Trends 2019: Why insight engines are more important than ever

Trends 2019: Why insight engines are more important than ever

Data is the gold of the digital transformation – but only if knowledge can be generated from it. This is exactly the task that insight engines were designed to accomplish. Daniel Fallmann, founder and CEO of Mindbreeze, defines the six most important insight engine trends for 2019. 


Rarely has there been a time in which the saying “knowledge is power,” expressed by Francis Bacon back in in the 16th century, has been more relevant than in the digital age. In today’s fast-paced world, knowledge that can be accessed at the right time will determine whether the necessary business decisions can be made promptly, whether a customer will remain loyal to the company because he receives the answers he needs immediately, or whether time and money will be saved because predictive maintenance enables machine parts to be replaced before expensive production stoppages occur.


How much knowledge do companies actually have today? Paradoxically, less than ever, if you look at it in relation to the existing potential. There are two principal reasons for this. First of all, along with the dramatic surge in the amount of data available – under the heading of big data – together with escalating complexity, it is becoming more and more difficult on the whole to generate knowledge. Secondly, users are still forced to glean knowledge using the methods of the analog world. After all, the traditional file systems of popular applications and the overwhelming results from online search queries are essentially nothing more than old-fashioned card index boxes in which answers have to be collected by means of tedious, time-consuming manual work.


This is exactly where the so-called insight engine comes in – a system that addresses the potential of the digital transformation not only technologically but also methodologically. Insight engines utilize technologies such as deep learning, machine learning, and natural language processing (NLP) to extract relevant information from a wide variety of data sources – be they structured or unstructured – and bundle this information into knowledge that can be used throughout the company. In addition, users only receive the information relevant to their specific context, which becomes more accurate the longer the system is in use. In other words – knowledge at the touch of a button and right when you need it.


The latest market studies confirm that the number of companies that are recognizing the benefits of insight engines is growing rapidly. In 2017, the global volume amounted to some 700 million US dollars, and in 2025 it is expected to break the three-billion barrier at an average annual growth rate of 26.4 percent.


Which milestones we can expect to reach along the way in 2019 are outlined below.


Trend 1: Improved customer experience  

Current studies convey an unambiguous message: It has never been more challenging to satisfy customers than it is today. And never before have there been so many outstanding ways to do it. For example, 79 percent of consumers expect to be fully supported by a company before making a purchase decision. At the same time, 84 percent of companies that focus on improving the customer experience report significant revenue growth.


With insight engines, call center employees and support desks have all the information they need at their fingertips so they can respond immediately and concretely to customer inquiries without having to be experts themselves. In 2019, insight engines will also rapidly become more important for the self-service systems available to customers 24/7. By automating the generation of knowledge and the ability to interact in natural language, a high level of customer experience can also be achieved at night and on Sundays and holidays.


Trend 2: Combining the forces of digital disruption, innovation, and transformation

Insight engines not only have the power to automatically generate knowledge from existing data and information, they can also create new knowledge. They do this indirectly, on the one hand, by relieving employees of busy work tasks, thereby freeing up resources for innovation and creative ideas. And on the other hand, insight engines contribute directly to obtaining new insight, which is primarily achieved through the disruptive deep learning technology.


Market researchers expect the deep learning market, which currently exceeds two billion US dollars, to climb to 18 billion US dollars by 2023 – with an average growth rate of a whopping 41.7 percent. While deep learning and machine learning are mainly used today to optimize internal processes (see the next trend), they have the ability to create predictions with unprecedented accuracy based on advanced analytics. In turn, these predictions form a solid foundation for new business models.


Trend 3: Insight engines support business process transformation    

Today’s business processes are typically the target of optimization measures. Thus, for instance, the incoming mail is digitalized, but the associated process is left unchanged. Insight engines, however, possess capabilities that remodel processes from the ground up, thereby transforming the process. One example of this is the insurance industry. While there are currently plenty of large customer service teams who are busy with nothing more than laboriously recording claims, insurance companies that rely on insight engines can achieve radical simplification. With the help of automated image classification, in the future the policyholder will simply send cell phone pictures of the claim, his or her passport, and the policy so that a new file can be created and the next steps can be initiated. If questions arise, the agent can intervene and – thanks to the automation of routine processes – have more time to devote to complicated cases.


Developing this principle further can create new opportunities for lead generation. Using automated image recognition, a maintenance company specializing in aviation, for example, can find out about a defective aircraft as soon as the associated picture is published in social media, and can then contact the airline concerned, which for cost reasons usually doesn’t have its own team of technicians. And in most cases, the first contact is the one who gets the assignment.


Trend 4: Conversational user interfaces give artificial intelligence a human face

Today’s standard chatbots are generally not perceived by consumers as being intelligent or helpful. As a result, companies are investing more and more in technologies that elevate customer interaction to a human level. According to IDC, so-called conversational agents currently make up a market of 12 billion US dollars; by 2022 that figure will soar to 28 billion. 


In 2019, companies will increasingly realize that insight engines provide the optimal basis for intelligent interaction with customers. These technologies, such as natural language processing (NLP) and natural language question answering (NLQA) – both sub-areas of artificial intelligence – are used to conduct dialogues in natural language. For example, when a customer asks who Francis Bacon was, he doesn’t just get an endless list of links, but rather an immediate answer: “English philosopher, lawyer, statesman, and pioneer of empiricism.” The context of the questioner was correctly interpreted and the information was then semantically processed.     


Trend 5: Innovative insights into company-wide information create new knowledge

Right now, information about customers, issues, processes, and physical objects is usually parked in so-called silos, for instance in the form of e-mails, documents, and data records from various company applications. Insight engines create a kind of bracket across all data sources, while keeping the data right where it was generated – in stark contrast to the method of traditional knowledge management systems.


Analogous to the current IoT and Industry 4.0 trend, in which machines at a production facility, for example, are networked and can thus provide new insights into performance and status, insight engines create a powerful instrument that can be described as “Unified Everything 4.0.”


This gives employees a 360-degree view of customers, issues, processes, all the way to individual components, from which they can derive new insights. In addition, it enables companies to create virtual representations (“digital twins”) that can be used for simulations in product development, process modeling, and marketing. Digital twins represent a rapidly growing market: With an annual growth rate of 37 percent, the 15 billion dollar threshold should be reached by 2023. 


Trend 6: CEOs take the helm

In the past, digital transformation was often seen as a purely technical issue or was delegated to marketing and human resources departments. However, more and more CEOs are realizing that access to and intelligent processing of data is crucial to their business. Some two-thirds of German business leaders confirm this. 


As a result, CEOs in 2019 will be stepping up their efforts to focus on digital transformation and the technologies associated with it. Insight engines provide them with an instrument that not only enables them to steer the transformation strategically but also gives them the means to make decisions in the operative business that are backed up by knowledge and secure information.  


The bottom line: “Knowledge is power” is more valid than ever

Insight engines consolidate the key aspects of the digital transformation under one roof. They not only help to bundle the data scattered throughout the company in order to generate knowledge from it, but also provide a reliable basis for looking to the future. This will benefit management, employees, and customers in equal measure, as insight engines increasingly move into the focus of strategic activities in 2019.