Spherecast (YC S24)

Think about selling IPA through your own shop, marketplaces & at all the different retailers 🍺 One day or another you have to produce it. And then also think about how much raw material you need, at what time. -> WHEN is a good time to source barley for my production? This requires you to bring demand per channel, warehouse needs, inventory policy, current raw material levels in one place, intelligently. NetSuite often falls short – no option to look at the future orders in one place, based on different demand planning & warehouse complexities. In Spherecast you’ll get this info, in seconds 👇

Spherecast (YC S24) at Winter Fancy Food Show in Vegas! Looking forward to connecting with brands & manufacturers to talk all things supply chain, inventory optimization AND trying their products at their booths! 😋 Hit me up if you’re going as well!!

𝗝𝗼𝗶𝗻 𝗼𝘂𝗿 𝘄𝗲𝗯𝗶𝗻𝗮𝗿 𝗼𝗻 𝗔𝗜-𝗽𝗼𝘄𝗲𝗿𝗲𝗱 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗲𝗱 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗣𝗹𝗮𝗻𝗻𝗶𝗻𝗴! 🚀 𝗜𝗻𝘀𝗶𝗱𝗲 𝘁𝗵𝗲 𝗦𝘂𝗽𝗽𝗹𝘆 𝗖𝗵𝗮𝗶𝗻 𝗣𝗹𝗮𝘆𝗯𝗼𝗼𝗸 𝗳𝗿𝗼𝗺 𝗕𝗲𝗿𝗻𝗱: Gain exclusive insights into how Bernd scaled enterprise supply chains at Montblanc, a global luxury brand, and built them from the ground up at Mammaly, one of the fastest-growing pet food brands. 🤖 𝗗𝗿𝗶𝘃𝗶𝗻𝗴 𝗦𝘂𝗽𝗽𝗹𝘆 𝗖𝗵𝗮𝗶𝗻 𝗘𝘅𝗰𝗲𝗹𝗹𝗲𝗻𝗰𝗲 𝗧𝗵𝗿𝗼𝘂𝗴𝗵 𝗔𝗜: Say goodbye to messy spreadsheets, email overload, and manual data entry. Discover from Leon how Spherecast leverages AI to revolutionize demand and supply planning, eliminating headaches and preventing stockouts. 🎯 𝗠𝗮𝘀𝘁𝗲𝗿𝗶𝗻𝗴 𝘆𝗼𝘂𝗿 𝗡𝗲𝘁𝗦𝘂𝗶𝘁𝗲 𝗘𝗥𝗣 𝗳𝗼𝗿 𝗦𝘂𝗽𝗽𝗹𝘆 𝗖𝗵𝗮𝗶𝗻 𝗦𝘂𝗰𝗰𝗲𝘀𝘀: NetSuite’s standard modules fall short for demand & supply planning. Learn from Martin, Partner at Alta Via Consulting, how to optimize your NetSuite ERP for effortless integration. 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗻𝗼𝘄! 👉 https://lnkd.in/d_PAZ2Mk

Spherecast is growing 🎉 We are happy to welcome Leon and Felix to Spherecast! Leon joins Spherecast as a Founding Engineer. He studied Computer Science at 16, built machine learning models at appliedAI Initiative GmbH and applied data science methods at Amazon fulfillment centers. Recently coming back from Entrepreneur First, he decided to bring his entrepreneurial tech spirit into his role as a Founding Engineer at Spherecast, growing the product. Felix is joining Spherecast as a Founding Business Developer. He founded the local TechLabs entity in Mannheim and led partnership and GTM efforts to bring tech to everyone. Combined with his entrepreneurial experience at Technische Universität München, his hands-on engineering and tech consulting background make him the perfect match to build the early GTM engine at Spherecast. Excited for the future!

Spherecast is growing 🎉 We are happy to welcome Leon and Felix to Spherecast! Leon joins Spherecast as a Founding Engineer. He studied Computer Science at 16, built machine learning models at appliedAI Initiative GmbH and applied data science methods at Amazon fulfillment centers. Recently coming back from Entrepreneur First, he decided to bring his entrepreneurial tech spirit into his role as a Founding Engineer at Spherecast, growing the product. Felix is joining Spherecast as a Founding Business Developer. He founded the local TechLabs entity in Mannheim and led partnership and GTM efforts to bring tech to everyone. Combined with his entrepreneurial experience at Technische Universität München, his hands-on engineering and tech consulting background make him the perfect match to build the early GTM engine at Spherecast. Excited for the future!

📈 Bottom-up Forecasting in Spherecast Bottom-up forecasts are based on SKU history and its characteristics. Some of these characteristics drawn from the product’s history include: 1) Growth Rate 2) Seasonality 3) Demand Outliers ... and much more! A common challenge is extracting these characteristics automatically from product history and applying them to future projections. Excel sheets often face limitations in this regard, resulting in imprecise forecasts thus bad re-ordering decisions. The Planning feature in Spherecast allows you to: ✅ Select different forecasting methods per SKU & channel ✅ Track forecasting accuracy per SKU and category ✅ Automatically remove demand outliers and approximate stock-outs

📦 Multi-warehouse setups Multi-channel brands do not only have complexities on the sales forecast side of things, but also ask themselves: ⏱️ When should I send-in products from warehouse one to warehouse two? 🔢 What is my ideal reorder based on inventory needs in both warehouses? Find your answers in Spherecast: ✅ Understand the ideal time to replenish products ✅ Receive the ideal re-order & send-in amount per product ✅ Automate send-ins to Amazon FBA

🙌🏻 Marketing events in Spherecast Forecasting sales per SKU is definitely complex, especially when planned events come into play. The key to that is to have precise base forecasts and dynamically adjust them with planned events. Questions for e-com ops teams arise, such as 🔢 How can I integrate my events? 📊 What will my new forecast per SKU be based on my planned events? Check Spherecast 🔮 In Spherecast, you can ✅ Insert an event for every product & every channel ✅ Adjust the expected sales uplift for every event ✅ Manage events in one place

📈 Replenishment Simulator in Spherecast As an ops manager, you often think about your coverage for specific purchase orders. 🔢 For how long does the new PO cover my inventory? ❓How much should I order so that I can cover stock until a specific date? In Spherecast, you now can ✅ Get the ideal order quantity for any date per SKU ✅ Simulate the order quantity for different dates within a PO

📈 Supplier Analytics in Spherecast Operations manager often face the difficulty of analyzing supplier information, including 🔢 What is my actual lead-time based on past purchase orders? 🤝 How reliable are my suppliers? Check Spherecast 🔮 In Spherecast, you can ✅ Track the actual, average lead-time over multiple POs ✅ Get an understanding of revenue per supplier to assess risk ✅ Understand reliability of your suppliers based on timeliness #ecommercelogistics #supplychain #inventoryplanning #purchaseorders