Truth be told, we experience self-service every single day of our lives - when we buy shoes online, withdraw cash from an ATM, self-checkout at supermarkets and more. And this model’s growing popularity makes it obvious that a growing number of tech-savvy, self-reliant customers, including the millennial generation clearly prefer the do-it-yourself model.
According to Gartner, by 2022, 64% of customer service interactions will be self-service enabled, and an additional 21% will include some level of agent-assisted self-service. This points to the powerful insight that consumers are increasingly expecting to, without brand intervention, solve most issues on their own.
For the sake of this article, let’s narrow our focus a little. I’d like to discuss how the ‘self-service’ concept has been accepted on the workspace front, and in this context, the phrase; ‘revolutionizing employee productivity’ is oft-repeated.
According to a Paychex report, 80% of employees want self-service tools to be more productive in the digital workplace. Organizations take their cue from data points like these and have been investing in enterprise products to manage the scale of operations and self-service mechanisms.
The belief that most organizations start their self-service journey with is; deploying huge enterprise systems will work because employees will log into systems to have their requests served. Interestingly, a Forbes article quoted industry analysts on how such a model leads to a system overload that eventually ends up undermining business productivity.
AI sandwich for real-time data processing
A connected issue (system stress), and perhaps the real struggle when deploying these enterprise systems is making data available in real time. Enterprises can battle this issue by evolving a ‘pre-emptive customer service’ approach because as per a Forrester report on customer service trends, operations will only become smarter and more strategic, and companies will only continue to explore the power of intelligent agents powered by conversational interfaces.
The nature of these agents is to anticipate needs by context, user preferences, prior transactions and thus deliver pro-active context. And, while contextual relevance evolves on one end, the rise of natural language processing and near-natural mediums like voice and gesture will create intelligent self-service experiences.
For employees who are constantly working towards intuitively engineering customer satisfaction, this era of self-service at the workplace is definitely something to look forward to - on-demand information assistance at a time and place of the employees’ choice combined with real-time, feedback, and no compromise when it comes to security standards.
The expectation is that workplace service intelligence will handle routine tasks, which will empower people can focus on operational optimization, creative design, forecasts. That expectation, however, calls for a pretty big cultural shift. Especially in the case of how operations teams are structured and function, there will be the need to negotiate the path of least resistance by letting go of routine tasks, up-skilling, and organically including data into daily routines and decision making.
Given the impending explosion of tech and tools in the workplace self-service realm, here are a few predictions of how self-service powered by mega-trends will transform the workplace and make it future-ready.
Megatrends driving the workplace self-service revolution
Consumers don’t want to be sold a promise; they want to experience it. Soon, prospective employees will enjoy an enhanced Virtual Reality, VR experience of the company they want to be a part of. AI and ML powered tools will target specific candidates, intelligent assistants while will manage interview schedules, handle initial candidate screening, collect feedback and assist with decision making.
At Thoughtworks, we have a built a pre-screening interview bot that supports a role-based first level discussion. This approach is especially effective when combined with the first round of interviews.
VR tech will not only allow new recruits to meet and greet with leaders from across company locations/offices but also make every employee’s first day that much more memorable. The tech will help employees navigate the organization for information, people and resources. Guided AI personal assistants will aid newbies using a customized planner based on the latter's' role, skill, experience, etc.
Thoughtworks has built an office tour experience for new joinees. This experience runs on AR and VR gadgets. They help new recruits learn the lay of the office. This was practical and also checked the ‘cool tech’ quotient or many.
Learning and Development
The 4E’s (Education, Experience, Environment, and Exposure) will be one of the many principals that are being adopted when developing VR assisted training programs. The learner’s behavior will determine recommendations and content that will be perfectly suited to the employee’s interest-based career growth. Increasingly, AI solutions will also provide for flexible learning styles; on-demand, customized plans, multi-format learning, etc.
Conference systems will provide live translations to ensure seamless collaboration within distributed teams, intelligent assistants will manage schedules, and voice assistants will provide an enhanced no-touch meeting experience. Apart from this, ML and VR will be deployed for a day or week-long workshops or knowledge sessions.
Perfect user experience amounts to how quick and simple a task is made. In that line of thought, it will be intelligent virtual assistants powered by NLP who will become the one-stop-shop for all self-service related services. Everything from information on policies to leave management to updating of employee records to planning task lists to managing work-related travel and stay bookings to IT hardware and software queries to handling reimbursements and claims. The list is virtually endless!
Thoughtworks built an NLP personal assistant to help with employee productivity requests that dealt with leave, vacation planning, employee expenses, queries on HR policies, and for IT support. However, it’s only been with the IT helpdesk that we have seen a 60% of tickets raised being responded to. Automated ticket triaging reduces the cycle time from 24 hrs to 1-4 hours. This NLP assistant was built as a part of the enterprise ‘@Chat’ platform and has a user base that’s close to 90% of the current employee count at the company.
The expectation is that one is surrounded by smart and connected devices at all times. Employees workspace will be powered by IoT solutions like hardware self-service kiosks, finding the nearby printer, and automated physical access to all worldwide office premises. Intuitive mobile apps and AR will help new employees or first timers to other offices with indoor navigation. No-touch meeting rooms, energy conserving hardware will usher in a greener environment.
A few Thoughtworks offices around the world are equipped with personalized facial recognition software for entry. IoT sensors in every meeting room manage occupancy-based room availability, room booking, and lighting. The Bluetooth Low Energy, BLE based infrastructure leveraging beacons across all offices have enabled self-service for IT operations at scale without increasing OpEx cost.
Staffing for projects
AI-based assistants will recommend project/project information based on employee’s interest area; intelligent dashboards will recommend team compositions to staffing managers. ML will predict unbiased patterns in employee interests, performance, feedback, preferences, and business forecast.
Thoughtworks built an experimental recommendation engine for the staffing team, that draws up possible team compositions based on employee availability, experience, location, etc. The engine helps staffing managers with dashboards in a matter of minutes. It usually would take between 6-8 hrs to build initial team compositions. The engine also visualizes different team compositions real-time, which helps with quick decision making.
Essentially, self-service scores high on scalability, thus the transformation of a workplace is as a whole making the experience collective and ‘un-siloed.’ And, these ‘delightful’ moments are of increasing importance in every employees’ journey or work experience. Automation and service intelligence will enable companies and their employees to be more empathetic and to focus on other high-value agendas like customer experience, employee engagement, client relationship management, data-driven decision making, and workplace culture.