With data analytics, businesses can make sounder decisions about new projects and better understand their customers and competitors. While big data projects may seem most applicable to marketing or social media firms seeking to make sense of new trends, they have also impacted enterprise sectors such as manufacturing. MBX Systems, a Seagate Cloud Builder Alliance partner, utilized analytics when deciding to get into the custom appliance market.

Speaking to Manufacturing.net, MBX Systems COO and president Jill Bellack explained that the company changed direction in 2000, moving away from the small and midsize business market and toward appliance manufacturing. It now uses a SQL-based enterprise resource planning system, on which it develops software and evaluates each solution’s viability by using analytics.

MBX has always used data analytics to make business decisions,” stated Bellack. “In 2000, we re-engineered our business model based on data that supported our decision to eliminate the SMB side of our business and manufacture exclusively for the OEM appliance market. The emotional side might have kept us where our roots and our comfort zone were, but the data clearly stated the appliance market was the right direction for MBX.”

Going into further detail, Bellack explained that MBX Systems makes extensive use of analytics for demand planning and assembly testing. MBX’s managers can data to better anticipate the labor requirements for production periods, provide estimates to vendors and negotiate prices.

Ultimately, smart application of analytics empowers MBX Systems to reduce overhead and train employees more efficiently. The company also gains granular insight into revenue and profit at each stage of production.

In a post for Forbes, gyro Denver senior analyst Luke Bemis observed that big data itself is just a catalyst and that it takes expertise to transform it into a valuable business asset. With cloud storage capacities continuing to surge, more enterprises will follow MBX Systems’ lead and optimize the value of big data for operations.

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