A responsive and cost-efficient supply chain requires the right structure. With an evolving demand landscape, competitive service models and uncertain geopolitical trends, the supply chain must constantly innovate to stay relevant and differentiated. Companies with agile supply chains are ready to adapt and respond faster to market changes.
Antuit combines traditional optimization-based network design with advanced financial modeling to develop the best possible recommendations. This approach maximizes ROI on supply chain assets and delivers a higher level of service.
Whether you’re thinking of adding a new plant in a new market, deciding to make or buy a product for the upcoming season or allocating distribution centers to customers in an omnichannel network, our streamlined approach gets you to the answer faster. Optimal supply chain design can reduce network costs by 15%.
The perfect forecast is a myth. Machine learning and other advanced techniques can drastically improve forecast accuracy, but demand variability is here to stay. The utopian scenario, where we know every detail of future demand and don’t need inventory, isn’t possible in the digital age as customer demands now evolve at an incredibly rapid pace.
Satisfying digital customers requires proper inventory buffers. For B2C and B2B businesses alike, you must have the right inventory not just at the right place and right time, but also the right level (component or finished good). If you can achieve that, you’ll boost growth and profitability.
An inventory stocking strategy plays a critical role in managing risk and reducing response times. Antuit’s inventory optimization solution, combined with machine learning-driven segmentation and demand modeling, analyzes end-to-end supply chain dynamics to recommend an optimal stocking strategy. We provide simulation-based validation of inventory levels before deploying to de-risk impacts to the end customer delivery. The simulation capability also acts as a what-if analysis layer, providing the ability to understand the inventory investments required to meet a service level. Additionally, we leverage predictive analytics to determine the risk of slow and obsolete Inventory (SLOB) and avoid continual inventory write-offs.
The results prove the value of our solution. We’ve delivered 15-20% reduction in working capital, with 2-4% improvement to service levels.
Product Flow Optimization
Today's supply chains span the globe. Components and finished goods are manufactured internally as well as sourced from contract manufacturers and suppliers. Products can be stored at supplier warehouses, in the channel or even at customer locations. With the larger number of fulfillment options, products can flow to consumers through many different paths. This increase in complexity makes it harder to manage costs while remaining responsive.
Antuit's product-flow optimization solution leverages data lakes and advanced algorithms for enterprise-wide connected decision-making. The impact of any decision variable on the end-to-end network is easily determined, leading to more confidence in the quality of the risk-return tradeoff.
You can determine what to make as well as when and where to make it; what to store where, and which demands are impacted by supply constraints. The end result is lower cost-to-serve, while maintaining or increasing service levels.
Precision is imperative as you get closer to demand. There’s little room for error. Rules-based manual replenishment decisions can result in poor demand response and increase out-of-stock or excess stock.
Antuit’s AI-powered, demand-driven replenishment optimization solution leverages predictive and prescriptive analytics to ensure optimal stock – at the right place and right time. We generate an accurate forecast at a granular SKU store-level for all your products and optimize order quantity for availability at stores – minimizing excesses and shortages.
Our solution covers all the details while optimizing replenishments – supply chain constraints like lot-sizes and lead-times, and store-specific dynamics like size profiles, storage constraints, daily demand trends, promotions and markdown risk – and generates orders based on machine learning algorithms and real-time data.
Integrated Business Planning
Delivering to customer demand involves balancing often conflicting organizational objectives. Optimally coordinating supply and demand involves bringing manufacturing, distribution, sales, marketing and finance teams together to make decisions that maximize profit and revenue.
Furthermore, your organization’s operational day-to-day decisions must align with strategy, budget, and the tactical plan. Organizations struggle to adopt the month-on-month cadence of IBP, often referred to as sales and operations planning (S&OP), due to lack of data supporting the decision process.
Our solution transforms the organizational S&OP from manual guesswork to a machine learning and descriptive and prescriptive analytics-driven process. We underpin the process with advanced analytics, from forecasting and demand consensus to supply-demand balancing and inventory optimization, and overlay what-if analysis on top. The results? A 15% reduction in cost-to-serve.
Get the right data, tools and analytical models to quickly power data-driven and profitable decisions across your enterprise with results like these: