Product & Pricing Analytics
About This Course
This course is designed to equip analytics professionals and managers with the skills to understand and implement advanced analytics solutions to help companies improve their mid-long term new product innovation, go-to-market and product portfolio strategies in line with commercial goals. Based on a recent 2018 study by Mckinsey on key value drivers and enablers in product innovation, companies can optimize R&D processes through rapid experimentation and extracting value from connected products and services (for example, deploying sensors and connectivity on consumer products to better understand customer usage, and developing services to generate new revenue streams)
This course will leverage the combined strengths of predictive and prescriptive techniques across disciplines (eg statistics, economics, decision science, machine learning etc) to provide attendees with a practical understanding of Product and Pricing Analytics to derive actionable insights for demand forecasting, commercial excellence and portfolio management.
What You'll Learn
Analytics for Product and Pricing Excellence
� Understand product & pricing sensitivity evaluation for making the �go/no-go� decision at the end of new product development process and estimating post launch adoption
� Apply experimental design methods for concept testing, factor screening, rapid experimentation and optimization for new and connected products
� Apply best practices in product innovation to optimize R&D processes through experimentation and extracting value from connected products and services (eg sensors)
Econometric Modelling and Forecasting
� Understand basic economic concepts including demand function estimation, elasticity measurement, pricing models and optimization to inform product and pricing decisions
� Apply econometric modelling techniques to understand the short vs long term demand drivers and elasticity impacts for demand forecasting and resource allocation
� Apply techniques for new product forecasting and implement resource budget allocation and prioritization across new vs existing products for portfolio planning
Decision Science and Optimization
� Overview of prescriptive analytics using various decision science optimization techniques
� Understand the optimization challenges in handling product and service from price and cost perspective and apply relevant techniques to perform product & price optimization
� Apply the strategy and method to plan and manage inventory at the optimal level
Entry Requirements
Please see course weblink for more information