Automation is the use of largely automatic systems in a system of manufacturing or other production processes. Automation can be seen in both machinery and in software and is used to help organizations elevate efficiency and productivity, improve collaboration, and reduce workload for human laborers. System automation is a relatively new concept but has proven its value in a multitude of industries. Like AI and Big Data (below), automation is used to help companies explore new heights and improve the way their manage day-to-day business operations. The demand for automation software tools has skyrocketed in the last few years, mostly due to the need for cost savings, given the rapid growth in many firms.
In software (particularly the workflow and document management space) studies have shown that automation helps eliminate data entry errors and associated rework as well as reduce paper usage by up to 75%. For a large enterprise, these savings can amount to millions of dollars.
As workflow software providers ourselves, we’ve seen first-hand what automation can do for your business, and as we continue to see new developments in this technology, we firmly expect rapid innovation to follow.
Further Reading: Workflow Automation – The “Now” of Engineering Project Management
Artificial Intelligence (AI)
When talking about the latest trends in engineering, it may come as no surprise that Artificial Intelligence (AI) is coming to the forefront of modern engineering. After all, it’s likely to define the way people interact with computer systems in the coming decade. Artificial Intelligence is defined as the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. It has applications in marketing, banking, finance, agriculture, healthcare, and even space exploration. In essence, there are virtually no limits to what artificial intelligence can accomplish.
The term Artificial Intelligence was coined in 1956 by American computer scientist John McCarthy at the Dartmouth Conference, although the first form of AI was seen as early as 1951. In this year, a machine known as Ferranti Mark 1 developed an algorithm to proficiently learn the game of checkers, which was followed by a General Problem Solver algorithm used to solve mathematical problems. Subsequently, John McCarthy created the LISP programming language, which later became important for machine learning.
For workflow and document management software AI is helping to accomplish many of the mundane tasks humans have had to do for years. This includes tagging and indexing files, finding files through heuristics and pattern searching, anticipating bottlenecks in workflows based on previous outcomes, and much more. Letting software make suggestions and recommendations based on deep learning patterns will ultimately improve the outcomes of workflows and speed up process accomplishment.
Further Reading: ImageSite – Driving Value and Innovation
If you’re working in technology, healthcare, finance, or any other data-centric disciplines, then you’ve probably heard the term “big data,” as It has become a focal point for consumers and organizations both large and small. The term “big data” was conceived in 2005 by Roger Mougalas – the director of market research at O’Reilly Media. Magoulas runs a team responsible for building an open-source analysis infrastructure, providing analysis services to decision-makers at O’Reilly Media.
Big Data refers to a large set of data that is almost impossible to manage using traditional business intelligence tools. Although the fundamental concept of Big Data has been around for decades, it hasn’t seen the spotlight until the early 21st century. This is primarily due to recent advancements in modern computing and computing resources now available in affordable PCs and networked infrastructure.
Companies are using big data to solve big problems. Influencers, academicians, and collaborators all agree that big data is changing the modern business landscape as we know it. It has been used in an extensive range of industry applications, including but not limited to, marketing, finance, engineering, and healthcare.
For a long time, engineering has relied on complex solution systems for structure design and analysis using sub-optimizing algorithms, such as finite element analysis. Using “big data” systems allows for a more exact solution, ironically using less complex algorithms but with the benefit of millions, if not billions of situational iterations.
Further Reading: Using Data to Improve Operational Efficiency
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Further Reading: What is a Document Management System?