Manual Data Collection Delays Digital Transformation for Manufacturers

Automate Data CollectionManufacturers today are overloaded with data. It’s a double-edged sword—you need the data to uncover flaws in your manufacturing processes, yet there can be so much data that it becomes counter-productive. Traditionally, this data has lived in discrete systems (i.e. siloes) with limited or restricted access. It is often collected manually with no standardized policies from plant to plant.
 
As a result, information can be difficult to find and cumbersome to digest. Additionally, manual data collection puts the data at risk of human error, skewing resulting intelligence and inevitably detracting from the real business of innovation, revenue growth, and customer satisfaction due to its time-consuming nature.
 
For many manufacturers, this is why digital transformation has become a critical, board-level issue.
Industry research from the Cloud Industry Forum (CIF) asserts that 72% of firms plan to roll out a digital transformation strategy in the next two years. While the manufacturing industry may have the same vision, research from InfinityQS revealed that these organizations are still manually collecting data, which poses a major barrier to achieving a full digital transformation.
 
InfinityQS recently surveyed 260 manufacturers—including some of the world’s largest manufacturing organizations—about the methods and systems they use to collect data. The findings revealed that 75% of respondents are still collecting data manually. Of these, an astounding 47% still rely on pencil and paper.
 
Interestingly, 77% of the manufacturers surveyed want to adopt automated data collection. While this finding demonstrates an awareness of the shortcomings of manual data collection, the contrast of only 25% acting on the desire exposes the real challenge that manufacturers face in pursuing digital transformation and ultimately adopting Industry 4.0 technologies.
 
InfinityQS’s findings match those of a report from the Boston Consulting Group (BCG); Sprinting to Value in Industry 4.0. BCG uncovered the desire of manufacturers to adopt advanced digital industrial technology. However, BCG reported that manufacturers face a host of barriers to adoption, including defining an effective implementation strategy and challenging cultural change within an organization.
 
In the InfinityQS survey, respondents noted the following top three most important challenges to collecting and analyzing data:
 
  1. IT Constraints: With limited or old workstations, spotty network connectivity, complex plant IT infrastructures, and IT teams stretched too thin, new and innovative IT projects take a backseat to putting out fires and addressing traditional “break-fix” issues.
  2. Not Enough Time: In a labor-intensive, time-consuming manual data collection environment, operators don’t have enough time to do anything with the data beyond confirming standard quality and compliance checks.
  3. Lack of Data Source Integration: The ability to gather and compare quality-related data from multiple sources is vital to making real-time decisions. But with legacy systems, incompatible devices, and disparate databases, gathering data into a single repository can seem impossible.
 
Luckily, there are options, but it will require manufacturers to muster the troops—from the plant floor to the C-suite—and prioritize automation. Moving to the cloud can simplify on-site IT infrastructure, creating a foundation for automation and industry 4.0. Finding a vendor that is well-versed in data source integration will streamline the set up, but it’s possible to address each source on a one-by-one basis to determine the best option for integration (and standardization!) When processes are automated, operators will have more time to analyze the data collected and find opportunities across the organization for global transformation.
 
Looking to the future, as manufacturing firms start to reassess their current technological capabilities, the ability to automate critical actions will pave the way for other recognizable benefits such as increasing operational efficiency, improving product quality, and achieving significant cost savings. It’s imperative that organizations look to address this now or risk being left behind by their more tech-savvy counterparts or competitors.
 
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