Forecasting is one of the most common use cases for machine learning we help customers with at Intellify. Machine Learning is particularly useful for forecasting use cases, and we’ve been able to help customers in a broad range of industries including retail. FMCG, energy, resources, infrastructure and financial services.
Forecasting projects can often involve repetitive work in setting up a machine learning pipeline, selecting the right model, building, training and deploying the model, and then managing the associated infrastructure. AWS’s new service, Amazon Forecast, removes a lot of this heavy lifting and enables customers to unlock the benefits of machine learning faster. Making accurate predictions using better forecasts unlocks many high impact use cases including:
- Retail inventory optimisation
- Workforce allocation optimisation
- Infrastructure utilisation
- Forecasting of revenue and other key business metrics
There’s no easier way to see whether the latest ML forecasting models can make useful predictions for your business than to get them into Amazon Forecast.
Our consultants at Intellify spent a week with the Amazon Forecast team at AWS learning the ins and outs of the service. We’ve developed a simple approach to getting results with this great product fast: bringing the data required onto the AWS platform, transforming it, generating predictions and then most importantly making good decisions in areas like inventory planning and control and corporate financial reporting. We’ve been deploying it with some customers in Australia and they have loved the simplified approach.
If you need help with your forecasting project, drop us a note!