Automation and robotics are here to stay and are becoming increasingly mainstream. More than just IBM’s Watson and its appearance on Jeopardy or a tax authority’s assessment of returns, automation and robotics are being applied to call center engagements, engineering and maintenance, delivery, sales, and customer research and service functions. Add to this the growing volumes of information available, particularly from the emergence of the “Internet of me,” and one can see the worlds of data and robotics colliding to drive us closer to “god from the machine” scenarios – and the substantial opportunities that exist from a commercial, productivity, and service perspective.
The Internet of me
With every generation of users, the Web is becoming more personalized. This evolution has created virtual hubs for people to connect and share thoughts, ideas, and work. From BBS to Geocities to Yahoo to Facebook to Twitter and YouTube and FourSquare, the individual is increasingly at the center of these virtual hubs, which are built around features, capability, and services targeting the creation of knowledge around the individual. A noticeable shift is under way from the Internet of us to the Internet of me.
In the past, users regarded the Internet as the source of knowledge for certain topics, news, and interests. This focus has now shifted: Individuals are increasingly the topic of interest and the hub of information flows, and the Internet is little more than the vehicle for the movement of this information.
Many of the elements that make us unique are becoming digitized through the use of data-capture interfaces such as Fitbit, Apple Watch, and Whereis, as well as “older school” ones such as Facebook and Twitter. Such data capture will include what we see, what we say, what we are doing, our physical state, where we are, whom we’re with, and what others think of us, all the way through to what we are thinking. This digitization is not only disrupting our personal lives, but the way we work (nearly 60% of employees use two or more devices on a daily basis for work), and by proxy a large number of industries, as users and knowledge workers increasingly impact the next generation of employment. According to a recent Ovum survey, digital channels are the second highest-priority SaaS investment area in banking in the next 18 months.
This translation of the analog physical person into a digital set of bits and bytes is set to unlock new business opportunities, will disrupt the established way of doing things, and is likely to open the door to the next horizon of personal digitization – a full 360-degree automation of a person’s interactions.
Automation (and robotics) are the natural progression
Leveraging the power and the benefits of the digitized footprint is becoming an extremely brisk area of investment. Although the amount of investment in automation and artificial intelligence is relatively small, the advancements in these areas have lowered the barriers to investment for those with a vision to transform new ideas into reality. Automation of these digitized footprints is the next natural step, and it will become a core capability over the next number of years.
IT environments have already seen an increasing degree of automation, with the aim of simplifying complex infrastructures, offsetting the potential of increased labor costs, and reducing the provisioning gap between business demand and IT supply. As cloud adoption progresses, this automated provisioning will be critical to support workload flexibility across hybrid cloud and on-premise environments.
We believe that over the next decade automation will quickly extend into the business process layer, and then into operational decision-making. Today, we are in the early stages of fully automated processes, with the adoption of software robots to augment or replace human actors in linear process scenarios. This is likely to extend into a fully digital approach to a wider range of both horizontal and industry business processes. However, as we mature and scale, the integration of artificial intelligence tools will be the main conduit for reaching scale in business process-centric approaches.
In more complex areas of business, cognitive techniques based on machine learning are being used to build expert support systems that can augment human decision-making. These will increasingly be embedded directly into business applications as their accuracy improves and users’ trust grows. The ability of these systems to extract insight from a huge volume of structured and unstructured information drastically outstrips what humans can do in this regard. The argument will continue as to how far the boundaries of automated expert decisions can or should extend, but there are already proven use cases for machine learning in expert decision support in domains such as healthcare and financial services.
Integration of innovative process-automation approaches, in particular artificial intelligence, will evolve as a key stage in the market scenario in the short term.
Future iterations of this approach will likely include use cases such as Amazon’s use of drones for delivery and Uber’s use of automated cars. Looking yet further ahead, one could start to expect us to have access to unlimited memories, full awareness of all the world’s knowledge, and instant access to experts across the globe, and the vast majority of data will become less textual and more visual.
The appeal of automation lies in the combination of cost reduction (which often justifies the project) with the ability to deliver value-added services in the form of pre-packaged solutions and processes, as well as the ability to analyze, map, learn, and target customer-centric processes.
In the banking sector, one of the world’s largest banks uses automation in its back offices, enabling it to rapidly scale its ability to process certain customer requests in response to customer demand. The bank has automated a range of processes, from fraud detection and risk monitoring to the automation of account opening. Another bank, the Co-operative Banking Group, has also automated over 130 processes including complex CHAPS (Clearing House Automated Payments System) processing and Visa charge-back processing, alongside other back-office processes that support sales and general administration.
Disney provides another example in the world of entertainment. With an initial capital investment of $1bn, Disney’s MyMagic+ program will offer a tailored geo-targeted entertainment service portfolio across the individual customer lifecycle. The wearable MagicBand will provide a single point of contact for customers (i.e. an access and payment tool for Disney theme parks) and enterprise data repositories (providing click-by-click customer behavior metadata).
The key for organizations will be to ensure that their digitization strategies and associated execution considers and addresses not only the technological requirements, but the human/cultural inputs, principles, and demands. Putting such structures in place will enable the next step of driving the levels of automation available. Such steps are required to ensure that cognitive decisions, based on machine learning, can lead to the creation of the rules that drive business processes. These will also provide the launchpad to enable the dynamic provision of new capabilities and a flexible and scalable platform.
The narrative in the automation world should move beyond its current focus on replacing FTEs (full-time employees) and saving short-term costs to addressing the essential transformation of knowledge management work and realizing the value associated with understanding the multitude of opportunities and how to best leverage them.
If they haven’t already done so, enterprises need to evaluate automation approaches that apply to their specific situation and should not be afraid to take a smaller, piecemeal approach to help build up levels of comfort. This will be contingent on where enterprises are on their journey toward standardization and industrialization, and the maturity of their service delivery model. The opportunities include low-hanging fruit that can be reached simply by implementing automation tools, but also by using organizations such as Deutsche Bank as a reference point for formulating a vision for their service delivery models.
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