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Hon Hai Technology Group (Foxconn) is the world’s largest electronics manufacturer and technology solutions provider. During the COVID-19 Pandemic, Foxconn faced unprecedented volatility in customer demand, supplies, and capacity. The company collaborated with the Amazon Machine Learning Solutions Lab to develop a demand forecasting model for its factory in Mexico to generate accurate net order forecasts with a simple API call and input data.

“I was very impressed with the world class machine learning team at AWS. My team worked closely with the Amazon Machine Learning Solutions Lab to develop a demand forecast model using Amazon Forecast within a few weeks. Our solution increased our forecasting accuracy by 8%. We project $553K annual savings using this solution for our factory in Mexico. As a bonus, it will be easy to integrate this solution into our cloud workflow once we migrate our data infrastructure to AWS. This collaboration with AWS helped minimize wasted labor costs and maximize customer satisfaction.”

Azim Siddique, Technical Advisor and CoE Architect - Foxconn

More Quality First

More Retail

More Retail is the pioneer in omni-channel Food & Grocery Retail in India and is pursuing its mission to be Indian consumers’ most preferred choice for food and grocery needs. More has 22 hyper markets and 624 super markets across India, supported by a network of 13 distribution centres, 7 fruits and vegetables collection centres and 6 staples processing centres.

“More is the market leader in the ‘Fresh’ category in food and grocery in India. To run a viable business, More needs to simultaneously manage in-stock availability of fresh produce, while minimizing wastage. To balance these competing priorities, More partnered with AWS and Ganit, a data science consulting company, to build and deploy a demand forecasting and automated ordering system built around Amazon Forecast. We needed to build a very granular forecast at store-item-day level, therefore we prioritized the development effort based on ABC-XYZ framework.
The store-item combinations were plotted on a 3x3 matrix: ABC axis of sales saliency (A – high, B-Medium, C-low) and XYZ axis of forecastability (X-easier to forecast, Z-difficult to forecast) based on historical pattern. As expected, forecast accuracy of items in ABC-XY buckets was much superior to the Z bucket. However, for combinations in the Z bucket, Amazon DeepAR+ significantly outperformed traditional methods like exponential smoothing yielding an incremental 10% forecast accuracy. This was possible because of Amazon Forecast’s ability to learn other SKUs (XY) patterns and apply to highly volatile items in the Z bucket.
Using Amazon Forecast, we have been able to increase our forecasting accuracy from 27% to 76% reducing wastage by 20% for the fresh produce category. Amazon Forecast provides a distribution of forecasts which helped us optimize our under and over forecasting costs leading to stock-outs at 3% and improved gross margins. This makes it easier for our store managers to place more accurate purchases orders by looking at the daily forecasts. We are now expanding the model to other categories, iterating with additional related datasets, and adding newer data to Amazon Forecast to continuously improve the model accuracy.”

Supratim Banerjee, Chief Transformation Officer - More Retail

Shivaprasad KT, Founder and CEO - Ganit



Anaplan Inc. is a cloud-native enterprise SaaS company helping global enterprises orchestrate business performance. Leaders across industries rely on our platform to connect teams systems and insights from across their organizations to continuously adapt to change transform how they operate and reinvent value creation. Based in San Francisco Anaplan has over 20 offices globally 175 partners and approximately 1500 customers worldwide. 

“Global enterprises use Anaplan’s cloud-native platform to orchestrate performance through continuous predictive forecasting and agile scenario modeling. With the integration of Amazon Forecast into our platform, our customers across finance, supply chain, sales, and HR can leverage further intelligence through embedded machine learning to create nimble, reliable forecasts. We are proud to deliver Anaplan PlanIQ with Amazon Forecast to help our customers forecast with increased accuracy for intelligence-driven decision-making that gives them a competitive edge.”

Rohit Shrivastava, SVP Product and UX - Anaplan



RetentionX is the plug-and-play analytics solution for any ecommerce store looking to make the best business decisions based on AI-driven data analytics. RetentionX translates your data into clear actions, replacing the power of an entire data science team with just one, easy-to-use tool.

"Our direct-to-consumer customers are looking for quick insights to manage their business operations and drive automated actions. We integrate with any ecommerce system, such as Shopify, and offer more than 100 data science-driven analytics such as demand forecasts, customer lifetime value, churn prediction, cohort analysis, and revenue forecasts. With one click, customers using RetentionX can generate custom machine learning based forecasts on the fly, powered by Amazon Forecast. In addition, customers can easily see insights such as churn prediction and customer lifetime value, which we have built using Amazon SageMaker, and automate marketing activities based on those insights. Our system has been enabled to learn from the data of similar companies, providing unique insights to decision makers. We chose Amazon Forecast for the ease of integration and having the whole architecture at AWS. Amazon Forecast allowed us to scale from 5 to more than 200 individual forecast models in less than a week. As a software-as-a-service solution with hundreds of predictive models, scalability and availability is a must. AWS is the perfect partner for us to ensure this.”

Alexander Jost, CEO - RetentionX



Swiggy is India's largest on demand hyperlocal marketplace with a vision to provide unparalleled convenience across multiple categories (food, groceries) for urban consumers. Headquartered in Bangalore, Swiggy has presence in 500+ cities partnering with over 130K restaurants/stores and operates an on-demand fleet of 200K delivery partners.

“It is critical for us to quickly react to changes in key business metrics which are segmented spatially (e.g. zone within a city) and temporally (e.g time-of-day). For example, if we can predict changes in key business metrics such as cost per delivery, then we can better manage our associated costs and incentives. AWS Forecast allows us to easily use related data that impacts our business metrics to improve forecasting accuracy. Our initial evaluation of Amazon Forecast to predict our business metrics in the hyperlocal logistics domain looks promising and we plan to leverage it to improve our business metric forecasting accuracy."

Vijay Seshadri, Distinguished Engineer - Swiggy

Axiom Telecom

Axiom Telecom

Axiom Telecom is the market leader in telecommunications in Mobile Handset and Technology distribution in the Middle East region with a market share of around 55% and an aspiration to grow above 60%. Today, it distributes telecom products to over 10,000 independent and organized retail customers. The company's operations merge wholesale, retail, value added services, and after-sales of wireless mobile devices such as Nokia, Honor, Sony Ericsson, Motorola, and Samsung. The group has 30 warehouses and a fleet of more than 300 distribution vehicles.

“Amazon Forecast has allowed us to accurately predict sales and deliver better inventory planning. It is a real win not only for us and our business but also for our customers. Prior to using Amazon Forecast, we heavily relied on a combination of statistical models and manual processes to forecast sales and inventory management. This required a significant resource allocation of time and people to maintain these manual forecasts but also left room for error. With Amazon Forecast we have seen over a 20% increase in demonstrated availability and 15% in stock optimization. Furthermore, we have shifted our teams that were doing manual forecasts to now focus on more value added efforts of extracting insights from the new forecasts to help improve our business outcomes.”

Wassim Al Khayat - Group Director of Technology and Innovation



DevFactory is the factory for repetitive, low-value tasks in software development that allow dev teams to focus their precious development resources on delivering value to their products and clients.

“Using AI to improve our own products and operations is core to the fundamental principles of a factory. We’re using Amazon Forecast as a foundational capability in some of our products to more accurately predict sales and be able to deliver better inventory planning as a result. Amazon Forecast gives us the ability to use advanced machine-learning algorithms in our products without having the build and train models manually. This not only makes our products simple to build and maintain, but it also offers our customers greater accuracy, availability, and scalability. This is a real win not only for us but also for our customers.”

Rahul Subramaniam, CEO, DevFactory is one of the largest travel sellers of escorted tours, cruises, river cruises, and active vacations in the United States and we send travelers all around the world on their dream vacation by offering low prices and providing the highest quality customer service with our award winning service team.

“At our customers have a compelling incentive to pick up the phone and call us. We diligently work to offer them low prices on travel packages helping them see and experience new wonders. For our business to thrive and to offer even lower prices we need to find efficiencies everywhere possible. With our global presence we regularly ran into issues having unbalanced resourcing to handle customer call volumes. Some days we had too many agents and other days we had too few which would create inconsistent customer experiences, increased our missed call rates and operating costs. By using Amazon Forecast we are now able to anticipate customer demand call volumes to ensure we have the right number of agents each day improving our missed call rate by approximately 20%."

Marc Rosenthal, Senior Project Manager,



CasaOne offers a one-stop, cost-effective furniture rental/leasing solution with design guidance, seamless project management and a white-glove moving, delivery, and installation experience.

“At CasaOne, we make sure our customers get access to their furniture in a few business days. In order to better predict how many couches CasaOne customers might rent in the Bay Area or how many coffee tables customers might rent in NY, we leverage the capabilities of Amazon Forecast. With Amazon Forecast, our sales prediction accuracy has improved by 20% compared to our existing forecasting algorithm. This means we can stock the right products and save on purchase costs worth a few thousand dollars. Improved product selection will also lead to enhanced customer experience in the long run."

Madhusudan Kagwad, Co-founder and Head of Products - CasaOne 



Heroleads is Southeast Asia's leading performance marketing company who provides clients with an integrated end-to-end solution that is tailored to their marketing needs and maximizes MROI.

“Our media planner team spends over 60% of their time on building and maintaining manual forecast models, supporting the Sales & Operation Team to understand the performance trends of various digital marketing channels and industries and to plan how we achieve KPIs. By integrating Amazon Forecast, we will free up the team to focus on more value-added work, expand the reach of our models to be used by other teams and improve our forecast model accuracy to 99%. Using Forecast increases our ability to better serve our customers and increases the confidence within our team through faster insights, improved predictability, performance alerting systems, dynamic budget planning and more accurate investment models to ensure all our marketing campaign KPIs are met efficiently and at the right time."

Amit Das, Lead Data Engineer - Heroleads



OMOTOR helps businesses improve through AI by providing them with the best of machine learning algorithms, computer vision techniques and cognitive bots that can communicate via WhatsApp and others platforms.

"At OMOTOR, we use AI to innovate on behalf of our customers, so access to the most cutting-edge deep learning technologies from AWS is imperative to our client's success. Using Amazon Forecast gives us the ability to create and refine various forecasts from time series data without having to build and train a model manually every time. We forecast real sales for the next 12 months, so we can adequately plan for inventory, estimate future profitability, track market share gain or loss, and other insights. This means we can use more contextual data, optimize more frequently, generate forecasts with upwards of 50% improvements in accuracy, and operate at a great speed. For example, we're helping customers in the automotive industry predict sales across 185 vehicles in Brazil.”

Marcio Rodrigues, CEO - OMOTOR



OMNYS provides ground-breaking solutions, by designing and building Digital Platforms based on System Integration, Web & Mobile Technologies, IoT, Machine Learning and Big Data. Throughout learning of ultimate technologies, R&D, analysis of market needs OMNYS brings innovation to many industries.

“Amazon Forecast is helping us bring new insights and business value for our client Arneg S.p.A., a global leader in refrigerator manufacturing collecting about 11 million IoT records daily. Using Amazon Forecast, within hours we were able to start building models that would have traditionally taken weeks or months. Our client simply wanted us to extract value from their raw data and with Amazon Forecast we were able to do much more. We built up models to predict energy consumption three days in advance for their refrigerators installed in malls around the world, with a 91% accuracy, and maintenance predictive models to better assess the risk of devices outage, at least up to one day in advance, and consequently reducing the number of emergency calls from their clients. The potential for our client to take these insights to improve how they manage their customer experience is limitless."

Davide Pozza, CTO - OMNYS 

Planalytics, Inc.

Planalytics, Inc.

Planalytics, Inc. is the global leader in Business Weather Intelligence®, delivering comprehensive weather analytics to help organizations make stronger business decisions. Through advanced weather analysis technologies, planning and optimization solutions and industry-specific expertise, Planalytics helps companies accurately assess and measure weather-driven impacts and effectively manage the never-ending variability of weather.

"At Planalytics, we don't take our market leadership position for granted and are always looking for tools and techniques that improve our analyses. Using Amazon Forecast, we are able to quickly and effectively quantify the forecast improvement we bring to our most advanced clients over the use of raw weather data. The quantification has been a game-changer for Planalytics, enabling us to prove real ROI to our customers."

Derron Simon, Chief Operating Officer - Planalytics

Puget Sound Energy

Puget Sound Energy

Puget Sound Energy (PSE) is the state’s largest utility, supporting 1.1 million electric customers and 825,000 natural gas customers in communities in 10 Washington counties.

“At PSE, we’ve used Amazon Forecast to forecast electric and gas consumption at a typical residence. We found that even with a very limited set of historical consumption and weather data, Amazon Forecast performed very well at forecasting 30 days out with virtually no manual effort. With the increased emphasis on environmentally-friendly energy solutions, the ability to produce more accurate energy usage projections at each of our customers’ homes and businesses will be essential for energy service providers like PSE. With these enhanced analytical capabilities, PSE will be able to identify custom energy saving programs and services, ultimately reducing customer bills.” 

Paul Johnson, Sr. Cloud Architect - PSE 

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