Antuit.ai’s Demand Planning solution revolutionizes the demand planning process. With the world’s best forecast and AI embedded seamlessly into the UI, the solution expedites collaboration, decision making, and troubleshooting via AI-driven recommendations that take care of the “no-touch” and “low-touch” areas and AI-driven alerts that surface the anomalies requiring “high-touch” review. Demand Planning delivers this exception-driven efficiency for CPG planners through a resolution-management UI, powered by visualizations, rapid drill down, tagging and easy overriding for when the plan and forecast are at statistically significant odds
As a result, planners are able to work at scale across tens of thousands of existing and new categories, reducing their cycle time while fostering consensus with retail customers, independent distribution partners, and within the rest of their own organization. Demand Planning supports every stage of the Planning Cycle - from Pre-Cycle forecast validation and outlier correction - to In-Cycle demand driver analysis, simulations and scenario analysis, overrides and plan approval - to Post-Cycle deep-dive analysis and performance review. With antuit.ai Demand Planning, planners will feel palpable workload relief thanks to increased operational efficiencies and will have room for more challenging tasks thanks to the productivity gains.
Demand Planning from antuit.ai is a powerful workflow solution delivering:
Planning Workbook – Easily navigate a multidimensional view of all configurable measures and key figures with the ability to conduct root-cause analysis.
Demand Driver Analysis – Take control with a multi-dimensional, time series view of demand and all drivers with a user interface that accommodate planner adjustments, including the ability to edit driver demand, introduce new driver events like holidays and promotions, automate the disaggregation of edits made at higher levels of aggregation and lock values where appropriate.
Alerts-based Workflow – Manage the demand plan by focusing on exceptions and outliers triggered by unplanned events or external conditions, leaving every-day demand to the AI forecast.
Analysis and Collaboration Toolset – Leverage intuitive tools to drill through the product hierarchy, edit aggregation hierarchies, and graphically view and analyze performance ratios and overrides while easily adding comments and annotations.
Further improve the ability to pinpoint customer demand and improve customer relationships with the ability to simulate the outcomes of different “what-if” strategies that can consider all the critical demand drivers while leveraging AI generated price and event elasticities. Users can create scenarios at different levels of the product hierarchy, enjoying the flexibility to test national promotions or account-level events, and then promote a different plan based on a preferred scenario to override the current one. An advanced user interface simplifies the comparison of different scenarios via graphs and tables.
For one multibillion-dollar global health technology leader with online channels growing to over 40% of revenue growth and expected to double in the next five years, it was increasingly important for their planners to have an integrated, omnichannel view of planning metrics across the entire planning lifecycle. What was needed was an intuitive tool which gave demand planners a wide variety of metrics and data visualization to assist with model output interpretation and adoption, but with controls that could be applied on a channel-specific basis.next week will be four units”.
For a multibillion-dollar consumer electronics company committed to delivering immersive entertainment and compelling lifestyle enhancements for the connected home, the goals were to both improve forecasting in a way that would differentiate the impacts of seasonality versus pricing events, and, at the same time, alleviate manual and time-consuming efforts to apply the impacts of past events to future planning. Rapid Scenario Analysis allowed for the ability to test the impact of pricing and events at a national or local level.
Control for the differences between regions, stores, online, and even the fulfillment type, and serve as the connective tissue across financial, assortment, allocation, size, and pricing decisions.
An analytic methodology to address data sparsity, avoid the impact of fringe sizes, handle new items, and protect unit minimums.
Delivering demand profiles that consider store and online sales independently, but optimize for BOPIS and ship-from-store (SFS) aspects of inventory location.
Delivers pricing and forecasting results through API integration, feeding either antuit.ai’s application suite or existing ERP solutions.
AI models capable of digesting data that accounts for every demand driver - including seasonality, price, product lifecycle, trends, and local events.
Built natively in the cloud with scalable distributed processing.