11 Dec CHALLENGES IN INVENTORY FINANCING
Today’s consumers want their products delivered within a matter of hours or days at most. As a result, efficient supply chains are structured in a way that physical inventories have to be within reasonable transportation time of the consumer. Often times, depending on the product, items are left unsold for which the inventory owner incurs costs. For larger companies, these costs have a smaller impact than for SMEs, as larger companies can afford better inventory management systems and have easier access to external financing.
Because holding excess inventory ties up working capital, companies often seek to finance a part of their goods in stock. The financing amount is based on the value of the stock, the risk involved in keeping the goods in storage and the predicted amount to be sold. As already mentioned before, larger companies have an advantage over smaller companies due to less inventory risk involved, more mature IT systems and (automated) access to more trustworthy information on the state of current inventory, better predictable moment of goods being sold, better relations with buyers, leading to less risk. For smaller companies, inventory management data can be less trustworthy, inventory financing often requires manual intervention and it offers no room for scalability or automation. As a result, billions in worth of inventory is tied up and restricts companies’ working capital.
Historic to Predictive
At this moment, too much focus is laid upon historical events and the benefits offered by big data aren’t realized yet. Willingness to share data is low for insurers, banks and logistics service providers, while the impact of data becomes increasingly beneficial if data originating from multiple sources is combined. Due to the largely unconsolidated market and a general lack of information system skills, involved parties are too hesitant to share data. Therefore, the logistics market requires a shift in attitude, where long-term overall benefits are pursued instead of short-term self-interest.
To initiate a shift towards a supply chain based on future predictions, as opposed to historical events, data needs to be consolidated. This way, meaningful insights can be derived, risks can proactively be traced and reduced, consequently benefitting the whole supply chain. A number of companies are paving the way. To give you an example, logistics insurer TVM analyses truck driver behaviour, logistics provider Mainfreight combines data sources to predict accidents, and insurer Achmea applies data from weather forecasts to prevent major insurance claims. The logistics industry is slowly starting to realize the benefits of data-sharing and analysis, which offers a lot of potential for the entire supply chain.
Logistics & FinTech Challenges Event
This Wednesday, December the 13th, HollandFinTech & Dinalog are hosting an event in which a Nedcargo will share its challenges concerning data sharing for transport companies. Rabobank and software company Exact will pitch their solutions to the challenge, making the session insightful and educational. Feel free to join and sign up here!