With more than 11 million people unemployed in the US and an estimated global economic cost of $28 trillion, COVID-19 has introduced unprecedented uncertainties into supply chains, making hard work more complicated. Businesses such as retail, manufacturing, food, consumer products, pharmaceuticals, and life sciences struggle to align production and warehousing with rapidly changing purchasing demands.

At the same time, some channels have gotten ahead: online businesses, retailers, delivery services and pharmacies are thriving. However, with such success comes its own set of supply chain complexities.

Nowadays, during these challenging times, retailers and manufacturers must work harder than ever to meet volatility in demand. Also, they need to identify key supply partners that are vulnerable during this disruption and need close coordination between the supply chain and store operations. Regardless of the pandemic, businesses that lack strong and agile forecasting skills face challenges in supply chain management.

The Power Of Machine Learning

Incorporating machine learning into existing business intelligence solutions can significantly improve retailers' and manufacturers' ability to predict future goods demands, even in uncertain and dynamic times. These platforms provide management teams with unprecedented information, enabling them to make more informed decisions in all aspects of supply chain management.

Machine learning enables AI-driven demand forecasting. Using various historical data sources to inform the future demand, retailers and manufacturers have increased availability in several cases by 5 per cent, decreased waste by more than 8 per cent, and reduced losses due to cancellations.

Forecast returns. By predicting how much stock will be returned, retailers can purchase less stock from suppliers, minimizing the risk of excess inventory throughout the supply chain.

Minimize out-of-stock. With better and improved store-by-store, week-by-week, and SKU-by-SKU forecasting, businesses can rely on better granularity to reduce out-of-stock.

Forecast of new products. AI and machine learning-based software can easily predict likely sales in the first weeks and months after selling a new product.

Price optimization. Identify optimal price points influenced by multiple factors, such as item, subcategory, brand, and location, thereby optimizing the alignment of supply and demand constraint or imbalance.
Businesses embracing homegrown AI-based solutions have faced several challenges. Many of them found it challenging to develop effective models and have trouble bringing AI models into production. However, those that add AI-based solutions can quickly accelerate efficiency and improve the bottom line. Fountain9's Kronoscope offers a seamless way to significantly improve business outcomes by simplifying, automating and democratizing AI-driven supply chain management.

A Trillion Dollar Problem

Before the outset of the pandemic, lost revenue due to overstocking or out-of-stock items cost retail and manufacturing businesses more than 1 trillion annually. Moreover, pandemic-driven store closures and supply chain hurdles made this situation worse. To compete in a constantly changing market, it's necessary to offer customers the right product in the right place and at the right time.

When they cannot predict how the market will change and what will be the shopper's habits in the future, retailers and manufacturers struggle to match the inventory with demand.

The Empowered Consumer

Nowadays, consumers are more informed and empowered than ever, expecting to find what they are looking for and buy it as quickly as possible. However, with the increasing prevalence of online shopping, the online customer experience is influencing local retailer experiences. Customers look forward to a seamless and efficient checkout and return process, no matter how or where they shop.

The pressure is on retailers and manufacturers to have an agile supply chain that can quickly adapt to several challenges, including the following:

● Modern consumers have evolving needs and can easily change their behavior patterns quickly in response to seasonality, trends, or other changing circumstances.
● Customers can choose between several channels, such as online and mobile shopping. This trend started before the pandemic and solidified during the pandemic as online shopping became the norm.
● Consumers are shifting toward utilitarian or requirement-based shopping, from local retailers to online merchants. Everyday products like toilet paper and other necessities can be easily purchased and delivered without leaving home.
● Consumers demand accurate information regarding the product availability and delivery times to their homes, and this requires a high level of transparency in the supply chain.
● Customers want personalized options. The supply chain must allow businesses to create "one-of-a-kind" products easily.
● Customers want easy returns, often leading to a reverse supply chain challenge.

AI Applied To Demand Planning

While traditional demand forecasting techniques apply static, predetermined rules to analyze data, AI-powered inventory planning software can easily detect complex interactions and patterns in large batches of data that would be impossible for humans to recognize.

In addition, automated AI-powered inventory planning systems go a step further by updating retail demand forecasts over time, dynamically adjusting to changes in the data collected. This significantly improves the accuracy of demand planning for launches, promotions and markdowns involving products with similar features.

AI-powered inventory planning solutions help businesses tackle one of their most challenging tasks: time series forecasting. Time series is a set of data points indexed, listed, or plotted in time order, and time series forecasting uses models to predict future values based on previously observed values.

About The Company

Fountain9 is one of the best demand planning software providers that assist food businesses and D2C brands to minimize waste and maximize profits while maintaining high availability and predicting future inventory requirements.