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When it comes to artificial intelligence (AI), a common misconception I see in the tech industry, especially in Support organizations, is that AI is a way to reduce headcount and cut costs. I believe that is the wrong conversation to be having when it comes to AI in Support Services. The right conversation to have should be about examining how the prevalence of AI and machine learning will enhance and evolve the employee experience.
As leaders, we need to look for the ways in which AI can be used to automate the mundane, repetitive parts of the current Support roles and create new and challenging roles for the people within our organizations. Tasks within roles that are leading to low productivity, repetition, manual, and non-satisfying work are the key areas to focus on as AI projects are undertaken.
While it’s true that not all roles can be automated, we should be looking for what parts of the roles that can be automated. As an example, the parts of Support roles that require “people skills” are not going away, and it can be argued these are becoming some of the most critical skills in the current experience economy.
My esteemed colleague, John Ragsdale, and I delivered a three-hour Virtual Summit called, “Leveraging AI to Automate Support,” which you can listen to here. During this summit, we released the E-Pyramid for AI in Support.
We outlined the need for Support executives to address each “E” in the pyramid in order to fully harness the power of AI for their Support organizations. TSIA recommends focusing on each “E” in a series of focused steps, which include:
The first “E” may be the hardest to tackle—Expectations. We have all heard it before, expectations equal trust. “I expect you to have your project plan submitted by tomorrow morning,” or said another way, “I trust you’ll have your project plan submitted by tomorrow morning.
If you reverse that to the employee view, employees expect (trust) us to listen to them. Too often, we create solutions for our customers and employees in a vacuum. Consider AI, where we create teams, develop project plans, buy technology solutions, and deploy some type of AI solution. Tools are also part of the AI solution, but so are the smart people we have working in Support today. We need those smart people to feel comfortable sharing their ideas, being curious, and being part of the change we want to introduce.
Today, many companies are struggling to build and continuously encourage an open environment for sharing ideas; this environment is necessary in order to build a culture of trust. Only when we have the culture of trust will we have open sharing of ideas, curiosity, and change.
If your customers and your employees are still invested in you as a company, as a solution, they will continue to provide ideas and suggestions. The day they stop making suggestions is the day you should worry, because that means they no longer care enough to try to make things better.
The second “E” is Engagement. Are you measuring employee engagement in your company or in your Support organization? We see this as one of the larger areas of focus today, and we think AI is one of the best places to look for and measure employee engagement.
As employees perform their day-to-day work, they know which tasks feel repetitive and mundane. They are keenly aware of the time that could be saved if only they had automation. They know they could truly be doing interesting work for their customers if they were able to save time on the items that could be done with AI. Look for suggestions, measure who is suggesting and what they are suggesting as far as automation with AI/machine learning. When one of the suggestions turns into a production project, reward that engagement.
The flip side of engagement is the customer side. How often are your customers providing suggestions on how to improve your service? Are you reviewing these suggestions? Besides customer satisfaction, NPS, and even customer effort, customer engagement is a fierce indicator of customer loyalty.
The next “E” at the center of our pyramid is employees. Most support skills inventories look for traditional elements, such as troubleshooting, customer service, the ability to write, problem solving, etc. These are without a doubt necessary skills to have, however we must not overlook other valuable skills. The competition is fierce for data scientists, data analysts, and AI skilled people, which are critical hires for support. Today, we need people with disruptive thinking, the ability to look at tasks and think “How can we automate this?” while taking those traditional tasks and re-engineering them with the use of technology.
Support employees are nervous about their jobs, so let’s involve them in the very thing that makes them nervous. Let’s help them see that re-engineering the more traditional tasks will only benefit them and not be the undoing of what they hold dear—job security.
The final “E” is effectiveness. Traditional projects for technology/automation tend to focus on the easy to solve, easy to automate, easy to do items—the low hanging fruit. AI can do those things, but AI is also bold, big, and game changing. AI should absolutely be about adding significantly more value and success to all it touches.
Support is going to evolve and be in an altogether different place through AI and machine learning. We are closer to customers than we ever have been, but we have to balance that closeness with creating roles that allow for it. We need to measure our success in different ways. Admittedly, AI can and will have great financial impact, and if done well, it will have positive impacts for the customers, the employees, and the business. Measure, report, and be bold on the impacts you are making with the use of AI. Are you measuring the right things, are you sharing results that illustrate the entire picture?
Has employee performance and productivity improved at your organization? Let’s be honest, very few people come to work to say, “I’d like to be moderately productive today.” The projects we pick should be measurable and show gains we can be proud of.
As I close out, I have a few final thoughts: I believe in AI and its goodness (especially for Support). We have the ability to create a workforce that is highly-engaged, and we have the ability to show and evolution of the valuable Support roles that have been done so much for so long.
To that end, I’d like to highlight one of the sessions at our upcoming Technology & Services World conference that, in my opinion, is going to be among the most exciting and thought-provoking discussions. I hope you’ll join me for my panel discussion entitled, “AI for Support Services and Beyond: The Time Has Come”. I will lead this panel discussion and I will be joined by a number of industry executives who will share insightful concepts and actionable steps you can take immediately regarding artificial intelligence for Support Services. This session is an absolute must attend for anyone wrestling with where to start or how to expand their AI initiatives.
One of my panelists, Robert "Bob" McDonald, is the vice president of support transformation and training for IBM. Bob has been leading IBM’s enterprise-wide initiatives focused on improving the IBM client experience. His leadership role of transforming the IBM Support organization, includes the development and deployment of cognitive computing solutions across IBM Support using IBM’s industry leading Watson technologies. I can’t think of a better person to tell their story and leave you with ideas and actions to take back to your company.
My goal for this session and the entire conference is to empower members to return to their offices with actionable steps they can take to address the needs of the business, the customer and the employees. Be sure to check out our full agenda, as well as our Support Services track, for even more great sessions you can look forward to by attending.
I look forward to seeing you in October.
Post Date: September 5, 2019
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Judith Platz, is vice president of research, Support Services, for TSIA. During her over 25 years of customer support experience, she has been responsible for supervising and coordinating multiple functional, strategic, organizational development and technical work streams, including technical support, account management, business consulting, implementation management, and training.
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