If the last few business cycles have taught us anything, it has been the importance of proactively managing inventory levels against the impact of business cycle swings and shifts in consumer demand. Retailers take great care in selecting the right products for the right locations in the right quantities. But once products are on the shelves and selling starts, imbalances can appear. Inventory builds up where it’s not wanted and runs out where there is higher demand.

That’s when pricing goes to work. It’s the key lever for recalibrating inventory to demand once products have hit the shelves. Coordinated pricing action for in-season and clearance season sales individualized to match each product and location’s own demand and inventory drives better results: better sales, better margin, better sell-through.

Especially toward product end-of-life, inventory must be steered to align with coincident consumer demand. Too often, however, pricing decisions throughout the product lifecycle are ill-informed by historical data and/or simplistic rules-based practices. To use pricing as an effective tool to improve inventory management, retailers need a forward-looking tool that anticipates consumer in-season behavior as it’s playing out and one that provides relevant pricing recommendations at a location/product level. In this way, inventory can be proactively managed to minimize possible margin and revenue losses synergistically across the combination of both in-season and clearance.

A SaaS Platform for your Expanding Data Science Team

DMS is a Data Science and Machine Learning (DSML) platform for building and deploying AI models with a single click using its lowcode / no-code interface. DMS shortens the time-to-value for an investment in AI and democratizes the use of data science, bringing value to an ever-larger audience of less technical experts.

The internal team – citizen and expert data scientists alike – can leverage DMS as an open pane AI solution to configure, tune and deploy out-of-the-box or custom-built models in production for targeted Retail and Consumer Products business challenges.

Don’t reinvent the wheel – get a head start from a pre-tested tool base

Pre-built Algorithms and Pipelines - Antuit.ai DMS comes with Retail and Consumer Products focused AI algorithms solving various problems including forecasting, demand planning, assortment, allocation, and replenishment. DMS provides pre-built AI pipelines that can be deployed into production in weeks.

The pipelines available in DMS are tested, implemented, and tuned across multiple customers in Retail and Consumer Products, providing a fit-for-purpose out-of-the-box option. With the research, iteration, and technical scaling needs taken off the internal data science, they can spend more time working with the business to understand the problem, prepare quality data, tune the models, and explain output for adoption.

If the internal team has a pre-built solution that addresses a specific edge case, they can integrate them in DMS.

Last-mile Operational Connectivity - DMS is fully integrated into Antuit.ai’s Inventory Planning suite, providing the ability to operationalize AI insights into day-to-day operations.
  • Leverage award-winning, production-ready models (Retail and Consumer Products)
  • Code if you want!
  • Bring Your OWN Modules (BYOM)
  • Production-ready, high-scale, and high performance
  • Last mile connectivity to Antuit.ai’s Inventory Planning Solutions
  • Citizen data scientists
  • Expert data scientists
  • ML engineers
  • COE’s
Industry focus
  • Industry focus
  • Consumer products
Business problem focus
  • Forecasting
  • Replenishment
  • Assortment
  • Pricing
  • Allocation
  • Store segmentation
  • and more

Our solutions are built upon antuit.ai’s world-class AI Demand Forecasting

Unified Demand Signal

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.

Dynamic Aggregation

An analytic methodology to address data sparsity, avoid the impact of fringe sizes, handle new items, and protect unit minimums.

Omnichannel Profiling

Delivering demand profiles that consider store and online sales independently, but optimize for BOPIS and ship-from-store (SFS) aspects of inventory location.

Seamless Integration

Delivers pricing and forecasting results through API integration, feeding either antuit.ai’s application suite or existing ERP solutions.

Scalable Data

AI models capable of digesting data that accounts for every demand driver - including seasonality, price, product lifecycle, trends, and local events.

Cloud Native

Built natively in the cloud with scalable distributed processing.

Download Solution Sheet (PDF)