Each business in every industry is unique, and yet there are common technologies that are used across each of these markets “horizontally”. For example, all service organizations – whether supporting utility, construction, mining or railroad operations – use heavy-duty pickup trucks, cellular data networks, and PCs with USB ports. Some organizations just add modifications to tailor these foundational tools to their specialized needs, such as hi-rail pickup trucks that can ride on railroad tracks, or the use of ruggedized mobile PCs with additional specialized I/O ports.
And although these are just a few examples of the well-established, fundamental tools that have been accepted as “must have technologies” in nearly every global industry, it’s rare to hear anyone really shed light on how they are impacting corporate performance across multiple industries.
Yet, when a new technology moves from niche uses to more mainstream application, that becomes news. That’s to be expected given that IT professionals need to be on the forefront of technologies that are quickly moving into their industries, whether as a company initiative, or something that a competitor is exploiting. But these stories don’t always articulate how the implementation of such new technologies impacts the ongoing performance and role of the previously mentioned, and more “common”, underlying technologies such as rugged tablets in various workflows and business processes. The correlation between the old and new is often very critical to understand. Especially if you want to maximize the benefits of these new co-existing systems and increase the ROI for your entire technology investment.
For example, consider Big Data. It is one such “new tech” trend which has been rapidly embraced and heavily used in some industries – as you’ve probably seen in headlines. And 2017 may be a breakthrough year for its use in the Telecom, Utilities and Manufacturing sectors. But this change in IT architecture and data analytics won’t affect just systems analysts. It also will put more pressure on field service organizations to support their technicians as information workers. That means the implications of Big Data utilization will extend “outside the four walls” of a manufacturing or warehouse facility and all the way to the “last mile” of utility and telco service areas – driving organizations to re-evaluate how their existing technologies can and should be used to amplify the benefits of Big Data.
Simply put, “Big Data” refers to the huge data sets that can be collected today, and which once collected, machine-learning algorithms can comb through to spot trends and make predictions that were “invisible” before. With mass computerization of so many aspects of our personal and professional lives, vast amounts of data can be collected and analyzed to the benefit of nearly every company. IoT (Internet of Things) is delivering low-cost networked sensors on machinery, generators, transformers, factory robots, and many other things, and all these sensors are delivering data that, in the aggregate, is immense. Of course, server farms and storage companies have seen significant growth over the last few years.
But what can analysis of Big Data really do? And what do those capabilities really mean for organizations supporting highly mobile workforces, such as manufacturers, utilities and telcos?
Come back next week as I discuss the convergence of Big Data and mobility
Blog Author: Bob Ashenbrenner
President of Durable Mobility Technologies, LLC.