The Importance of Frictionless Self-Help in a Work From Home World
According to McKinsey & Company, 62% of employed Americans are working from home as a result of the pandemic. The good news is that 41% of them are actually more productive working from home. The bad news is that 31% are less productive. Since the start of COVID-19, the ability for employees to shoulder tap their neighbors for IT help no longer exists. So it’s no surprise that there has been a 35% increase in IT incident tickets every day.
With increased ticket volume and one in three employees struggling to get productive at home, now is the time to provide a frictionless self-help experience that will solve these problems.
Self-Service Portals Are Just Another Way To Open A Ticket
Traditional IT help desks rely on portals for employee self-service. The reality is that portals seldom provide answers. Instead, employees use portals to open IT tickets and then wait for a response. It’s estimated that 30–40% of IT tickets are created and routed incorrectly, resulting in a phenomenon called “ticket ping pong.”
Every time a ticket is reassigned, employee happiness drops by ~10 points and productivity drops by ~1 hour according to HappySignals Research.
The Employee Experience Using Espressive Barista for Self-Help
Unlike portals that seldom provide the right answer, Barista provides immediate, personalized answers to employees 66% of the time on average. And when Barista isn’t able to provide an answer, Barista invites the right agent into the conversation through Smart Ticketing. This exclusive feature eliminates the time help desk agents spend classifying, assigning, and prioritizing tickets, thus eliminating the frustration and productivity loss of ticket ping pong.
By using machine learning to build a predictive model from customer historical tickets, newly created tickets, and agent actions, customers can deploy fast without the requirement to build and maintain a large index of static rules. Instead, the machine learning predictive mode will predict the ticket data and populate the tickets for agents to review. As new tickets come in and agents occasionally correct predicted tickets, these changes are reviewed and approved, ultimately creating a better machine learning model that requires less human interaction.
Because tickets are correctly assigned to the right team from the start, customers are able to dramatically reduce mean time to resolve (MTTR) while providing a frictionless employee self-help experience. In a work from home world, that is an imperative.
Learn more about Barista Smart Ticketing here.