The concept of Shift Left has been around for many years, originating in the software testing domain, focused on early testing in the software development lifecycle commonly referred to as, test early and often.
In recent years, the term Shift Left is becoming more common in the IT Service Management (ITSM) domain referring to shifting call resolution left along the support chain to level zero or self-service.
Whilst all organisations have different cost structures and formulas for calculating cost per call, it is well understood the further left the call is resolved the lower the cost per call and typically the shorter the call resolution time.
Historically Shift Left strategies have largely relied on providing a knowledge base to customers that address frequently asked questions.
Unfortunately, this approach often fails to deliver the expected benefits as knowledge articles can only be useful if; 1) the user is able to find the knowledge article relevant to what they looking for; and 2) the knowledge is written in a format the end user can understand i.e. non-technical and simple to follow.
AI-based Intelligent Assistants like Sofi developed by Soapbox leverage machine learning combined with natural language understanding to engage customers in a human like manner, understanding their request and guiding them to a self-service resolution through natural language dialogue and automated actions or by providing contextually relevant knowledge at the appropriate time.
To better understand the benefits of a Shift Left strategy is to understand the “buckets” of call types your Service Desk receives and then look to apply the Pareto principle ( 80/20 rule). Typically we find a high volume of calls fit into a small number of call types. For many organisations this is commonly system access and password related calls.
Benefits by the numbers
Assume the following mid-sized organisations Service Desk usage.
15,000 calls per month of with 12,000 fit into the 20% bucket. Assume of these 12,000 calls we are able to resolve 50% either through an intelligent virtual agent conversation or by providing the correct contextually relevant knowledge to the user at the right time. Assume your cost per call for a Service Agent to handle is $10
6,000 calls * $10 per call = $60,000 per month cost savings
Advancements in AI and semantic search technologies has made is possible to achieve a step change in self-service for customer service. The challenge remains, that incumbent customer service platforms do not make use of these technologies.
The approach Soapbox have taken with Sofi is to deliver this technology as a service that tightly integrates with a customer’s existing customer service platform, retaining the investment a customer has made and leverage the historical data within to ‘bootstrap’ Sofi to enable rapid deployment and return on investment.