Big things come in small packages

2018 has seen trends like artificial intelligence, machine learning, augmented reality, edge computing and smart sensing flourish. Looking towards 2019, enterprises need solutions that connect the physical and digital worlds to drive innovation through real-time guidance, data-powered environments and collaborative mobile workflows.

Achieving greater enterprise asset intelligence offers businesses a sense of what is happening in their operations, provides them with a way to quickly analyze the information and gives them a platform to act on it to reach higher levels of customer experience, productivity, and service.

One of the future trends that will drive the enterprise environment in the year ahead is “small actionable data”

As the world becomes more complex and data-driven, businesses want better ways to navigate and automate these complexities without the expense of human capital. Successful enterprises of the future will rely on real-time data and insights into that data to run their businesses efficiently with a competitive edge.

Enterprises have sought for years to obtain insights from “Big Data” - large amounts and volumes of data that businesses collect and store on a daily, sometimes instantaneous basis. But in 2019, priority will shift towards “small actionable data” accessible naturally within a workflow, where it is specific to a use case to solve a problem and achieve desired outcomes.

In terms of data capture, two-dimensional bar code scanning continues to gain acceptance and outpace the global market as the preferred track and trace method. In the bar code scanning handheld space, the transition from 1D to 2D imaging comprises more than 70% of total handheld scanner sales.

UHF RFID will continue to expand beyond the item level inventory use case in retail back into the supply chain and manufacturing spaces. Over 10 billion UHF RFID tags will be used throughout the retail, manufacturing and transportation industries in 2018. Healthcare use cases have also started to emerge and show promise in clinical and hospital settings for track and trace use cases.

In the future, machine vision holds great promise once some of the constraints (cost, size, speed) are more optimized for historical use case scenarios. It will provide additional value to business applications including pattern recognition, color recognition, etc. In addition, advanced image recognition software will augment the capabilities to serve many additional applications, such as recognizing produce directly on a grocery scanner, measuring the size of a box or providing quality checks on printed circuit boards in an electronic manufacturing operation.

Businesses are looking to expand the capabilities of data capture and the way it is employed to track and trace assets and critical data in an automated fashion. They demand integrated data solutions that not only take data capture to the next level but are also integrated with analytics that offer real-time guidance - generating directional and actionable insights for real-time decision making.

In today’s on-demand economy, advanced analytics capabilities enhanced by AI and ML are critical as businesses need the predictive (providing anticipation of what will happen) and prescriptive (providing recommendations on what to do to achieve the desired outcome) insights to turn dark data into actionable data. General AI is applied to identify things when you don’t know what you are looking for. ML is utilized when you know what you are looking for, and you can utilize ML to sharpen your knowledge around known areas and build in rules and logic to create a best next action.

With enhanced analytics, businesses are moving from forecasting to intelligently anticipating and predicting both operational and customer needs.