Jun 2015
Machine Learning and Dynamic Pricing: The New Game in Retail
How do pricing engines fed by competition, demand and inventory signals balance margin optimization with price perception management in retail?
Etiket
How do pricing engines fed by competition, demand and inventory signals balance margin optimization with price perception management in retail?
The shift from backward-looking reporting to forward-looking forecasting is reshaping management practice. How do you build a predictive planning cycle, and where does it fall short?
Forecasting models that learn from seasonality, promotions and external factors together improve inventory turnover; every percentage point reduction in forecast error translates directly to cash.
Connecting demand forecasting, production orders, and shipment in one data flow is not a technology problem — it is a process design problem most ERP projects get wrong.
How algorithmic pricing based on demand, inventory, and competitor data works, and whether the airline model can realistically extend to other sectors.
Choosing the right scope for a first big data project is decisive for both technical success and organizational trust. Here is a framework for project selection.
Instead of locking into a single plan, MRP II scenario management lets manufacturers prepare optimistic, base, and pessimistic scenarios with defined trigger conditions.
Moving from forecast-based push to demand-driven pull: how data sharing and decision rules help SMEs build a responsive supply chain.
When real demand data is not shared across the supply chain, the bullwhip effect takes hold. Learn how visibility cuts inventory waste.
safety stock policy is not merely a technical choice; it reflects how the organization makes decisions. When process, data, and ownership are unclear, investment creates speed in the short term and complexity in the long term. Real value begins when technology is connected to a business outcome.