Alloy product overview
Alloy is a data platform designed to break down silos that separate data, systems, and teams using a unified architecture. The platform is built for sales, marketing, supply chain, and planning.
The Alloy Data Platform facilitates data-driven operations across the organization and aligns execution and planning to consumer demand. It allows consumer goods companies to connect real-time demand data from the point of sale through the supply chain. It integrates, harmonizes, and enriches data from partners and internal systems.
Alloy allows users across the business to analyze and find insights in point-of-sale, forecast, inventory, order, and shipment data from all retailers. It is a single source of truth for supply and demand. By connecting retail data, the platform provides complete visibility from manufacturing to the consumer to support planning and executing decisions.
The platform lets customer-facing teams proactively identify risks and opportunities using retail insights to influence partners’ actions and build trust over time.
Pros of Alloy
- Alloy is purpose-built for consumer goods brands and can analyze sales and inventory at macro and micro levels.
- The platform can take large quantities of data from different sources and make them available in a simple user interface.
Cons of Alloy
- Using Alloy’s export functions is cumbersome for some users.
Breakdown of core features
Alloy utilizes data modeling and AI to create a unified representation of the end-to-end supply chain. The system translates SKU identifiers, units of measure, and other attributes. It can also map locations and location types, shipment lanes, DC inventory targets, and lead times. Brands can understand business performance better by flexibly analyzing data at any time interval and modeling different fiscal calendars, granularities, and forecast versions.
Once data is collected and synchronized, Alloy’s predictive analytics and forecasting engines create forward-looking views of the supply chain so businesses can anticipate stockouts and predict demand. The platform uses machine learning algorithms to keep users ahead of supply-demand imbalances. Brands can prepare and avoid outages or overstocks with forward-looking metrics like Future Weeks of Supply for every item-location combination in the network.
Alloy allows brands to adapt to shifting demand with outside-in forecasting. Demand planners can focus on integrated retail data and built-in forecast models. The platform simplifies tracking forecasts and plans against sell-through, sell-in, and channel inventory in real time, creating a feedback loop between planning and execution. It lets companies forecast more accurately with pre-ingested demand data.
(Last updated on 02/02/2022 by Liz Laurente-Ticong)