MANUFACTURING TIDBITS
Automating Pricing Strategies in Q3/Q4 2020 by T.R. CUTLER
Shockingly, many Fortune 500 companies are still using spreadsheets and manual data collection. Such antiquated processes prevent the required price alignment and robust management of pricing strategies. Researching the perceived barriers to price alignment automation, most industrial business decision-makers feared an extensive implementation time, complexity, and significant costs. New solutions overcome those concerns offering an automated pricing alignment technology which can be implemented cost-effectively in just weeks. Delivering significant improvements in revenue and margin by providing a clear, guided user experience (via insightful dashboards and comprehensive pricing science) means hundreds of manufacturing companies in Q3 and Q4 2020 will ensure pricing execution remains aligned with strategic objectives. In fairness there a several expensive solutions on the market, well into six figures, which promised the automation, yet became as cumbersome as legacy ERP installations and maintenance challenges. The notion of price alignment is not new The way these new automation solutions have been adapted and adjusted promotes the ease of setting and managing pricing boundaries in context of all variables. Price alignment was designed to alleviate the pain for any manufacturing organization using simple rules or trial-and-error methods to derive prices; this is especially true if corporate objectives include rapidly and repeatedly adjusting and maintaining prices at the most granular level. Automation must start with easy integration to source systems followed by seamless population of
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Manufacturing Outlook / July 2020
transactional systems with optimized prices. With those processes in place price alignment enables complex pricing logic automation. Manufacturing pricing experts Pricing experts, Dallas Crawford and Dan Barrett were asked to elaborate how manufacturers should analyze pricing needs using data analytics. Crawford insisted that price aligning with data analytics can be done readily in real-time. The ability to concentrate on high and low volumes that fall outside a normal distribution of trend or seasonality can inform where margin opportunities exist. This is particularly valuable during the pandemic where buying patterns are in greater flux. Higher volume provides opportunities to adjust prices based on demand or to capture market share. Lower volume provides opportunities to analyze pricing, determining if market share is being lost or if the product’s lifecycle is near its end. Barrett noted the best method to analyze and optimize customer pricing is to model the data and ensure that the analytics platform supports it at a very discrete level. Customer data by location or product SKUs allow for optimal delivery of unique pricing. Understanding and forecasting the customers’ pricing elasticity is key to determining the optimal price. Pricing sensitivity for manufacturers during the pandemic Crawford suggested that PriceAlign’s Machine Learning models can be more adaptive than typical time series models in the pandemic environment.