Demand Forecasting
MOTIVATION
Efficiently Generate Scientific Forecasts with Automation
Demand forecasting analyzes historical data to forecast the potential of sales in the pre-determined future. Demand Forecasting helps Automotive companies make crucial business projections for project turnover, profit margins, revenue inflow, expenditure, risk assessment, mitigation scenarios, and capacity planning. AI-powered predictive analytics is used to predict customer demand and operationalize supply chain and business management.
The Problem Canvas
- No Pre-trained Demand Forecasting Model
- Datasets are not suitable, no story will be generated, or functions
will be limited as there are only two columns
The Data Question
- By applying ML to market data, product specifications, and sales trends, you can predict future sales more accurately. This helps to plan better and optimize inventory, production capacity planning & scheduling
Solution Canvas
Approach:
Rubiscape’s demand forecasting leads to effective inventory management and evaluation of proposed holding cost. It helps map uncertainties and looks at how hidden undercurrents in present-day data change the business track at the organizational level in particular and the global level in general. Thus, you can identify all possibilities without making limited predictions.
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Toolset:
RubiStudio – Merging and Joiner, Expression Evaluation, Descriptive Stats, Hypothesis, Code Fusion, Writer
RubiCast – Data exploration, Data preparation, ARIMA, Auto ARIMA, Random walk
Rubisight – Exploratory and Demand Forecasting Dashboard with filters
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Skillset:
Collaboration Platforms
Business Reporting
Machine Learning
Domain Knowledge
Data-driven Problem Solving
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Dataset:
The dataset contains month-on-month car sales data for a period of 9 years.
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OUTCOMES
Business Impact
- Better Bin Planning for Inventory Management, reduction in the shortage of the spare-parts
- Improved after-sales service, and enhanced customer satisfaction
- More visibility on Supply Chain and more control to reduce inventory costs leading to improved cashflows
- Higher precision on capacity expansion planning
- Achieve Incremental Savings and higher-order fulfillment
