SMART Demand Forecast: 6-12 months implementation

SMART business LLC

We provide 6-12 months of implementation the system which improves operational planning that is based on Azure

SMART Decision HUB| Demand Forecast

Demand forecast system based on ML & AI algorithms. Improves operational planning in a changing environment and allows you to ensure that the business has optimal stock on time, maximize profits and service levels at low cost. The system contains 3 pages:

● Analytical page

Designed for sales retrospectives analysis, quality of promo sets involved in forecasting, and compensated sales.

● Modelling page

The Modelling block is designed to start/restart the model training process, save and export forecast results, and administer promotional campaigns.

● Analog processing page


Allows to check for products/stores that do not have enough actual sales data for further forecasting by machine learning and artificial intelligence algorithms. In this block, it is possible to analyze the list of proposed analogs of products / stores and choose the relevant one as a benchmark.

Why choose Demand Forecast?

✔️ Increased quality of forecasting

● An integrated approach to forecasting both promotional and regular sales.

● Short-term forecasting with SKU/Store/Day (Week) level drill-down.

● Adaptation to changing sales patterns.

● Advanced technologies and approaches are used to build forecasts based on artificial intelligence and machine learning.

✔️ Taking into account the optimal set of factors for forecasting:

● Price

● Cannibalization

● Seasonality

● Trends

● Promo

✔️ Forecasting sales of products with insufficient history

● Automatic generation of a list of proposed analogs.

● Possibility of manual adjustment of analogs by the user in the interface.

● Generating a forecast based on the history of a product/store analog.

✔️ Increased transparency and business processes efficiency

● Providing analytics at all levels of granulation.

● Drill-down reports to analyze the quality of the forecast.

● Simultaneous access to analytics for cross-functional teams.

Solution value

✔️ Accurate forecasts

✔️ Reducing the workload of teams

✔️ Ensuring high availability

✔️ Reducing stock

✔️ Reducing write-offs

✔️ Increasing the service level

✔️ Powerful analytics

✔️ Making informed decisions

Payment model:

✔️ Project Scope and budget will vary and depend on functional and non-functional requirements

Supported languages: Ukrainian / English / Russian

The Demand Forecast architecture based on modern cloud-based components and services.

✔️ Scalable and effective Azure Data Bricks for model training and forecast modelling.

✔️ Flexible and customizable Azure Data Factory for business process orchestration and effective data transformation.

✔️ Cost-effective storage, such as Azure Storage.

✔️ Scalable and productive integration and computing components, such as Service Bus, Event Grid and Azure Web Application.

✔️ Fully customizable Power BI reporting service natively integrated into the web application.

✔️ Demand planner portal based on the latest rich UI framework with appealing design.

https://store-images.s-microsoft.com/image/apps.54264.c68d9210-c416-43d9-a1fc-8aefd77a71df.450da6c8-0624-4d01-b164-6a04a5400a34.7d40c5f5-63cd-47b4-b868-03c3c6c8b2a5
https://store-images.s-microsoft.com/image/apps.54264.c68d9210-c416-43d9-a1fc-8aefd77a71df.450da6c8-0624-4d01-b164-6a04a5400a34.7d40c5f5-63cd-47b4-b868-03c3c6c8b2a5
https://store-images.s-microsoft.com/image/apps.36803.c68d9210-c416-43d9-a1fc-8aefd77a71df.450da6c8-0624-4d01-b164-6a04a5400a34.84e85695-29f7-4374-9361-b58a9ee190e0
https://store-images.s-microsoft.com/image/apps.34108.c68d9210-c416-43d9-a1fc-8aefd77a71df.450da6c8-0624-4d01-b164-6a04a5400a34.8fe27e5c-2251-403f-8ac1-fe49b64b3068
https://store-images.s-microsoft.com/image/apps.50656.c68d9210-c416-43d9-a1fc-8aefd77a71df.450da6c8-0624-4d01-b164-6a04a5400a34.37def5b6-2560-49f5-a057-cf553f1fdb12
https://store-images.s-microsoft.com/image/apps.59432.c68d9210-c416-43d9-a1fc-8aefd77a71df.450da6c8-0624-4d01-b164-6a04a5400a34.39b9ce1f-47cd-4528-8164-abcc681e3058