What would you do if you had access to a hive mind?
The thing is, you do. It’s in your pocket, and it’s known better as the search engine accessible from your mobile device. When you have a question or need information about something, it’s muscle memory at this point to whip out your phone and type your query into the search box, drawing on the information provided to you by millions all over the globe.
You don’t just ask any Tom, Dick, or Harry off the street, hoping they’ll have the information you seek—you can go directly to an expert and get the answer you want, in record time. What’s even more amazing is the astounding level of access everyone has to information these days.
This is the idea behind intelligent swarming. For January’s KCS Roundtable, we took a deep dive into the concept—what it is, how it transforms the customer support process, and what to think about if you want to use it at your company.
Why Is Tiered Support Obsolete?
In the traditional tiered support model, agents are structured in levels. Level 1 is the frontline, those getting the brunt of customers’ questions. When one of those agents can’t answer an inquiry, that question gets escalated to the next tier. Customers are stuck in waiting room limbo, and staff miss out on educational opportunities.
Tiered support is a pretty weak structure in an information ecosystem where customers expect answers yesterday. Not only do they get passed from one support agent to the next, waiting for someone to provide them with a response, let alone the one they’re looking for, they often have to repeat themselves ad nauseum, adding to their frustration.
In fact, 33% of consumers stated that waiting on hold and repeating yourself were the most frustrating aspects to customer service. As customer satisfaction dwindles, churn increases and profits plummet.
This structure isn’t fun for support agents, either. Greg Oxton, the former executive director of the Consortium for Innovative Service, said that he’s seen a caste-like system evolve where level 1 agents who’ve amassed enough expertise seek to escape the frontline, feeling that they’ve “earned” the right to not have to interact with customers anymore.
“The idea that anyone in support could ‘earn the right not to have to talk with customers’ (a common attitude in higher tiers) is a ridiculous notion,” he writes in a 2012 blog post for Think HDI. “Customer support is, after all, about supporting customers.”
Still, it’s not difficult to see why they might want to escape. Because of an increase in self-service options, driven by internal knowledge management initiatives and external customer demand, support agents are naturally getting the most difficult questions simply because they’re new and haven’t been addressed before.
Added to this is that customer patience wears thin within 10 minutes or less, according to Hubspot.
Thankfully, intelligent swarming is a solution for just such a perfect customer support storm.
How Does Intelligent Swarming Work?
The Consortium defines the intelligent swarming model as, ‘collaboration on steroids.’ It’s a framework that enables a support organization to draw on the collective intelligence of the company. This allows agents to collaborate among themselves or with other departments to resolve requests by matching the request to the person most likely to resolve it.
Intelligent swarming has four objectives:
- Perform skill assessment and utilization
- Optimize people’s ability to contribute (create value)
- Increase engagement and loyalty for your customers and your employees
- Improve customer success and realized value through improved problem solving
“Most people work just hard enough not to get fired,” joked the late comedian George Carlin. “And get paid just enough money not to quit.”
Sadly, it’s not just a joke. According to Gallup, 70% of the workforce is disengaged from their work or from the business’s overall purpose. The same research shows that true engagement comes from things like a stimulating career path, personal growth, and a sense of community.
The intelligent swarming methodology seeks to create that community by developing a collaborative environment. A big tenet of intelligent swarming is developing an ‘opt-in’ mentality, where knowledge workers choose to share knowledge they’re passionate about, or learn more on what they’re interested in. This is accomplished by creating ‘profiles’ that describe a participant’s expertise and interests, allowing others in the ‘swarm’ to pinpoint who they need to speak with to find a customer resolution on the first touch.
What’s more, intelligent swarming works best on novel questions that haven’t been resolved before.
What Are The Biggest Challenges In Adopting Intelligent Swarming?
There are four critical success factors for implementing intelligent swarming:
- Developing a culture of collaboration. The tiered structure is ingrained. Switching to a collaboration model isn’t like flicking a light switch; for many, this is a transformation that will take time and effort.
- Alignment to brand purpose and company values. This ties back to the problem of engagement, and more specifically, nurturing clear and streamlined communication between groups.
- Establishing new indicators of organization health and value creation. Intelligent swarming moves companies away and beyond traditional metrics. What success looks like will vary, depending on overall goals.
- Transformation of management’s role. One of the biggest changes is breaking traditional hierarchical structures. In an intelligent swarm, those traditionally in a management role move closer to being coaches.
How to Swarm the Knowledge You Already Have
As an increasing number of companies transition to either hybrid or remote offices, employee swarming is an emerging best practice for virtual workplace collaboration. Introducing chat messaging into enterprise search results presents a whole new type of content that needs to be considered carefully and displayed a little differently.
The promise of enterprise search is that you can search everything. This requires connectors to the data sources you want to index—such as Dropbox, Salesforce, YouTube, Jira, Google Drive, Twitter and many more—and a way to display that content to the right person at the right time using powerful AI technologies.
All these sources of information have something in common. Not their content, of course, but rather the fact that they are self-contained—in that each are relevant individually and can live by themselves in a search page. These types of search results don’t rely on each other to be relevant and useful.
In other words, you don’t need a second YouTube video to understand another.
On the other hand, conversational documents—and more specifically Slack messages—depend on each other because they are part of a conversation. To understand a message and its impact, you need to understand the context around it—where the message is from, who’s talking to whom, for which project, when was that said, etc.
This represents some challenges for adding it to an enterprise search engine, which we discuss in more detail in Should You Index Slack? 4 Considerations Before Indexing Conversational Content.
Is Intelligent Swarming Right For Your Company?
For more info, here’s the full webinar that dives much deeper into the concept of intelligent swarming, how to apply it, and lessons learned from early adopters.
No matter where you are on your KCS journey, you can find value in intelligent swarming. If you want to discuss other KCS-related topics, attend our monthly KCS Roundtable live and contribute to our growing community, please register here.
*KCS® is a service mark of the Consortium for Service Innovation™