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Predictive
Analytics

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Increase demand planning accuracy for increased profit and leaner operations, and reduce risks to boost your competitive advantage.

Our solution offers precise forecasts, integrating multiple demand factors for comprehensive insights. We provide detailed demand projections for every product, store, and channel, enabling effective short and long-term planning.

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Predictive Analytics

Here are a few examples of how we have helped our clients:

Demand
Prediction

Optimize inventory levels, reduce overstocking/understocking costs, increase profitability through supply-demand alignment, with customizable dashboards and alerts for informed decision-making.

New Products or SKUs Recommendation

New Products or SKUs Recommendation

Identify new, high-potential SKUs for each distribution channel, expanding your sales opportunities alongside current offerings.

Optimal Outlet
Location Prediction

Optimal Outlet
Location Prediction

Enable businesses to select sites with the highest potential for sales, customer traffic, and profitability, minimizing investment risk and maximizing returns.

Our Past Success

Product placement and new SKU recommendation
Highlights
  • Implemented within 1 year, achieved payback period of only 4 months.
  • Over “75%” of our recommended new SKUs delivered “over 100% revenue growth”.
  • “31%” of our suggested SKUs have achieved repeating orders.
  • Placing over 10 millions products per week.
Highlights
  • Implemented within 1 year, achieved payback period of only 4 months.
  • Over “75%” of our recommended new SKUs delivered “over 100% revenue growth”.
  • “31%” of our suggested SKUs have achieved repeating orders.
  • Placing over 10 millions products per week.

Use case

Project Background
One of our clients, a consumer product company, places more than 10 million items into over 300,000 sales channels weekly. The challenge is predicting which products to sell at each outlet and in what quantities to manage their supply chain effectively and prevent stockout issues. Additionally, the company aims to boost revenue by expanding the number of SKUs sold at each outlet. We were asked to build a predictive model to address stockout problems and enhance revenue through new SKU recommendations.
Our Approach
Our team employs design thinking to grasp the purchasing needs and behaviors of outlets, ensuring our model truly aligns with their business requirements. We identified that the previous SKU recommendation technology was burdened with excessive factors, causing slow processing and inaccurate results. We delivered an enhanced model that prioritizes crucial internal and external factors, significantly reducing processing time from two days to just four hours, allowing our client to run the model daily. Thanks to its speed and accuracy, we swiftly helped our client improve revenue, and achieved payback within only a few months.
Cooler placement recommendation
Highlights
  • Implemented within 1 year with a 6-month payback period.
  • Reduced data processing time from 2 days to 4 hours.
  • Revenues increased by over 300% compared to the old model.
  • Placing more that 30,000 coolers per year.
Highlights
  • Implemented within 1 year with a 6-month payback period.
  • Reduced data processing time from 2 days to 4 hours.
  • Revenues increased by over 300% compared to the old model.
  • Placing more that 30,000 coolers per year.

Use case

Project Background
A nationwide beverage company is faced with a decision about whether to place their products in the coolers of outlets, such as mom-and-pop shops or restaurants, alongside their competitors’ products, which may reduce visibility, or to invest and install their own coolers. Additionally, they need to decide between using double-door or single-door coolers. We were assigned the task of identifying the optimal locations for both types of coolers to assist them in making well-informed decisions.
Our Approach
We began by conducting a thorough business survey using the design thinking approach to fully grasp our client’s specific requirements. With this deep understanding, our model focuses on important factors, making our analysis precise and highly relevant, thus providing insights that better suit the client’s unique situation. Our method of delving into user needs and combining it with our machine learning expertise significantly enhances accuracy and effectiveness in placing cooler cabinets, ultimately leading to superior results.

Guiding You Towards
AI Solutions for Maximum Impact

Because that’s what we do.

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