predictions. However, as noted earlier, AI has been shown to provide more accurate predictions than traditional methods, particularly when analyzing large datasets. By carefully selecting AI models and continuously monitoring their performance, businesses can ensure the accuracy and reliability of their AI predictions.
Case Studies of AI Use in Retail and CPG Sectors
To illustrate the benefits of AI in retail and CPG, let's look at a few case studies:
Intelligent Order Promising - During the COVID pandemic, a multi-billion-dollar consumer goods company was required to react and adjust more quickly to inventory planning and order fulfillment to counteract skyrocketing consumer demand for food and consumable products. To optimize business performance in these market conditions, this global company launched a strategy focusing on a competitive advantage by investing in data and analytics. One critical area that promised significant business benefits was Order Processing and Available-to-Promise (ATP). The system helped them achieve a 4-5% improvement in case fill rate for strategic customers, and 10x ROI (Return on Investment) from increased revenue and reduced OTIF penalties.
Demand Forecasting - PacSun, a leading retailer of California lifestyle clothing, used AI-powered demand forecasting for Allocation and Fulfillment, to improve inventory accuracy and reduce stockouts. The system helped the company double their ship completes, forecasted and allocated omnichannel demand, and balanced inventory between stores, DC, and web-depot locations for in-store and online sales.
“Antuit.ai’s solutions and expertise ensure we have the right inventory in the right stores, which significantly improves our ship completes.”
Shirley Gao, CIO PacSun
These highlights among our antuit.ai case studies illustrate how AI can drive significant improvements in demand forecasting, inventory management, and overall profitability for retail and CPG businesses.
Improve Retail and CPG Margins
AI offers the potential to revolutionize the retail and CPG industries by optimizing demand forecasting, inventory planning, and pricing and promotions. However, businesses must ensure they have the right integration, adoption, and execution strategies in place to fully realize the benefits of AI. By addressing perceived concerns, involving employees in the adoption process, and showcasing successful case studies, businesses can overcome barriers and unlock the full potential of AI to maximize their margins and gain a competitive edge in the market.
Thanks for reading our three-part series. If you would like to learn more about the power of AI for your business, contact us.