Cameron SmithCameron SmithAugust 9, 2019
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8min2164

At its best, science fiction taps into our contemporary anxieties to predict the fate of humanity.

An episode of Doctor Who, for example, featured robotised mega-corporations, human irrelevance, and despair. The Doctor may be sci-fi fantasy, but the issues are real.

Artificial intelligence (AI) technology is reshaping many sectors – for both good and ill. Gartner predicted that artificial intelligence would generate $1.2 trillion in business value in 2018 – an increase of 70 percent from 2017. But on the negative side, it creates much anxiety about the elimination of jobs, and prolonged focus on the cost and job-cutting aspects of AI has overshadowed how the technology can help human employees.

The CX example: how tools can hinder trade

In the customer service sector the rise in AI, decision-support, automation, and chatbots has exploded across the industry, driving multi-channel customer experience (CX). But adoption of these technologies for employee engagement has been slow. Contact centres have some of the highest employee turnover rates in the world, and there’s been troubling analysis suggesting new technology is inhibiting employee performance, engagement, and satisfaction.

Gartner analysis reveals service representatives use the mindboggling average of 8.2 different systems and tools during a customer interaction. Small wonder, then, that talk-time is up nearly 14 percent while call volume has remained the same.

We have amazing systems driving less-than-amazing experiences for the people charged with using them. A primary source of the problem stems from something obvious. We’re measuring the wrong things.

Just exactly what should we measure?

In our rush to capitalise on AI technologies, we’re failing to evaluate the way they ultimately integrate into human workflows. In the customer service sector, technology is better at handling many discrete tasks but does not replace human representatives.

It’s becoming standard practice, for example, for companies to host automated, largely self-service interaction options for customers that are always available. Digital account portals supply constant access and handy personalisation capabilities, while well-designed chatbots and virtual assistants are excellent at taking orders, payment processing, status checks, or informational queries.

But for more complex requests that require human nuance and context, technology-enhanced services can complicate the situation. When dealing with the customer, human agents are at a loss without access to what transpired during those digital interactions. And even when human agents can access those systems, they shouldn’t be flipping back and forth between applications and databases while attempting to deliver proper support to a customer.

This problem is perfect for AI solutions. Analytics engines that deliver historical and/or relevant customer information to support agents automatically and in real time can speed rather than delay productive conversation. Natural Language Processing (NLP) systems recognise spoken keywords and supply agents with useful prompts or notes, sparing them from app fatigue and task-switching. Virtualised on-demand training systems can keep them stimulated and engaged.

This employee-centric AI deserves more study and development. Systems that aren’t generating a positive Employee Experience will negatively affect the Customer Experience they deliver. Exploring ways AI can better serve employees is the solution. And measuring how employees view these tools should be the first metric for success, not an afterthought.

Collaborate to work out what best to measure

Applying AI to better serve the employee is crucial, but should be measured and managed with caution, given the enormous amount of data available.

One of the greatest struggles from an AI development perspective is determining how often a system should prompt the employee and whether there should be a trigger. Can such a mechanism be ranked? Do we allow the employee to turn off certain notifications because they’re annoying?

There’s a risk of overdoing AI assistance for Employee Experience. It could get very frustrating, very quickly. The only way to arrive at balanced employee-centric AI application is through collaboration. The people using the technology should have representation at the development table, which is also an excellent way to increase job satisfaction.

The future will require us to adapt what we measure

As AI technology becomes integrated into the enterprise, we must adapt how we gauge human performance. In CX management, technological innovation dictates that businesses restructure how they view customer contacts and the human staff who perform those jobs.

Contact centre positions will no longer be entry-level or outsourceable roles. With automation handling all the basic contact tasks, human customer service becomes a more specialised profession. Savvy and emotionally intelligent customer service employees with thorough understanding of a business and its technology will be a necessity. They’ll be managing only the most important, complex, or delicate customer concerns.

Today’s metrics, such as talk-time or calls-per-hour, provide little quantification under such circumstances – but the quality of this work will largely determine a company’s reputation among human beings.

And that’s not science fiction!




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