Today, most businesses are linked in one way or another to technology. We continue to search, within our perspective processes, for the most assertive way to embark on digital transformation. Where we take advantage of the latest technology and do not fall behind in sector development.
One of the most relevant areas within the digital transformation process is workflow optimization. We seek to find the best technologies to automate, coordinate and reach the next level of our operational efficiency. Here cognitive automation represents the next generation towards unprecedented automation.
What is cognitive automation?
Cognitive automation focuses on software that brings intelligence to information-intensive processes. It takes advantage of different algorithms and technological approaches, such as natural language processing, text analysis and data mining, semantic technology, and machine learning.
It is associated with Robotic Process Automation (RPA), Artificial Intelligence (AI) and Cognitive Computing developments. These partnerships have the power to help organizations extend automation to more processes, making the most of not only structured data but also the growing volumes of unstructured information. For example, unstructured information, such as customer interactions, can be easily analysed, processed, and structured into data useful for subsequent process steps, such as predictive analytics.
Cognitive automation creates new efficiencies and improves the quality of business processes at the same time. As organizations embrace cognitive automation by placing it at the centre of their business and digital transformation strategies, they will have a growing opportunity for much more advanced intelligent tools.
So how are the tools for traditional automation and cognitive automation different?
Cognitive automation vs traditional automation
Traditional automation is a tool that is mainly limited to process automation. These may or may not involve structured data, which needs quick and repeated actions. These actions do not require much contextual analysis or contingency management. Simply put, traditional automation is limited to just finishing or performing tasks within a rigid set of rules. These types of processes can only work effectively, as long as, the decisions follow an “if/then” logic without room for any human judgment involved. This limits the time you want to process unstructured data since they cannot reformulate meanings.
Traditional automation has great advantages and works effectively in a wide variety of processes, such as data entry, automated help desk and approval routes.
On the other hand, cognitive automation or also known as intelligent process automation allows us to accommodate structured and unstructured data to automate much more complex processes. This process is infused with a cognitive capacity that can handle automation using large volumes of text and images. This means a radical advance compared to the traditional approach because it stops repeating or copying rules and activities, to “respond” and adapt automatically towards the interpretation of a specific scenario.
Benefits and applications of cognitive automation
One of the great benefits of cognitive automation is that after training the system, you do not need the support of a data scientist to create complicated models, which often become obsolete in a short time. These systems weave unstructured data in documents, customer interactions, voice, and computer vision into workflows so they can respond and adapt to change. Building on this, let’s look at some key benefits:
- IT service management tasks around problem identification and incident response automation are simplified.
- Decision-making can be automated, reducing manual decision-making. With this, mitigate risks and accelerate processes that can be stagnant due to human factors.
- Reduce costs even more than with traditional automation. If implementing traditional automation is an alternative to reduce costs in processes, cognitive automation takes it to another level. Reducing contact points within the system, delegating it to a single intelligent tool.
- Eliminate tedious and repetitive tasks and work for quality improvement. When we remove these factors, error rates drop dramatically. Reducing manual labour results in the anticipation and reduction of human errors.
- Improving productivity without the need for more staff. Cognitive automation solutions can work 24 hours a day, 7 days a week, 365 days a year. It can offload even complex tasks like extracting decision-making data from documents and emails. This not only improves the completion time of critical tasks but allows to expansion organization’s capacity without additional staff.
Cognitive automation applications
- Warehouse management. Cognitive automation once implemented, helps to keep track of all machinery status and inventory. For a company that has warehouses in multiple geographic locations, managing them all is a challenging task. Keeping track of all the available inventory in all the warehouses, always ensuring the maintenance of all the machinery, solving any problem that arises, etc., are some of the associated tasks that can be cognitively automated.
- Airbus has integrated Splunk’s cognitive automation solution into its systems. Helps them track the status of their devices and monitor remote warehouses through Splunk dashboards.
- End-to-end customer service. Thanks to cognitive automation, companies can understand the customer journey and generate much more empathetic automated experiences that solve more complex situations.
- Religare, a health insurance provider, automated its customer service using a chatbot powered by cognitive automation. Through this tool, it is possible to carry out procedures such as policy renewal, customer query ticket management, resolution of large-scale general customer queries, etc.
- More efficient logistics operations. One of the big problems within logistics operations is delays in deliveries. The biggest challenge is sorting systems and warehouses. Automating them allows you to adapt to changes and increase efficiency in shipment volume.
- Postnord solved this problem through cognitive automation. Its implementation ensures that systems are always up and running and free of errors. In case of failure, it is the same intelligent automation that solves the problem.
Cognitive automation has proven effective in addressing these key challenges by helping companies streamline activities and processes. Whether it is for the improvement in compliance and the general quality of the business, greater operational scalability, lower response time and lower error rates. In general, it produces a positive impact on the flexibility of the business and the efficiency of the entire value chain.
It is a technology that will have to be kept track of. Its development focuses on one of the key pieces that intelligence technology development focuses on creating human-like and even superhuman intelligence. With this, the possibilities multiply.
