Is Big Data in Manufacturing a New Buzzword or a New Tool?

    2/27/19 10:00 AM

    data-in-manufacturing--big data

    What is big data?

    The term big data may mean different things to different people and organizations.

    Google’s dictionary defines big data as “extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.”

    Gartner defines big data as follows, “high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation.” The focus in that definition is on variety, volume, and velocity.

    Big data is a buzzword. It is often used in relation to how companies can improve their business operations using advanced tools for analytics. Enterprise application companies are providing these tools for managing big data. For example, Infor included a Data Lake as part of the Infor Operating System (OS) that is delivered with its CloudSuite Products. Infor also has BIRST, which is one of the leading business intelligence tools offered today. In short, there are powerful big data tools available to capture, organize, manage, and interpret analytics in the manufacturing industry.

    But how does big data translate to helping manufacturers? Specifically, how does it help small to medium-sized manufacturers?

    Big Data and Manufacturing

    Historically, most small to medium-sized manufacturers are starved for data. Having data in manufacturing is not a given. Manufacturers try to capture data using mostly rudimentary methods, struggle to trust the data they have, and find it difficult to use the data they acquire.

    So, there appears to be quite the dichotomy between the theoretical discussion of big data in manufacturing and the reality of SMBs having any data at all.

    Given that premise, here are the areas we have seen manufacturers improve operations using big data.

    Sales data - Sales data is captured in primarily three places:

    • The CRM system is the first area where sales data is captured and pipeline activities managed. Forecasts, pipeline, and specific product interest can be gathered. This information may reside in the CRM system or, in cases where the ERP has a CRM, this data resides in the ERP database. The only way to gather this data is to have a CRM system collecting and populating the information.
    • The second area where sales information is primarily captured is at sales order entry in the ERP system. The more detail desired for analytics, the more information that needs to be captured. Good procedures must be in place to support capturing the proper information.
    • The third area where sales information is captured is from the ERP’s shipping area. A good ERP will provide what has been shipped and what is left to be shipped against bookings.

    Production data - Production data is best captured with shop floor tools, specifically labor and material transactions.

    The capture of labor transactions and manufacturing data in real time is one of the most important things a manufacturing company should do in relation to big data.

    • Collect indirect vs. direct time to have visibility into efficiencies, and also plan to have the optimum level of resources on staff.
    • Gather data showing actual run rates vs. estimates. This information can be used to update run rates, costing standards, and modify lead times to reflect actual data vs. speculation and hope.
    • Get actual costs for specific operations in the routing sequence. These actual costs can make it easy to gain a true profitably data analysis for specific parts, product lines, and customers.

    The capture of material issues and transactional manufacturing data is very important as well.

    • The use of material barcoding tools on the manufacturing floor will provide for improved, real-time inventory accuracy, improved job costing, and allow for optimization of inventory levels. The data gained can quickly flow throughout a manufacturing-centric ERP, making the material and production planners more effective in their roles due to having accurate real-time data.

    Please read What Should Go into a Weekly Production Report to better understand how production data can be used to keep the correct score for your manufacturing operation.

    Summary

    Ultimately, big data in manufacturing is a buzzword. It may be a tool for some companies, and especially huge manufacturers, but for small to medium-sized manufacturers, it’s a goal and a priority. Companies of this size struggle to gather regular data that could drastically improve their operations.

    Data in manufacturing has to be captured and have a home where it can be turned into useful information. The best way to ensure accurate, timely, and useful data is to have proper data acquisition tools and supporting procedures. The data needs a home and it needs to be in your manufacturing ERP database. One central location. That premise means not using spreadsheets. Finally, you need an ERP system that supports presenting relevant and desired manufacturing data analytics that can be used to quickly make good business decisions.

    Here to help

    Visual South specializes in Infor ERP software, supporting services, and business solutions. For more information on how an Infor ERP software system can help your business, visit the Visual South website.

    Visual South also offers guidance on all things ERP for small to medium-sized manufacturers and production companies. We are also more than happy to provide a free consultation about managing your ERP implementation, evaluating ERP, or just wanting to get better with your current ERP. Please reach out to us for a free assessment.

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    Tim O'Brien

    Written by Tim O'Brien

    Tim has over 20 years of successful experience helping companies improve their processes and operations using enterprise software solutions. Those enterprise solutions include Enterprise Resource Planning for manufacturers, Service Management for service oriented companies, and Enterprise Asset Management in the process manufacturing industry.