The happy workplace is always the home of the productive workplace, filled with a lot of talent around. Millennials being part of this productive workplace are transitioning from process-centric interface to consumer centric interfaces, basically the interfaces employees are familiar like messaging interfaces, touch interfaces, voice interfaces etc. In many organizations the new trend of “Elevated employee experience” is gaining traction, to attract greater talent within the millennial pool.
The 2018 Gartner Emerging Technologies Hype Cycle showed smart workplace, virtual assistants at the peak of expectations and the tech which will revolutionize the industry for the next 2–5 years. Also, Gartner highlighted a trend named “Democratized AI” that highlights AI as one of the most disruptive classes of technologies, which got a major impact with scale and its availability to the masses.
According to a Mckinsey report, about 10 hours per week on average, is spent by an employee for searching and gathering information. Today’s typical enterprise till has 100’s of internal apps and 10’s of huge enterprise systems, which are used by employees to communication and for productivity gains. Every enterprise of this nature really needs a transformation from “Maze” model to “Real time” models for the millennial workforce to be productive, which is powered by AI (NLP+ML) engines connected to all corporate systems.
Also in recent days, decision makers in the organization are looked up for making their teams smarter to handle the scale of operations and to provide consumer centric experience. They are looking to introduce smart technologies as a standard, allowing employees to access anything at anytime and on any device. With this, Virtual assistants/Intelligent Chatbots are becoming a crucial part of every process, that currently follows a decision tree format.
Employees around the globe are excited to interact with their new “virtual personal assistant” skilled with Artificial intelligence (AI) powered by conversation interfaces and natural language processing (NLP), where getting on-demand assistance to information, when and where they need it. Employees are turning up to a new personal assistant to get their queries answered. Yes, it’s their assistant who never calls in-sick, sleeps or goes on vacation.
Here are the top 7 ideas to introduce virtual assistant at your workplace.
For operations team in any organization, the natural behavior for each wave of innovation and the first question being asked is “Is the goal to eliminate jobs. Am I losing my job.’’ It’s important that the operations team should be given the confidence that “AI assistants will act as an enabler with their efficiency and trained intelligence”. With AI, there will be a huge scope of service intelligence to handle routine tasks, so that people can focus on operational optimization, creative design, forecasts and plans for the future.
On the other hand for employees, the first question that comes to their mind is “Are you saying, I can’t interact with humans anymore and only interact with virtual assistants. Am I losing the personal care provided to me by the operation’s team”. To solve this ambiguity, the initial skills of the personal assistant should be chosen in a way that the employee feels a personal touch in the same way they have experienced by interacting with humans. Also, when the assistant doesn’t have the skills, it should do a smooth hand-over to humans.
AI has the power to create a compelling employee experience by building a strong relationship between operations team, IT and employees and thus enabling workforce transformation. Gartner’s latest prediction estimates that one in five workers will have an AI powered assistant as their co-worker by 2022.
“Introduce virtual assistants as co-workers, who will work along with humans”
In this new era of virtual assistants, many organizations start their journey of “Self-service” by building bots. As this trend started picking up, every operational function start building their own bots.
“This introduces a poor user experience and at some point of time, employees will need to remember a cheat-sheet of bot names for their requests, the side-effect is higher decline of user-base. Also, the overhead of maintenance of bots increases and also there is less content sharing between systems.”
Every organization should create and brand a personal assistant, so that it becomes an integral part of the employee ecosystem. For any productivity requests, be it related to people, recruitment, finance, IT helpdesk, corporate knowledge base, the assistant should be multi-skilled to handle all operational functions requests. This approach also helps in building an end to end journey for their productivity request.
Let’s take the simple example of reimbursement, where a multi skilled bot can help with highlighting the policy (people function) and accordingly raise a reimbursement request (finance). With this approach, the transaction is completely self-serviced by the virtual assistant handling the fulfillment between 2 different systems. To handle multiple skills, the assistant also needs to be suggestive by highlighting to the user “I found 2 mathcing requests for this. Did you mean this”.
“Build a multi-skilled, trained with suggestions and connected with corporate systems for end to end ful-fillment”
Enterprises start their AI journey, by building a “Task-bot”, which basically is the first step towards introducing AI. On the flip-side what happens is, as more feature requests flow in, its natural to miss the AI journey and continue being a “Task-bot”, automating user tasks. Gone are the days of task-bots.
Instead of focusing on task-oriented assistants, organisations should work toward building an individual AI helper that caters to all employee productivity needs and how it can help in a broader context. It would learn from individual actions in order to predict and personalize its responses.
For example, consider we are adding benefits and policy domain to the bot. The basic idea every team would start off is by referring to the relevant policy documents via the assistant. This is really a good start. But what we have noticed is, as the employee interaction grows, the popular user queries are “What is the overall medical coverage for my family”, “How much of dental claim can I avail my spouse”, “How many annual leaves can I avail”, “when can I plan my next vacation for 10 days”. These are more natural queries and NLP+ML powered virtual assistants can handle these types of requests. This is what I call it as intelligent assistant.
Assistant can become smarter by learning user patterns, providing contextual information based on working office, department, employee interests and expertise, 360’ feedback, matching employee interests with corporate opportunities, etc..
“Build a bot with NLP intelligence, so as to provide a more real-time information rather than task or rule based”
There are a lot of single-purpose products built to help people get through their work days: For example, Mark can schedule your meetings, Lucy can help you with market research, and Karl automates the candidate-screening process. So, building a bot app is more like adding this list, which attracts less user adoption.
The key success to drive user adoption is to build the virtual assistant in the existing enterprise chat platform. For example, if the enterprise is on google chat, the virtual assistant should be available on google chat. With this approach, there is no investment needed to drive user adoption. Also, there is no additional learning curve for employees to install a new app and use it. Enterprise platform features like infrastructure, hosting, multi-device support, mobile first approach etc, will be an added advantage. It’s not recommended to build communication bot in google chat, corporate search in skype, people bot in slack etc.
“Virtual assistant resides as one of users in the enterprise chat with no challenge to user adoption”
For any organization, legacy is an asset and represents the journey organization have sailed thru. The challenge will be how do you make use of the historic data? How do employees use this data or interact with the legacy systems.
The questions around poor productivity, re-invention of thoughts, valuable use of historic data arises, because its not easily accessible to employees and it doesn’t provide the expected user experience etc etc. To solve this, many organizations move towards rolling-out new enterprise products, which is one of the solutions, but it costs a bomb for the organization and introduces user adoption challenges.
Alternative cost effective and smarter solution would be to provide access to this data via chatbots. In the background there will be ML models which connects meaningful data from different enterprise systems to fulfill employee requests. Over a period of 1–2 years, this solution proved to be the best cost effective and best employee experience solution.
Virtual assistants at workplace are the omni-channel solutions which encourage conversations, interactions, non-linear collaboration, consistency and non-bias. Users may not this experience with a web portal solution.
According to Forbes, the future of conversational AI is enterprise. Intelligent conversational interfaces are the simplest way for the business to interact with devices, services, customers, suppliers and employees everywhere.
“Build ML models which connects meaningful data from legacy enterprise systems”
Self-reliant consumers:Led by millennial consumers, a growing number of tech-savvy customers clearly prefer the do-it-yourself model. Employee feedback will become increasingly real-time, in context, and meaningful. At the same time, people are becoming more and more willing to share personal information in exchange for a more personalized experience.
For example, let’s talk about the staffing manager in a firm. Staffing manager plays a key role in meeting demand vs supply. Plays a vital role in employee-organization relationship. To staff a role for a demand, there are quite a lot of data like tenure, previous project experience, feedback from peers, specialization, employee aspirations, previous staffing decisions etc. I would want us to imagine a world where a staffing manager asks the virtual assistant like “Give me options to staff a team with the “abc” constraints. The manager could even do deeper with options like asking the assistant “Tell me about the aspirations of employees 1”, “Setup time with employee 1 for a staffing discussion this week”.
On the other hand, employees could use the virtual assistants to find a suitable project for them asking the same question “Get me the list of projects suiting my aspirations”. In this case, the employee is more willing to share personal information in exchange for a cool experience.
As the personal assistant learns about the employee aspirations, interests, passion towards a topic, they will be able to suggest helpful services , push notifications and alerts based on role, location, technology, interest groups preferences, and more. For decision makers, I really want to believe in a world , where the personal assistant telling what the plan for the day, prioritizing emails, and answering common questions you receive by connecting programs and data individuals use and available on any device,
Reports estimate $8 billion in annual savings from chatbots, with 80 percent of businesses considering implementing them. Chatbots allow your enterprise to scale seamlessly with speed and alleviates from the limitations of human resources . Early Technology adopters are replacing standalone web portals with interactive chatbots.
“Create a more personalized, pro-active experience, at anytime on any device“
Today’s modern companies are now seeking ways to make their workplace environments more connected and intelligent. The good new is IOT based sensors, bluetooth powered beacons and low power high efficiency ARM based devices has already paved the way into enterprises to make this workplace connected and intelligent.
Let’s consider these example, where an employee is looking for a printer ; When an employee visits a different office and looking for a discussion room, with IOT, the solution is to provide an indoor navigation map from employee’s current location. Many organizations deploy meeting room solutions and hardware solutions for indoor navigation to achieve this experience. But these solutions are really expensive, not scalable and expensive hardware like tablets gets outdated as the technology revolutionize.
This is where AI, Data and IOT sandwich provides a unique and seamless employee experience. For both examples discussed above, about printer and looking for a discussion room , introducing conversation interfaces takes the conversations to next level. For example a conversation flow would look like, looking for a discussion room — [assistant provides a closest discussion room and triggers booking] — Employee confirms booking — [assistant books and provides an indoor navigation map]. With this experience employee don’t need to use one tool for booking, one tool for navigation.
Using this sandwich, the whole concept of self-service for hardware’s could be revolutionized. For example, we will able to provide employee experience like, when an employee needs a laptop, monitor or any other device, the employee just needs to converse with his assistant , without any need to raise a support ticket, wait for agent’s response, delay in fulfilling this request.