AI insights and solutions to enhance cosmetics supply chains
With increasing product complexity, shifting consumer demands, and evolving regulatory landscapes, cosmetics and personal care product manufacturers and suppliers must navigate a host of challenges to stay competitive and optimize supply chains. To shed light on these issues and explore advanced solutions, CosmeticsDesign spoke with Inna Kuznetsova, CEO of ToolsGroup, a leading firm in supply chain planning and optimization.
With over 30 years of experience and a global clientele that includes major beauty brands, Kuznetsova offers valuable insights into how AI-driven technologies are transforming supply chain management, including the current hurdles faced by the industry and how innovative approaches can help improve efficiency and service levels.
CDU: Can you share a bit about your background and experience in supply chain management, particularly within the cosmetics industry?
Inna Kuznetsova (IK): I’m the CEO of ToolsGroup, a leader in supply chain and retail planning with over 30 years of experience of using AI to optimize supply chain, and hundreds of customers in over 40 countries. We see our mission in making the supply chain a force for good, helping companies reduce inventory, improve customer satisfaction, and deliver powerful financial results amid increasing complexity, product proliferation, and uncertainty.
Besides Belcorp we have many personal care, cosmetic and luxury brands as our customers, including Boggi, Kiko Milano, Miroglio Fashion and Karl Lagerfeld.
CDU: What are the most significant supply chain challenges faced by cosmetics and personal care product manufacturers today?
IK: The cosmetics and personal care industry faces a unique set of supply chain challenges that require manufacturers to adapt and innovate.
- Demand Volatility and Seasonality - Consumer demand fluctuates due to trends, promotions, and seasonal factors. For instance, consider the impact of social media trends on product popularity. A single viral TikTok video featuring a particular lipstick shade can cause demand to skyrocket overnight, leaving manufacturers scrambling to ramp up production. Seasonal variations add another layer of complexity, e.g. sunscreen peaks in summer while holiday-themed gifts surge around winter holidays. The brands lifecycle has decreased, and a large number of new launches presents complexity in forecasting demand.
- High shipping costs and political uncertainty. The Red Sea situation forces the ships to sail around Africa adding 2 weeks to the delivery time from Asia to Europe; the ports strikes and even inclement weather in Africa add to delays and the share of shipping costs in the price tag. In addition, the dynamic global political environment impacts retail in this election year. Thus, we just saw luxury brands being affected by the anticipation of higher taxes due to the French election results, and spending patterns in the U.S. start to weigh in the results of the U.S. election. Cash conservation results in putting many strategic initiatives on the back burner, narrowing the focus on projects with fast return on investment (ROI).
- Product Safety, Sustainability, and Ethical Sourcing - The cosmetics and personal care industry is subject to increasingly stringent regulations regarding product safety and ingredient transparency. This necessitates robust quality control measures throughout the supply chain, from raw material sourcing to final product distribution. Moreover, the growing demand for sustainable products is pushing the industry towards using recyclable or biodegradable packaging materials, different sourcing and water conservation in manufacturing processes. It often leads to significant changes to existing supply chains.
CDU: How do advanced approaches such as AI-driven technology help improve service levels and optimize inventory in the cosmetics industry?
IK:AI-driven technologies can significantly improve service levels and inventory optimization in the cosmetics industry in several ways. First, Demand Forecasting, where AI can analyze historical sales data, market trends, social media sentiment, and other factors to more accurately predict demand for different products, and stock appropriate inventory levels.
Second, Dynamic pricing with AI can adjust prices in real-time on a granular level based on demand, competitor pricing, and inventory levels to maximize sales and profitability. The AI-driven approach helps beauty companies optimize logistics, maintain optimal inventory levels, to reduce cost and improve efficiency and overall service levels to customers.
CDU: How does AI-based probabilistic forecasting work, and how does it help in managing inventory levels and avoiding stockouts?
IK: Probabilistic forecasting with inventory planning leverages advanced algorithms and statistical techniques to capture the inherent variability in demand, lead times, and other crucial factors. By embracing uncertainty, businesses can make smarter decisions that optimize inventory levels, improve customer service, and reduce costs, all while reducing stockouts and improving service levels.
CDU: How does AI-based probabilistic forecasting anticipate and capitalize on market changes in the cosmetics industry?
IK:AI-driven probabilistic forecasting combines external causal data with historical and demand relevant internal data to provide planners with a more nuanced understanding of demand patterns. This allows businesses to make intelligent decisions quickly, calibrate their forecasts to achieve maximum accuracy, and ensure a consistent, positive customer experience.
CDU: Can you elaborate on how ToolsGroup’s solutions specifically address cosmetic and personal care product supply chain challenges?
IK: ToolsGroup is a pioneer in probabilistic forecasting methods. AI-based probabilistic forecasting works by analyzing historical data, considering seasonality, trends, and other patterns, to generate probability distributions.
Instead of a single point forecast, the algorithms produce a range of possible outcomes with associated probabilities. It incorporates external factors such as economic indicators, weather, marketing campaigns, and competitive actions. Advanced machine learning algorithms are trained on this data, continuously learning and adapting so that the system updates its predictions based on new data and outcomes.
This approach helps manage inventory and avoid stockouts by providing more accurate demand forecasting, allowing for better inventory planning, quantifying uncertainty, enabling more informed decision-making about safety stock levels, adapting quickly to changing market conditions or unexpected events. It allows the system to identify potential stockout risks early to set proactive measures and optimize inventory across multiple products and locations simultaneously.
Probabilistic forecasting can also anticipate and capitalize on market changes through trend detection such as social media or other data sources to identify emerging beauty trends early, or seasonal variations, and adjust forecasts accordingly. It’s also possible to forecast the demand for new products without sales history, predict impact of events such as fashion weeks, celebrity endorsements, viral social media content, or changes in consumer preferences that might affect demand.
The capability of planning different scenarios allows organizations to be prepared for potential changes. Rapid response is one plus, because as market changes occur, our AI engines can quickly update forecasts and recommendations for inventory and pricing adjustments. The resulting visibility between inventory, marketing, and product development strategies leads to a better alignment of supply with demand, reducing waste, capitalizing on opportunities, and improving financial performance.
CDU: How does ToolsGroup help companies in optimally sourcing materials for production and defining the amount of each product needed at different points in the supply chain?
IK: Understanding the demand forecast, including seasonality of products and stores, along with their respective probabilities allows planners to better plan and match supply to that demand. Planners can then optimize their inventory across their global manufacturing and distribution network, to drive targeted services and inventory levels.
CDU: What methods do you recommend for mapping constraints such as inventory availability from suppliers and production capacities?
IK: Including constraints in supply chain planning is key to providing a truly optimized plan with the best strategic outcomes – service levels, inventory and production plans, supplier purchases, etc. ToolsGroup’s supply chain solutions include those and many more constraints into our solutions.
CDU: When introducing new products into a cosmetics lineup, what strategies should be employed to ensure the right quantity is produced and stocked?
IK: New product introductions (NPI) are critical to any company’s success, but many of them never become household names. In fact, it’s estimated that up to 80 percent of new product launches in the consumer packaged goods (CPG) industry fail. Adding to this already uphill battle, we don’t have trustworthy new product forecasting methods because forecasting new products with no sales data is very hit-and-miss.
However, machine learning (ML) provides an effective weapon for your new product forecasting arsenal. ToolsGroup’s solution employ machine learning techniques that can produce fully-automated forecasts for new products.
CDU: How can AI assist in making these decisions more accurate?
IK: AI enhances decision-making by analyzing data, reducing biases, and adapting to real-time changes, ultimately leading to more accurate decisions and therefore better outcomes.
CDU: How do you think advancements in AI and other technologies will continue to shape the industry?
IK: Artificial Intelligence (AI) remains a focal point in supply chain discussions. However, the excitement surrounding AI has led to fatigue and skepticism among supply chain professionals. Despite its potential, overemphasis on AI has caused confusion about its practical value.
Many companies struggle to articulate the specific AI technologies they use, leading to a lack of trust. Companies don’t want to hear the hype, they want to see real use cases, with real customer successes, that are delivering proven business value. This was a key topic at the recent Gartner Supply Chain Symposium and you can read more about it here.
CDU: What is ToolsGroup’s vision for the future of supply chain management in the cosmetics industry?
IK: We help the industry to move from the static to dynamic planning as a steppingstone to assisted Navigation where several AI engines optimize different parts of the process under the same user interface (UI) empowered by real time data from a digital twin. Ultimately, our portfolio helps customers to achieve the desired state of automation based on internal and external data freeing up humans for exceptions and strategic decisions.
CDU: What advice would you give to cosmetics and personal care product manufacturers looking to improve their supply chain processes?
IK: Companies that have a digital supply chain that is designed around antifragile supply chain concepts as noted above, will be the companies that not only survive, but thrive in today’s fluid and dynamic environment.
