Nowadays, we hear about data science technologies like machine learning and data modelling. But, now new cloud services for machine learning is gaining importance and more do-it-yourself (DIY) tools will emerge for sectors like financial services, healthcare or retail, predictive sales or marketing. Read more at: http://www.business2community.com/b2b-marketing/diy-predictive-modeling-pitfalls-opportunities-01527315#PHERr4OuiDd4QyeJ.97

Optimizing production for manufacturers with complex operations is not an easy task. There can be volatility in costs and prices, managing multiple plants and figuring out the combination of inputs for products are complex operations. These complexities are abundant in the chemical industry. Advanced data modelling and analytical techniques have helped this industry perform better. Data about companies’ performances can be put into a mathematical model which predicts production under different conditions. The resulting model brought sea changes in the companies’ production decisions, increased plants’ EBIT returns and production capacity. This change was not without a side benefit: better cross-unit collaboration and decisions were made with all constraints and trade-offs in mind. Read more at: http://www.mckinsey.com/insights/operations/taming_manufacturing_complexity_with_advanced_analytics