The requirements are demanding, individual and personal, up to date and consisting of modern technical standards and in all this showing immediate results – our digital era has led to business activities in which customer communications take centre stage, demanding a great deal of rethinking from companies of all sizes and segments.
Long before the breakthrough of artificial intelligence (AI) and robotic process automation (RPA), managing communication with clients was a rather simple task. Contacts were made telephonically, concerned users called the helpline about small issues and posted a letter whenever more details were necessary. No other touchpoints were employed. Another major difference compared to today was the extended period it took to solve the task. In former times, it was solely dependent on the company to decide the time span. This went on until the Internet pushed its way through. Thanks to digitization, the power has shifted and now the clients have their say! Consequently, customer service procedures were turned upside-down and had to be rethought.
Banks like in most other business, the customers are now more demanding than ever. With the rise of smartphones, Amazon’s Alexa, Social Media, and the growth of self-service options both online and at ATMs, there’s now an expectation that consumers should be able to complete major banking activities whenever and however they want. Banks are now under pressure to improve and offer more channels. But in today’s environment, simply having an online banking solution or self-service options in the contact center is not enough, and this is where banks that have not yet fully embraced OmniChannel need to do so.
Around the world, there are numerous jobs that require human beings, be it for creative or consulting tasks, or issues requiring intuition and contemplation. In these cases, AI software can only be helpful by diagnosing circumstances and supporting human labor. Experts are in agreement that cognitive software will influence modern digitization in a similar way to how steam engines impacted industrialization. According to the IDC, more than half of all company software applications will be equipped with artificial intelligence in the course of 2018.
As far as intellectuality and cognition are concerned, so-called ‘knowledge workers’ play key roles in modern enterprises. For knowledge workers, contributing to a successful business by forming and implementing their concepts is often considered a lifelong task. As analysts have predicted an increasing skills shortage for years to come, companies are trying their best to counteract any adverse effects. The ‘war for talent’ entails new ways of finding and keeping the necessary talent for company plans.
We often associate big data with research problems that are important to humanity as a whole – problems like human evolution, energy sources and cancer. To process big data, we often think that one needs big iron like computer nodes, scale-out storage and parallel systems to compute the massive amounts of data.
There is no way to deal with data processing in daily business without coming across document and mobile capture. But when exactly is an investment in the proposed solution of smart data capture profitable – or even essential? And how do the applications wield influence over following processes once the initial handling has been completed? A compact overview with all the relevant information is provided in trade group Bitkom’s significant guidelines.
Despite rising digitization, numerous enterprises are experiencing increases in their expenses as well as inefficient processes. Some of the issues include manual data acquisition, permanent switches between different applications, media disruption and more. Robotic Process Automation (RPA) could be the solution to these complex problems if it is deployed in the right way.
Often, when we think about big data, we think about the volumes of data that are referred to. It is tempting to do this because big data does involve large volumes of data that are constantly growing at exponential rates. Advances in the growth and development of big data computing constantly dominate the news. It takes advanced software and BI tools to even begin to comprehend the volume of certain measurements, such as petabytes and exabytes.
Most of us have heard about it, but are we all able to explain what it is? Robotic Process Automation (RPA) is based on artificial intelligence. A wide variety of definitions have been used to try to predict its effect on years to come in business and privacy. People do not tire of discussing possible future changes, with both skepticism and emotion. So, what exactly lies behind the terminology, and in which way can RPA improve our future workflows and processing?