Businesses everywhere are digitizing their architecture in a bid to improve efficiencies and customer experience. As part of this process, software systems offer more automated ways of providing value in those situations which once required the physical intervention of humans to make decisions between two or more enterprise systems. Over time, these systems have evolved from creating automated workflows by opening communications paths and integrating different data systems. They have created runtime workflows and, more recently, intelligent workflows, in which some form of machine learning will drive context-specific decisions for the end user.
Consider the purchase recommendations we receive online, based on related searches or recent areas of interest. The technologies that underpin these are largely limited to specific exchanges and experiences within a particular vertical or use case; humans are still heavily involved in coordinating and driving decisions.
Machine learning, combined with workflows, will soon be able to make decisions for users based on profiles and interests. This is an example of ambient computing, in which independent software systems communicate across various contexts, protocols and systems to transfer data and orchestrate decision-making at lighting speed. It’s likely that, with the widespread adoption of Alexa Echo, Google Home or Apple’s HomePod, most of us already have a primitive form of ambient computing in our homes.
The potential application of the technology ranges far beyond consumer-focused ecommerce and virtual assistant capabilities, however.
Ambient computing and IoT
The value of the data created by the billions of connected devices comprising the internet of things lies in the improved business processes that can result from the intelligence and insight it delivers. Integrating this data — and the intelligence its analysis provides — with business processes is key to the successful implementation of IoT systems.
If a manufacturing business, for example, can predict equipment failure based on the information generated by a network of embedded intelligent sensors and algorithms, it will be better able to improve its inventory management, reduce costs and even prevent potentially harmful failures. Today, humans are still required to make decisions — particularly where disparate systems are involved.
Enterprises will enjoy greater value from IoT when these diverse systems are able to communicate using a form of machine learning-based intelligence and canonical data architectures. With the appropriate permissions and security measures in place, accessing and pulling together the relevant information from different applications and platforms will deliver more insightful results. Operators will play a critical role in providing access to a cross-industry set of rationalized information that can be used via cloud-based platform services.
Furthermore, by optimizing the supply chain, ambient computing will play a key role in an organization’s digital transformation, which will include the significant benefits to clients that require product performance, availability, reliability for their competitive edge and/or in support of their customers’ safety. As a result of this move to intelligent IoT systems to correlate cost, availability and performance data from components and systems from many different manufacturers and operational systems, businesses will be better able to automatically select and purchase the best, most cost-effective parts and provide higher-value services to their clients.
To enable IoT, ambient computing requires available access to all relevant data, but it is also necessary to translate this data into a form that can be understood across all systems. The provision of layered and rationalized data architectures that can be rapidly accessed across intelligent systems is, therefore, crucial to its success. Business analysts play a critical role in providing the vision necessary to translate the current business process environment into this next-generation automated and intelligent workflow.
However, while the technology may already be available, it will never be fully implemented until businesses appreciate the value that it offers. Most organizations tend to focus on their own business processes. To visualize the potential of ambient computing, and create these next-generation scenarios, they must broaden their gaze to consider what can be achieved across different verticals and their associated systems.
A design for the future
By allowing the simultaneous sourcing of data, either specific to a business or from external sources, ambient computing enables business to improve experience, competitiveness, relevance and customer satisfaction.
Digital design is key to its long-term success in providing the visualization of the end-state value to the business owner. Creating top-down plans, via design-integrated engineering, that incorporate elements such as workflows, integration patterns and, most importantly, a conceptual journey of where the business is now to where it needs to be, will drive the required technology, data and intelligent flows required for ambient computing systems.
Digital transformation is improving efficiencies and experiences across all industries — from consumer online shopping experiences and digital assistants to the efficiency and productivity of automated manufacturing plants using IoT technology. With greater digital design, wider access to data and a standardized understanding of its analysis, as well as, importantly, the buy-in of an organization’s stakeholders, we will experience a new wave of value to consumers and enterprises alike that will have a positive effect on our daily lives.
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