According to Allied Market Research, in 2018, the market value of cognitive computing was $8.87 billion, wherein in 2026 the market will reach up to $87.39 billion. Also, the market is growing at a CAGR of 31.6% from 2019 to 2026. Besides, the market research company also highlighted that cognitive computing is a next-generation system to process unstructured data quickly. IBM was the first company which develop the cognitive computing-based system.
If you are a tech-enthusiastic, you indeed would have heard, “Cognitive Computing is the future.” Why? Because this technology mimics human behaviours. At present, almost all businesses are looking for a solution that can mimic their customer’s behaviour because there is no value in the industry without customers. To acquire better insights into cognitive computing and its increasing role in business, we must understand certain aspects. So, let’s discuss why every business enterprise must reinvest in this technology, how they can reinvest in technology, and what they will get in return with a real case study.
Before discussing why enterprise needs cognitive computing, let us briefly understand cognitive computing. Cognitive computing is all about understanding and simulating human reasoning and human behaviour, and it is a part of Artificial Intelligence (AI) with some similarities and differences. One prominent cognitive feature: “mimic human intelligence”, makes it different from AI, which focuses only on solving problems using algorithm-based systems. Adaptive, Interactive, Iterative, and Contextual are four attributes of this technology attracting every business sector.
You all know that data is a valuable asset for any enterprise, which is only a medium to grow continuously. The business’s success depends on accurate data collection, processing, and analysis. The increased use of social media platforms in business has encouraged customers to share their views in different forms. The Amazon reviews, tweets, memes, images, video testimonials are famous examples of customer opinions, thoughts, feedbacks. All these are unstructured data.
Most enterprises have around 80% unstructured data that comes in various forms.
The analysis of these unstructured data is quite challenging. However, technologies are making it easy for enterprises. The cognitive system’s features efficiently understand human language patterns and input. Thus, it quickly processes the unstructured data to streamline the business operations rapidly.
Without the support of other technologies, no single technology can bring valuable solutions for any business growth. Cognitive computing requires technologies to develop customized solution systems. Machine Learning (ML), Deep Learning (DL), Natural Language Processing (NLP), Neural Network (NN), Automated Reasoning, Informational Retrieval (IR) are those key technologies. In all these technologies, the key technology is NLP and, after this, Machine Learning. The NLP’s capability to effectively process the natural language raises cognitive systems’ demands in varied business sectors. NLP makes it easy to analyze this unstructured data that automatically improve customer services by better understanding their requirements.
The analyzed data could be used to make better decisions to enhance customer experience. These decisions efficiently optimize the business processes, assist in operational costs, and boost business growth. Cost is another factor that impacts the business and its performance. Enterprises are looking for a solution that supports them in cost-cutting without any loss. You all know, at present, cloud computing has become a mandatory technology within businesses. By adopting the cognitive system, enterprises can also reduce their other costs. Enterprises with cloud-based services seek to invest in cognitive systems to reduce the investment cost because of the cloud.
A few years back, healthcare was a top sector in investing the cognitive computing. Although at present, various other businesses have unstructured data, and to analyze it, they need a robust analysis system. The Independent Liverpool Student Newspaper has also discussed Verified Market Report done for the Global Cognitive Computing market. The news agency has also highlighted business areas for future scope: Telecom, IT, Aerospace, Defense, BFSI, Consumer Goods, Retail, Energy, Power, Education & Education, and media.
Another company Reportsglobe has also verified the immense growth of cognitive computing between 2016 to 2019. Ohio University has also created an infographic and highlighted that cognitive computing has been changing all businesses. These statistics are enough to understand that this is the right time for reinvestment in business through cognitive computing systems.
Every technology implementation and execution requires following specific steps, and it applies to the cognitive computing implementation. The enterprise executives must have to study the market and develop a systematic approach before implementation. IBM was the first company which develop the cognitive computing-based system. The name of the system is “Watson” which answers to questions asked in natural language. The company executives have built a 3-phases strategy to accelerate enterprise reinvention using cognitive computing. With this reference, we have three steps framework to support enterprise executives.
Strategy formulation is a standard step in any reinvestment, and the strategy should be developed by considering needs, costs, benefits, and timeframe. The executives must have to test the change management process before implementing a major technology change. They have to find answers to questions like current technology culture, employee’s skills, readiness to embrace change, challenges, and risks. These answers would build a lucrative strategy.
The executives must have to test the change management process before implementing a major technology change.
In the following steps, it is necessary to assess the current business operations. Understand how enterprises function inside and outside. Analyze every department and find out functions that are time-consuming and unable to produce results. For example, in the marketing department, building lasting customer relationship is not easy. To make it easy, companies are investing in automated tools and analytics systems. In these ways, identify all functions which could get benefits after implementation of cognitive computing. These benefits could rewrite the business mission and future vision to be competitive in the market. Since multiple functions have been executed within each department, thus, prioritize the functions which must be changed.
The prioritized functions help to select the right company to implement the cognitive strategy. It is suggested to follow a use-case approach to cross-check whether the strategy would work to solve the identified problems. The testing of the use-case gives an idea about how it is helping in enhancing the customer experience. By measuring performance, the strategy could be scaled into various levels.
Cloud-computing attributes, rise in big data analytics, adoption of machine learning technologies, and demand for excellent customer services are major factors behind the growth of cognitive computing within the business. Every enterprise thinks about “ROI” whenever investing in any technology and new information systems. Cognitive computing doesn’t only ask for investment but also gives benefits in return. The following points highlight those benefits:
It is already discussed that unstructured data size has been increasing every day as soon as enterprises move towards digitization and automation. The analysis of these unstructured data using cognitive computing makes its processing easy. When they understand those data, they efficiently provide solutions to their customers by finding out the latest patterns. And, satisfied customers always be beneficial for enterprises.
Technology and data-driven economy are increasing competition in business sectors. Enterprises need to stay updated with the latest trends and technology to compete with their competitors. Implementation of the cognitive system does not cut the operation costs but also enhances the operational business processes. Facility to collect and process customer data assist enterprises to make better decisions and improving business processes.
Human resources can make improved decisions while hiring, costing, and scheduling using this system. Better decisions are taken for employees also impacts the business performance.
The integration of varied data such as market trends, customer behaviours, service preferences, etc., generates insightful data statistics. Interpretation of those statistics helps marketers and decisions makers to develop new strategies for enhancing customer interaction.
Every investment returns something if it is done in the right way. The enterprise needs to make a great team and keep patience to get in ROI after making a technology investment
Many big players are working in cognitive computing, but some names most often reside at the top. The Canadian-based research company Pat Research has listed the top 10 companies: Spark Cognition, Expert System, Microsoft Cognitive Services, IBM Watson, Numenta, Deepmind, Cisco Cognitive, Cognitive Scale, Customer Matrix, and HPE Haven OnDemand.
Apart from these, 3M, Google LLC, Oracle Corporation, Hewlett Packard Enterprise Development, Sap SE, Tibco Software, etc. have also positioned in the global cognitive computing market.
Quantitus Innovation Inc, another prominent IT solution provider, believes that technology can advance business and offer incredible customer services. The company has also shared a video to explain that the retail sector can leverage cognitive computing in various ways: data analysis, sales conversion, demand forecasting, pattern detection, and inventory planning.
All these provide intelligent solutions to various vertical and horizontal businesses. Let us take a new case study of the leading global IT solutions organization, Coforge, utilizing emerging technologies in unparalleled domain expertise to make a real-world business impact. The company has been offering services in the insurance sector as well, and it has brought a cognitive computing solution to reinvent insurance to speed up insurance claims. You are aware of how it is challenging to claim insurance. Customer churn, manual intervention, increased loss ratio, fraudulent claims are extensive pain areas of claim management, and it is impacting whole financial performance and associated stakeholders. To overcome these pains, the company developed a cognitive computing-based claim management system. Machine learning, deep learning, cognitive adoption, and image recognition have been used to design this system. The reap attractive margin is the best feature of this system. The company is offering this service to its various insurance sector clients and supporting them in enhancing operational efficiency.
The technology companies have a similar objective: harnessing the technology and making it accessible for their customers and business growth. The reinvestment in cognitive computing with integrating other latest technologies is opening the door of enhanced market opportunities. Its effective implementation can quickly scale the business and enhance productivity. Successful and established businesses suggest creating a digital strategy and building a robust infrastructure for integrating cognitive computing systems. The business can be advanced to the sky and bring high value to the table. If you are a young entrepreneur or established businessman, evaluate your existing IT system and plan for cognitive reinvestment to elevate your business growth.