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Price Optimization Applied to the Manufacturing Industry

By September 11, 2013Article

In my blog post last week, I discussed the impact that Big Data and advanced analytics can have on business-to-business, enterprise sales. That got me thinking about examples of technology revolutionizing the status quo. While there are countless examples of this occurring, it is well known that manufacturing companies have long leveraged technology to successfully optimize supply chain management and procurement processes.

Not too long ago, manufacturing managers walked the floor with little more than a pencil and clipboard to note needed supplies, lines that were underperforming, etc. Fast forward to 2013 and this is considered inefficient at best and downright archaic at worst. The space has matured to include mobile devices, advanced analytics software and more recent innovations like RFID tags. 

Technology is now spurring a similar evolution on the manufacturing sales side. The solutions and acronyms may be different but the end result is the same — a movement away from making decisions based on human observation and manual systems towards one that depends on machine data and analytics. 

Enter profitable selling

Recent advancement in cloud and Big Data have pushed this evolution into the realm of possibility, and forward-thinking manufacturers have begun to turn this remaining bastion of “seat-of-the-pants-operations” into a competitive advantage. 

The often-complex sales cycle in the manufacturing industry requires that front-line salespeople have the right tools to drive margin across a variety of products and through multiple channels: direct, distributor and OEM. For this reason, leading-edge manufacturers have started to leverage systems to analyze massive quantities of data to identify where money is being inadvertently left on the table during the sales process. They also use this information to set data-informed, intelligent pricing and deliver meaningful data to the front lines. 

This simplifies business decisions and enables sales to capture opportunities to sell more profitably by negotiating confidently at the “moment of truth,” which is anytime they ask for a customer’s business. 

Broadening the impact 

Traditionally, this type of profit optimization was only achievable if an organization had a team of analysts manually crunching data. And even then it could take months to identify opportunities. As a result, these capabilities were accessible only to the largest enterprises.   

However, algorithm-based predictive analytics now enable insights to be derived almost instantly. Using machine analytics to maximize profits provides manufacturers of all sizes with a new way to improve their business and develop real competitive advantage. 

In next week’s blog, I will move from the theoretical to the actual by outlining a specific use case where a manufacturing company leveraged Big Data and advanced analytics to improve its bottom-line results.   

Neil Lustig is CEO of Vendavo. He is an accomplished executive with over 25 years of experience in the IT industry. After joining Vendavo in 2007, he led the global commercial team for three years prior to assuming his current role. Before Vendavo, Neil successfully directed Ariba’s North American field operations for two and a half years. Follow him on Twitter @vendavo.







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