In the article A Signal in the Noise: How to Best Manage Big Data, the author advocates some ways to improve the use of data for manufacturers as well as his idea for the best way to approach the use of big data analytics and data management. The author equivocates big data as sometimes “a needle in the haystack” when it comes to finding and using it in the manufacturing environment. With so much data produced by even small firms, the management, organization, and analyzation of the data can become overwhelming if not impossible. Industrial Internet of Things-based systems are estimated to create $4 trillion to $11 trillion in new economic value for manufacturers by 2025, according to McKinsey Global Institute. With such large value to be had, ignoring or underutilizing data could be a catastrophic mistake for manufacturers.
In a study of manufacturers conducted by the MPI Group, 76% of respondents reported plans to increase their use of smart devices in the next two years while 66% plan to increase their investment in IIoT-enabled products over the same time period. With many firms taking the necessary steps to collect and use data, a strategic approach is necessary. The author suggests a number of steps to jump-start the transformation to using data analytics. Recognizing human limits and the burden of isolation is the first suggested step. Here the author is advocating that firms understand that human teams are just not capable getting the insights that technology is capable of. The next step is forgetting the traditional supply chain cycle, and embrace the complexity of modern supply chains. With the IIoT, data can be captured all along the supply chain which can offer useful insights not previously possible.
Finally, the author advocates understanding four different measures before taking on new data management and analytics initiatives. Find the actual problem, the “signal in the noise” is the first and foremost issue at hand. Unless there is direction to the project, the project will almost certainly fail. Next is understanding the business case. One has to understand the strategic advantage behind any data management implementation. Lastly, finding where the optimization is most desperately needed and identifying the experts that are best suited to handle the data being generated is key. Overall, the biggest pitfall in bringing on new technology is the belief that good things will just happen. An understanding of the problem, the right people, and a tailored process will allow the technology to do the work it is supposed to.
Do you believe that understanding big data is really about finding the proverbial needle in a haystack?
Do you believe the increase in smart device usage automatically translates to more useful big data, or just more data in general?
As with most strategic IT plays, projects start off to gain a strategic advantage but quickly become part of the IT infrastructure. Do you think we are in the middle stage between big data being a strategic advantage and a necessary IT infrastructure requirement for manufacturers?