Service Management of the Future
Service management of the future won’t be about service desks, call centers and support tickets. It won’t be about response times, first-call resolution and satisfaction surveys. Service management of the future will be about automated workflows, self-service capabilities and self-healing IT systems. Machine learning will be the engine for resolving routine requests. Artificial intelligence (AI) will modernize end-user experiences. IoT and embedded sensors will provide accurate and real-time monitoring of both technological components and end-to-end services.
If you are having trouble visualizing service-management operations of the future, then look at customer service related industries where modern service management techniques and capabilities have already become mainstream. Self-service, automated provisioning workflows, technology-enabled incident management processes and advanced resource scheduling capabilities are not only transforming user experiences but also improving profitability as well. Here are some examples:
Airlines
The airline industry has become almost completely automated since 2009. Online ticketing via websites, mobile applications and 3rd party aggregators (such as Expedia and Orbitz) have replaced human staff at airports and traditional travel agents. Customers can browse offerings; compare prices and flight options anytime, anywhere; and make purchases without waiting in a queue to talk with an agent. Customer seating preferences, frequent-flyer perks and other provisioning policies are managed electronically and applied using business rules, leading to greater efficiency and customer satisfaction.
Airport check-in processes have migrated from ticket agents to self-service kiosks, mobile apps and home-based capabilities, so customers are able to print their boarding passes and baggage tags. Electronic boarding passes have eliminated the need for some travelers to visit the ticket counter entirely, making airport logistics much more efficient.
Behind the scenes, machine learning capabilities are powering pricing algorithms, so airlines can implement demand-based variable pricing to achieve an optimal balance between asset utilization and the profitability of operations. For flight operations, data from sensors embedded within planes are used to drive maintenance scheduling and prevent asset downtime for repairs. Air traffic control data, weather forecasts and flight schedules are used to predict disruptions and service delays – allowing carriers to provide more consistent, on-time arrivals.
Grocery Stores
The retail industry has been experiencing a technological revolution since 1999, primarily through a shift towards e-commerce. Grocery stores are one of the few segments in the retail industry that, until a couple of years ago, had been successfully focused on brick-and mortar-operations due to the fresh and refrigerated products they offered. That changed during 2018, as customers sought the same conveniences of at-home grocery shopping to which they became accustomed to retailers, such as Amazon and Walmart. Automation combined with local-delivery capabilities has transformed the grocery-buying experience.
Customers can use store Websites, mobile applications and, most recently, inventory capabilities built into smart appliances to compile shopping lists at home that can either be transferred to the store for delivery or accessed via a mobile app while browsing the grocery store in person. Many grocery stores now offer self-service checkout capabilities, leveraging barcode scanners, visual recognition of produce items and weight sensors embedded in bagging areas. These self-checkout kiosks allow a larger number of customers to check out simultaneously, utilize less floor space in the store and don’t require a cashier for each kiosk (significantly saving operational costs).
Online ordering, self-service kiosks and delivery services are integrated with inventory management, scheduling and supply-chain systems with automated workflows for stock replenishment, inventory forecasting and real-time profitability analysis. Some stores have even used this capability to determine the optimal time to bake fresh bread at in-store bakeries to create pleasing smells that lead to increased impulse purchases.
Internet and TV providers
While some industries have focused on automation to enhance customer experiences, the telecommunications industry (formerly phone and cable companies and now Internet and TV providers) are using technology to streamline service provisioning and reduce their dependency on field-service technicians. The results are reduced operating costs, faster provisioning times and more accurate monitoring of service outages and disruptions.
Customer service has always been a challenge for the telco industry and for many years, providers were ranked as having poor customer satisfaction, due partly to time delays associated with manual ordering, installation and service repair. Customers now shop for service offerings on providers’ websites, making subscription choices and managing billing without having to talk to an agent on the phone or visit an office.
For customers in newer homes or where service was provided previously, installation appointments are not required. Equipment is shipped directly to the customer, pre-registered and activated automatically the first time the customer plugs in the device. In some areas, customers using self-service capabilities can complete as much as 90% of new service installations. If an installation fails, then company technicians can access diagnostic data and logs remotely – to perform remote troubleshooting, which results in more efficient scheduling of field staff. Customers manage their subscriptions on the provider’s Website and/or mobile app, so they’re able to respond to marketing offers, upgrade service and manage billing anytime and from anywhere.
Behind the scenes, service providers use real-time data from user devices to offer customized advertising based on viewer demographics and locations, which helps drive greater ad revenue. Usage data also determines content offerings and meters bandwidth to achieve optimal infrastructure-capacity utilization. Device-diagnostic data is used to monitor service outages and disruptions. This data is combined with infrastructure-dependency data to pinpoint the cause of outages and expedite restoration of service.
Customers consider Internet and TV providers as utility services – they just expect them to work and, unless they are broken, customers don’t actually think about them often. With self-service capabilities and automation, providers are able to relieve many of the customer pain-points, which are the causes of dissatisfaction, while also reducing internal costs.
Modernization of employee experiences
It isn’t surprising most companies first invest in technological solutions that directly relate to customer engagement and decreasing the costs of producing and providing goods and services. These investments have a clear ROI and tie directly to competitive differentiation and company profits. The impact of entire industries modernizing with self-service and automation capabilities is a change to the underlying expectations of consumers about how they interact with businesses. Consumers from the Millennial Generation who have come to expect self-service and real-time and automated experiences throughout their young lives now represent a large proportion of the global workforce and they are bringing their consumer expectations to work with them.
IT departments face internal pressures to provide modern employee experiences, utilizing technologies, such as mobile apps and real-time data, while also reducing operational expenses and overhead costs. Service-management automation applied to internal business processes is providing IT departments with a means of achieving both goals simultaneously.
Cloud services and service-management automation
During the past, automation and developing modern employee experiences have been expensive undertakings. Only large companies with well-funded IT departments had the resources to invest in the custom development, integration and maintenance necessary to provide the experiences that employees desired. Small and medium-size companies simply could not afford the investments, and still mostly use the same manual processes they have for decades.
The popularity of cloud services and SaaS offerings have changed the situation. Providers, such as Freshworks, offer subscription-based, cloud platforms that support core business functions, such as HR, finance and IT operations, which offer the same features of large, custom solutions with a pricing model that small IT organizations can afford. These platforms include many of the most commonly requested self-service capabilities, automate provisioning and approval workflows, and include full-featured support for mobile devices.
The impact of emerging technology in service-management automation
Emerging technology, including machine learning, artificial intelligence, global broadband and IoT devices, are poised to accelerate adoption of service-management automation during the next few years by making devices easier to connect and providing management capabilities that cross the boundaries of individual technology types. Machine learning (ML) has already become a mainstream technology embedded in ITSM systems, integrated with cloud-management platforms and extendable into business services. ML empowers companies to orchestrate complex workflows efficiently for the many systems that use business rules and pattern recognition. Once a skill has been “learned,” it can be executed repeatedly without human intervention.
Artificial intelligence is transforming the interface between IT systems and the physical environment. Since the beginning of the computer age and to the present, a keyboard and computer screen (sometimes a mouse) have been the primary interface tools for humans to interact with computer systems. AI has introduced a new set of natural-language-processing capabilities (such as popular digital assistants Siri, Alexa and Cortana) that allow users to interact with devices and technology services using voice commands. Those commands are then translated through “AI skills” into tasks, queries and commands that are executed in the IT environment. AI’s capabilities extend beyond voice interactions to image matching, pattern recognition and statistical forecasting of potential outcomes. The total impact of artificial intelligence on service management has not yet occurred, but it is anticipated AI systems will oversee most service-management functions during the next few years.
One of the biggest challenges in service-management automation today is connecting devices and people who are not physically located at a site with reliable broadband-Internet access. Recent announcements of multiple initiatives to develop commercial broadband internet access globally using a network of low-orbit satellites have the potential to allow companies to overcome this challenge and provide automation and self-service capabilities anywhere on Earth. Connectivity is important, particularly considering mobile technologies and IoT devices, which require access to cloud services and other centralized resources.