by Richard Howells, Global Vice President, IoT and Digital Supply Chain, SAP
The massive numbers of connected devices — and the explosion of data that these “things” generate — has changed the way we do business forever.
Smart products, assets and always-on things have provided us with access to unparalleled amounts of information. This — along with the evolution of Big Data, machine learning, artificial intelligence (AI) and technologies such as blockchain — is enabling us to converge operational and information technologies to make machines smarter and drive end-to-end digital transformation.
Every “Thing” Is Connected
Everything is connected, from the products we buy to the equipment and assets we use, from the cars we drive to the places where we work — and even our homes.
We have seen the evolution of Industry 4.0 and the Industrial Internet of Things. And now we are seeing this in everyday life, with sensors on:
Every “Thing” Is Intelligent
As connected devices collect and exchange data, we can leverage the data they provide to make them smarter through built-in machine learning. We can improve how employees perform their jobs in the warehouse, on the production floor or across the business by leveraging AI. We can use 3D printing to transform the way we think about business processes and reimagine the manufacturing of products.
By moving to an environment where we can leverage the data from these innovations, we can predict patterns, automate processes, and manage by exception.
Every “Thing” In The Moment
This constant connectivity is resulting in more real-time transactions. As consumers, we leverage omnichannel technology to place orders, anytime, anywhere and on any device.
This ability to order “in the moment” has raised the bar for how quickly vendors are expected to fulfill our orders. And when we go to work, we expect the same real-time systems, ease of use, and access to information.
We want to leverage the Big Data that is now available to not only make real-time business decisions but to automate as many of these decisions as possible. But we can’t afford to hire armies of data scientists to analyze Big Data to tell us everything is fine.
We need to drive predictive analytics and machine learning techniques to enable us to focus on identifying and solving issues when they occur, as well as recognizing patterns and opportunities to increase margins or drive new business processes. To achieve this, we must place Big Data into the proper context to solve business problems.
Every Business Process Needs To Be Connected To “Everything”
IoT creates the ultimate Big Data challenge. Data contains zero value unless it can be turned into actionable insight and integrated into a role-based business context that provides visibility of “everything,” including structured and unstructured data.
It is not good enough to rely solely on the business data from the systems we leverage.
We need to access data from real-time sensors on products, assets, fleets, infrastructure, markets and people in the field. We must also capitalize on unstructured data, such as customer sentiment, to get a true picture of demand. And data from weather and traffic situations can help us see the impact of environmental changes on our business processes.
Connect “Things” With People And Processes
A company’s journey to connect things with people and processes is becoming the catalyst for digitalization. IoT is not necessarily new to most companies. But while many can collect, store and visualize their data, they may not understand what to do next.
We need innovative solutions that enable companies to not only digitalize existing end-to-end business processes but enable them to evolve new business models to run digitally. Leveraging the Big Data provided from IoT would allow our organizations to create:
This story originally appeared on SAP’s Business Trends.