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The importance of forecasting for business management.

Strategic planning is an organic activity for companies that seek growth and differentiation from their competition. It is based on the idea that market and customer needs can be estimated, along with the necessary resources to meet those demands.


This estimation is not done blindly but relies on processing datasets using Machine Learning (ML) tools for predictive analysis related to demand management or financial forecasting, for example.


This estimation practice is commonly known as forecasting. Its implementation has allowed e-commerce giants like Amazon to accurately predict the future demand for millions of products in mere seconds and, even more impressively, fulfill their promise of fast shipping.


While the use of forecasting impacts various areas of the business, such as sales, logistics, finance, and marketing, its implementation in the modern industry is crucial to:

  1. Retail demand planning: Accurate estimation of product and service demand enables efficient inventory management and reliable pricing.

  2. Supply chain planning: Estimating the required quantity of raw materials for manufacturing and other resources ensures uninterrupted operations.

  3. Strategic resource planning: Estimating personnel requirements for operations or resources allocated to advertising, energy consumption, and server capacity.

  4. Operations planning: Estimating web traffic levels, cloud infrastructure usage, IoT sensor utilization, among others.


Where to start?

To implement predictive intelligence in your business, investing in proven machine learning tools such as Amazon Forecast is essential.

This market-leading technology, backed by the quality of AWS, offers a range of algorithms to process different data models and make accurate predictions with just a few clicks.


Its key advantages include:

  • Deeper estimation insights: Amazon Forecast not only provides estimations for a specific variable within a certain time period but also indicates the factors driving that forecast, such as price, holiday season, weather, and more.

  • Pre-configured domains and models: This AWS tool automates complex machine learning tasks by finding the optimal combination of algorithms for a given dataset. With Amazon Forecast, you gain access to pre-configured domains like Retail or Inventory, as well as a wide range of algorithms, from common statistical methods to complex neural networks.

  • Weather pattern detection: By incorporating the Weather Index, Amazon Forecast captures the weather conditions of the past 14 days in enabled locations to evaluate their impact on product demand.

  • Model accuracy metric generation: Unlike other solutions, Amazon Forecast generates point estimates at three different pre-determined quantiles: 10%, 50%, and 90%. Moreover, you can choose any quantile between 1% and 99%, including the "mean" forecast. This flexibility allows you to tailor the estimates to your business needs.

  • Use of any historical data series: Amazon Forecast can utilize any historical data series to create accurate forecasts. Additionally, it can combine them with associated data (such as product features, floor location, and store location) to reveal more intricate insights.



How to successfully implement Amazon Forecast?

To implement Amazon Forecast, you can engage the services of ARKHO.


Our team of engineers holds certifications from Amazon Web Services (AWS), validating their strong competencies and skills in predictive intelligence. Furthermore, their professional experience is backed by over 50 successfully implemented digital transformation projects across various industries.


ARKHO offers an end-to-end consultancy that includes optimizing infrastructure with machine learning (ML) solutions tailored to meet your business demands.


To learn more about ARKHO's proposal, please contact us. comercial@arkho.io


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