Companies face a wide range of challenges where IT can help them perform more efficiently
Delivering those services and helping customers – whether they are internal or external – requires a new way of thinking. However, many teams are currently facing problems around planning for the future, as there are so many options open to them.
Service desks are developed to help companies build new services, support applications and fix issues. However, over time they went from essential facilitators that could design and support overall approaches to working through to lower cost teams that were solely tasked with “break-fix” responsibilities. For many companies, these teams have to deliver support and service that can be managed effectively based on assumptions that issues will be routine, predictable and scalable when needed.
Sadly, service delivery today is anything but routine, predictable or scalable. Take a new application built in the cloud – an issue with the cloud provider could lead to all customers being locked out of their service. With each and every customer suddenly needing assistance, scaling up to cope with the problem is difficult; diagnosing the issue with a supplier is also tricky. Coping with a bigger problem and automating responses where possible is therefore necessary.
In the State of the Service Desk Report, 13,000 service desk teams provided their insights into what is working and what is needed to cope in future. Around 69 per cent of front line responders stated that they spent too much time firefighting, rather than being able to plan ahead through better problem management. Similarly, around a quarter pointed to increased automation as essential for their efficiency. Yet each company will have to look at its own approach to automation – there is no one size fits all solution.
Future approaches to service delivery – Voice, AI, Search
There are a number of new options that service teams can take to evolve their approach – voice, AI and search. These categories describe how teams can improve service at the point of delivery and how to make more efficient use of resources using automation.
The approach that is most similar to current service strategies is search. This involves looking at how you provide information to people so they can help themselves. By looking at patterns in behaviour, you can improve response rates around self-service.
Traditionally, ITSM teams have maintained and updated articles, KnowledgeBase entries and Frequently Asked Question (FAQ) lists so that they can help on requests faster in the future. Using search data – a common approach that everyone is familiar with, and one of the most common steps that people take when they have a problem – ITSM teams can respond faster to common problems.
Based on this information, new articles or help guides can be put together and then shared with users either directly when they contact the service desk, or through self-service channels. This takes a more proactive approach to self-service and where to concentrate resources. At the same time, this approach should work alongside building up a better view of change management within the organisation, so that potential issues can be predicted. Looking at previous change management results can help you prepare for future ones too. By looking at user responses to materials that were shared, you can create more of what went down well and less of what did not. For example, short video tutorials may be more successful than large, in-depth guides.
Another approach is to look more specifically at AI and chatbots. Chatbots take the concept of live chat further by using technologies like machine learning to provide automated responses to requests. By matching issues to potential articles or existing materials, a chatbot can take on most Tier 1 calls or requests and provide information back.
To make this process applicable, there are several steps that you have to go through:
- Training the chatbot – this involves providing a set of training data (typically email conversations between agents and customers) and letting the chatbot see which responses helped the customers the best.
- Testing the chatbot – once the chatbot has been trained, the service team should test the bot with some common requests for information and typical problems. This will test that the chatbot is responding appropriately and that the right information is being provided.
- Rolling into production – after the testing phase, the chatbot can start handling conversations that come in via live chat. If there are issues that the chatbot can’t recognise – or that aren’t being dealt with in the right manner – then they can be automatically handed to the appropriate agent.
Chatbots can be seen as an evolution of self-service, rather than being a complete revolution that will replace more traditional search functions and channels. Chatbots tend to be popular with those that want to be provided with direct answers in a more conversational manner, as opposed to finding their own answers with search.
Alongside this, it’s important to bear in mind how chatbots will have to evolve over time. For service teams, training the chatbot on appropriate responses and monitoring how customers respond will be a long-term role change. Chatbots won’t learn on their own.
The third option – Voice-led – is still at the beginning of its life cycle. Alongside traditional telephone requests, voice assistants can provide a new channel for service delivery. The likes of Amazon Alexa and Google Home make it possible to ask for information and have it delivered automatically, extending the potential for dealing with queries.
For consumer-focused organisations, the popularity of voice assistants will be interesting to track. Many phone manufacturers are embedding assistants into their phones, so they may become widespread alongside the stand-alone devices that are available. For business-to-business companies, voice assistants may be useful for delivering updates or answering questions from users, but this will depend on a more specific business case to work. Voice can provide additional opportunities for automation to create value for customers alongside other channels.
To make use of voice assistants, it’s worth looking at two areas: how popular they are becoming with customers, and if there are specific services that can be either created or duplicated using voice. For example, a chatbot’s content and responses could be duplicated by a voice assistant to take advantage of this new channel, but this will require additional development support and training over time. Will it meet demand from customers, or will it represent an overhead on the budget that does not pay back?
Over time, voice-led services can provide some of the personal interaction that traditional conversations with agents can provide. However, this will take a significant amount of time to deliver. Integrating with AWS, Microsoft and Google services will be possible, but it will require a strong business case and interest from customers to justify in the short term.
How to develop the right approach for the future
Each of these approaches can help develop your approach to delivering service in the future. Depending on how your customers prefer to interact, and the goals that you have, implementing voice or chatbot-driven services may be more applicable. However, underneath all these channels are two overall goals – the delivery of better service, and the role of automation.
Combining faster interaction and smarter services across multiple channels should be possible using automation. Turning this into actionable and practical service delivery strategy involves looking at how current services are managed as well as looking into the future at how these preferences may change over time. However, it’s important to emphasise the role of the IT service team in supporting these efforts over time. Without the right people available that understand both your customers and your processes, you can’t automate service delivery effectively.
These approaches to service should not be seen as goals for the future; instead, they can all be part of a strategy that aims to continuously improve service over time using automation.