Cognitive automation is a blending of machine intelligence with automation processes on all levels of corporate performance. It takes the old model of augmenting people’s work with the help of machines, and turns it into machines doing the intensive labor while being guided by people!
Through cognitive automation, enterprise-wide decision-making processes are digitized, augmented, and automated. Once a cognitive automation platform understands how to operate the enterprise’s processes autonomously, it can also offer real-time insights and recommendations on actions to take to improve performance and outcomes.
This entire digital infrastructure results in what’s now known as a “self-driving enterprise.”
Change used to occur on a scale of decades, with technology catching up to support industry shifts and market demands. Corporate transformation was driven by organic customer demand and fulfilled by people who took the time to sift through trends and marketing research, and then used their years of experience to plan out the optimal supply lines and resource allocations.
Times have changed.
Now change occurs on a daily basis. Technological and digital advancement are the primary drivers in the modern enterprise, which must confront the hurdles of ever-increasing scale, complexity, and pace in practically every industry.
Yet the way companies respond to these shifts has remained oddly similar--using organizational data to inform business decisions, in the hopes of getting the right products in the right place at the best time to optimize revenue. The human element--that expert mind that is able to comprehend and act on a vast amount of information in context--has remained essential to the planning and implementation process, even as it has become more digital than ever.
But as those upward trends of scale, complexity, and pace continue to accelerate, it demands faster and smarter decision-making. This creates a whole new set of issues that an enterprise must confront.
For more, read or listen to Fireside Chat with Marc Engel, CSCO Unilever
No industry is immune to the digital transformation that is causing higher market volatility and a massive influx of data that requires unique collation and management techniques. Alongside this, corporate planning processes and supply chains are being disrupted by:
All of these create chaos through inventory mismatches, ongoing product research and development, market entry, changing customer buying patterns, and more. This occurs in hyper-competitive industry sectors that are being constantly upset by startups and entrepreneurs who are more adaptable (or simply lucky) in how they meet ongoing consumer demand.
The best way organizations can respond to all of these is by harnessing the available data, both internal and external, to make the most informed decisions possible with efficient workflows and profitable results in mind. Yet another problem arises from this: much of the essential data is either locked away in legacy computer systems or siloed in networks that don’t communicate efficiently (or at all) with one another.
Attempts to use analytics and create data lakes are viable options that many companies have adopted to try and maximize the value of their available data. Yet these approaches are limited by the sheer volume of data that must be aggregated, sifted through, and understood well enough to act upon.
To manage this enormous data-management demand and turn it into actionable planning and implementation, companies must have a tool that provides enhanced market prediction and visibility.
This is being accomplished through artificial intelligence, which seeks to simulate the cognitive functions of the human brain on an unprecedented scale. With AI, organizations can achieve a comprehensive understanding of consumer purchasing habits and find ways to deploy inventory more efficiently and closer to the end customer. As the predictive power of artificial intelligence is on the rise, it gives companies the methods and algorithms necessary to digest huge data sets and present the user with insights that are relevant to specific inquiries, circumstances, or goals.
Even so, there’s another level of AI performance that is giving companies the ability to tap into the full potential of their data: cognitive automation.
For more insights, read Pascal Bornet's How To Succeed In Your Cognitive Automation Transformation
A self-driving enterprise is one where the cognitive automation platform acts as a digital brain that sits atop and interconnects all transactional systems within that organization. This “brain” is able to comprehend all of the company’s operations and replicate them at scale.
Most importantly, this platform must be connected outside and in, must operate in real-time, and be fully autonomous. It must also be able to complete its functions with minimal-to-no human intervention on any level. It drives itself forward, taking the company along with it.
Only one platform exists that enables companies to achieve this level of operational automation. Aera is unique in its ability to empower self-driving enterprises in the following KPIs:
Aera releases the full power of intelligent data within the modern enterprise, augmenting business operations while keeping employee skills, knowledge, and legacy expertise intact and more valuable than ever in a new digital era.
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