Tag: bots

Five Ways to Reduce Contact Center Costs with Automation and Chatbots | Sherpas in Blue Shirts

Everest Group’s recent research revealed that successful adoption of RPA and chatbots in contact centers can reduce the total cost of contact center operations by 11-16 percent. Yet, very few enterprises have achieved these levels of automation-driven cost reduction in their contact center operations. Why? Technology is just one piece of the puzzle. In order to unlock the true benefits of automation solutions in your contact center, you also need to focus on organizational readiness, effective change management, and better governance mechanisms.

Five ways to reduce contact center costs with RPA & chatbots


Analyze and select the right processes for automation

Enterprises should start by identifying the contact center processes that are most suitable for automation. To achieve breakeven in quick time, it’s best to start by automating highly repetitive and less complex business processes with RPA. For example, a process wherein agents spend exorbitant amounts of time navigating through multiple systems and applications to fetch the required information is ideal to automate with RPA.

Re-engineer business processes before automation

Automating business processes that aren’t standardized or simplified can result in more exceptions. But optimizing them before automating them, with IT and operations jointly looking at them through the RPA lens, can greatly reduce exceptions. Learnings from best-in-class RPA implementers also suggest that business process re-engineering is a significant step to realizing the strategic objectives of RPA adoption.

Build winning partnerships

Building a partner ecosystem with leading RPA technology vendors and/or system integrators that offer best-in-breed automation platforms and specialized domain expertise is crucial to achieving successful RPA adoption. Doing so can help enterprises save time and effort at every stage of RPA adoption, which eventually manifests in effective cost savings.

Make a quick transition from pilots to large-scale deployments

Enterprises that achieve significant financial impact and rapid return on their RPA investments quickly scale-up from the pilot stage to large-scale deployments. To move fast successfully, it’s important to foresee challenges ahead while in the pilot stage, and begin mitigation efforts earlier. Enterprises can also follow an agile implementation approach, which could enable their RPA deployments to quickly and flexibly adapt to changes in business requirements or underlying applications.

Integrate RPA with chatbots to achieve incremental cost reduction

Once RPA has delivered some quick wins, enterprises can deploy chatbots alongside RPA to realize incremental cost savings. For example, chatbots can resolve less complex customer queries more quickly when RPA bots fetch the necessary information and relevant insights from multiple systems and applications. Enterprises should envision building a digital workforce with both RPA and chatbots in their contact centers to achieve long-term benefits that can extend well beyond the incremental cost savings.

Adoption of best practices for contact center automation can help enterprises achieve tangible business outcomes. And the returns can be quick: our latest research shows 9-15 months with RPA, and 18-24 months with chatbots adoption.

To learn more about how you can build a successful business case for automation adoption in your contact center, check out Everest Group’s recently released report: The Business Case for RPA and Chatbots in Contact Centers.” And, please feel free to share your automation adoption experiences in contact centers with us: Katrina Menzigian ([email protected]) and Jayapriya K ([email protected])

Enterprise Challenges in Bot Adoption | Market Insights™

Entrprs Bots Adptn-challenges

In today’s digital world, automation and user experience have become critical for enterprises. Bots – which drive operational efficiency and facilitate consumer engagement – are central to the strategy of any forward-looking enterprise. However, as these bots proliferate, enterprises face significant challenges.

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AI: Revisiting Future Shock | Sherpas in Blue Shirts

In his 1970 book “Future Shock,” author and futurist Alvin Toffler made the argument that the modern world disorients people as it creates so many overwhelming changes that we are unable to handle them. Almost 50 years after the book was published, I was struck by Toffler’s argument during a recent client engagement in which we were helping an enterprise identify virtual agents/chatbots for its customer-facing processes. All of the bots contained a healthy dose of artificial intelligence (AI), and each one was trying to push the envelope.

Is AI starting to overwhelm people to the point that they may get frustrated with developments they cannot fathom or use?

Every day we see and read about new use cases that “wow” us. We are amazed and bedazzled by advances in AI. And some are becoming increasingly commonplace in the consumer arena…just think smart homes.

On the flip side, there have been instances in which consumers have found dealing with these omnipresent home devices scary and frustrating. Humans have already strongly voiced that they don’t need bots to shop. And, feeling the need for peace in their home, they have switched off many of their home assistance devices.

Some may argue that the technology industry, driven by the high intoxication from the ivory towers of Silicon Valley, is getting way ahead of the people who are expected to be the eventual consumers of these technologies. The amount of new AI research and products coming every day out of these factories is mind numbing. A significant number of such products may not have any immediate utility, but they do indeed demonstrate the far-reaching power of such advanced systems.

There is an unending scare around AI, cognitive, and other advanced systems taking away jobs from human beings. In the case of virtual reality, people are entranced by engaging with virtual objects as if they are real. It’s fun, until they realize the negative impacts it can have on their day-to-day lives. And, instead of assuaging such fears, the technology industry continues to create use cases to replace human tasks with robots.

From an enterprise perspective, organizations need to proactively create an AI adoption strategy for their business. Though most now have some vision around using AI technologies, frighteningly few are preparing for the massive change management aspect. Their employees must be comforted around the impact AI can and will have on their lives. Indeed, the significant disruption AI technologies can create within a business context may require a very different approach than other technology adoption we have ever witnessed. Technology vendors need to focus on how AI-enabled systems are assisting or helping human beings. The use cases need to be very precise, clear, and friendly, not overwhelming and complex, which they currently are.

The problem is not AI technology. The problem is the way it is being introduced, and the hyperbole around it that may end up overwhelming a significant portion of the human race, leading to eventual burnout. We are humans, and should create technology for humans. If the very technology we create results in alienating a large percentage of us, we will have failed as a human race. AI systems need to be leveraged for enhancing human lives, not for creating technology marvels that overwhelm people and create the future shock.

AI Bots for Strategy-in-a-Box? This Is Not a Google Problem | Sherpas in Blue Shirts

Most, if not all, of us rely on some form of Google search these days to accomplish our tasks. And because of its ease, we tend to be unwilling to say no to questions because we know we can Google to get the answers. By proxy, this has deluded us into believing we are “experts” on everything.

Bots for strategy-in-a-box
How does this relate to Artificial Intelligence (AI) enabled-bots in a business strategy context? AI is disrupting every walk of the life. The likes of Google (Alphabet) DeepMind, Facebook FAIR, IBM Watson, and Microsoft Cognitive Network Technology are demonstrating increasing use cases by the day. All these platforms crunch massive amount of data to become intelligent over a period of time.

As strategic decisions and long-term initiatives require huge amounts of data to be churned, AI bots are ideal candidates to assist, particularly because it’s not humanly possible to keep track of the multitudes of parameters that must be factored into development of a business strategy in today’s environment. Thus, strategic leaders may have to rely on a second “expert” going forward…an AI-enabled machine expert, that is.

Can the data crunching go so far that enterprises won’t need strategic leaders at all anymore and, instead, will be able to pretty much leverage a virtual agent to create their business strategy? Can this data crunching make the bot a strategy “expert” that can design a strategy out of the box?  Let’s step back for a moment.

Who needs a 10-year strategic plan?
I have argued multiple times that the days of creating a long-term enterprise strategy are well over. Given business and technology disruption, it is becoming impossible to see beyond your nose, forget 10 years. Can an enterprise afford to create a 10-year strategic plan? Can any business leader put her hands on her heart and say she believes in that strategy?

I doubt any enterprise can make that kind of long-term commitment. While a long-term vision used to be the differentiator between a great company and its peers, the differentiation point is quickly becoming how nimble the strategy is to incorporate and adapt to the rapidly changing business environment. Such a dynamic strategy needs to be built on massive amounts of data that incorporates parameters, including disruptions from outside a given industry, which the human mind cannot fathom. For this, enterprises need AI.

Back to strategy-in-a-box from a bot
If the above is the case, should an enterprise opt for a strategy-in-a-box rather than a strategic planning exercise? Can a bot create an enterprise’s strategy roadmap sans business leaders or maybe with just a little help from them? This may sound far-fetched, but it is certainly possible.

One can argue that strategic leaders rely on their experience, intuition, and other factors beyond data to make decisions and create an enterprise vision. While this experience and intuition were valuable when the business environment was largely stable and “known,” in the rapidly changing world these “assets” could be counterproductive. Strategy leaders experience will continue to hold value but less than what is generally thought.

If the enterprises do not need or can’t afford a long-term strategy in this rapidly changing world, why would they need the experience and intuition of strategy leaders? How is this experience that was accumulated in the last 30 years relevant for the coming years in such a fast changing technology environment? Moreover, an AI-enabled bot can possibly compensate for some of this experience and intuition through other parameters such as correlating seemingly uncorrelated data.

Adopting bots as a fulcrum of strategy development may go against the general perception that AI-enabled systems will augment, rather than replace, human powers. I, for one, don’t buy that “enhance human” argument entirely. In fact, humans may be assisting machines to make better decisions, rather than vice versa.

I think next-generation AI, automation, deep learning, and cognitive systems will definitely result in job losses, and we should be prepared for it. The argument that technology in the long term helps create more jobs has been sugar coated, and no one talks about the fact that disruption can create havoc in the short term. And people being impacted by this mayhem see no long term.

However, this is a reality from which we cannot escape. Enterprises need to ensure they are using AI as much as possible in their strategic planning. Believing that AI is only suitable for basic tasks will set them up for disaster.

Therefore, enterprises should not confuse AI-enabled bots as “experts” who rely on Google… “experts” who may not know but still answer. AI-enabled bots will be credible experts who rely on data, massive data, and their own intelligence.

The bottom line is that while your enterprise may not yet be ready for an AI-enabled, bot-developed strategy-in-a-box, you must take baby steps toward that future.

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