3 Ways Talent on Demand Helps Manufacturing Put Big Data to Use


A manufacturing operation today is a lot like an orchestra: It depends on a multitude of individual events to occur in precisely the right way at precisely the right time. No longer do factories keep deep inventories of a product’s components on-hand. Instead, they rely on sub-contractors to deliver them just before they’re needed on the line.

For that matter, in many instances assembling a product involves receiving pre-built modules from distant factories so that they can be integrated into a product at the right moment. Boeing’s 787 Dreamliner, for example, involved more than 100 suppliers who provided everything from individual nuts and bolts to engines and airframes.

Manufacturers have embraced big data to do everything from identify process interdependencies to monitor product quality.

All this happens because of big data, which manufacturers now use to do everything from identify process interdependencies to more accurately forecast demand, monitor product quality and connect machine-level daily production to financial performance.

For years, the biggest companies have used advanced supply chain systems to manage the flow of components across the manufacturing process. But the capabilities of these systems shouldn’t be confused with the predictive and prescriptive uses to which big data can be applied. Businesses like GE and Boeing understand that, and have integrated the use of analytics tightly into their operations.

Other organizations, though, are just beginning to explore how big data can improve their processes, or aren’t large enough to warrant a full-time analytics staff. For these companies, talent on demand provides the exact kind of solutions they need, when they need them. They can engage big data expertise that’s tailored to their precise requirements in planning, operations, logistics or quality control. For example:

Analytics can identify areas where operations can be made more efficient, and thus where procurement levels can be reduced for equipment and supplies.

  1. Fine-Tuning the Production Line: Big data tools excel at capturing data at the machine level, says IndustryWeek. That means you can gather the information you need to determine whether each product is being manufactured in the most time- and cost-effective way. Not only does this help you achieve greater profitability on existing products, it allows you to determine the optimal approach to future products as they move from planning to production.
  2. Understanding Historical Data: Some manufacturers have gathered machine-generated information for years. But because few tools were available to tease useful intelligence out of the data, they did little more than archive it. With advances in technology and the increased number of people who’ve been trained to take advantage of it, that’s changed. So, for example, on-demand analytics talent can identify areas where daily operations can be made more efficient, and thus where procurement levels reduced for equipment and supplies.
  3. Identifying Where Data Can Play a Role: This one might be obvious, but no company reaps rewards simply by deciding to embrace big data. The keys are to understand which data are important and to develop solutions for analyzing it so its insights can be applied in ways that increase the value of your efforts in everything from daily production to marketing and sales. To do that, you need not just a “data specialist,” but an executive on demand whose expertise includes the workings of your industry, your company’s technology, and how data can be used to optimally position your business for success.

Analytics have become a foundation block of modern manufacturing, but every company faces its own set of unique challenges. Analytics talent on demand allows you to engage professionals whose skills align with your needs, whether your aim is to improve existing operations or plan for the future.


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