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2019 Was a Fantastic Year for Service

It’s December, a time when we look at the year in review to see what has changed in the world of service and summarize the major drivers of progress. (Our January 2020 column will discuss the leading drivers of change for 2020, the first year of the new decade, a year in which DMG expects to see the real beginning of service transformation.) 2019 was a year in which it became clear that customers and clients were often displeased with the level of service, with a few notable exceptions. It was a year in which enterprise executives and service leaders have finally accepted that their organization needs to deliver the personalized service experience their customers want, in their channel of choice, instead of doing what is best for the company. Leaders are beginning to realize that what is best for customers IS what is best for their company, as long as they have the tools and operational framework and knowledge to deliver that level of service effectively.

Enabled by the digital transformation and enterprise-wide initiatives to retool and position companies to succeed in a digital service economy, 2019 was a great year for service organizations and contact centers. The level of investment was one of the highest ever experienced, and 2020 is looking to be even better, as long as the economy remains strong. This is great news for enterprises and the vendors who deliver their service solutions.  2019 was the year of artificial intelligence (AI) and robotics, a trend that is going to continue while the tools improve. The greatest areas of investment in service organizations and contact centers were: 

1. Artificial Intelligence – while the claims of AI capabilities far exceeded reality (a trend that is certain to continue), many vendors delivered nascent AI functionality to the market. AI comes in many forms, from natural language understanding (NLU)/natural language processing (NLP), to algorithms applied in workforce management (WFM) solutions that identify the best way to optimize and balance the needs of companies, customers and employees. With the positive developments come some new challenges; AI introduced a new level of complexity, as each contact center application (and there can be as many as 45) has its own AI (or AI-like) functionality, and each is dedicated to doing what is best for its own purposes. This means that just like in the “old days,” many of these solutions conceptually work against each other, without intending to do so. This trend will continue until an AI “brain” is introduced into the market, to oversee and optimize the performance of the overall department and all of its tools, solutions and platforms.
2. Robotic Process Automation (RPA) – We define RPA as software that leverages AI, machine learning, workflow and other technologies to automate the processing of repetitive tasks, initiate actions, and communicate with other systems or employees. RPA emulates the processes performed by human workers and can be trained to adapt to changing conditions, anomalies and new situations. The concepts behind RPA are over 35 years old, but new-generation RPA solutions deliver flexible tools to operations managers who know their business and what it takes to makes things move more productively and effectively, thereby essentially removing IT from the development process. (RPA solutions need to be administered by employees who are very logical and excellent in developing process flows, such as business intelligence (BI) analysts or coders who are tired of traditional coding, despite vendor marketing that claims that most anyone can create RPAs.)
3. Big-Data Solutions – This is a very over-used and old trend, but one that cannot go away, as data repositories are an essential component of all AI and machine learning (ML) initiatives. The “fun” (and it really is for those of us who have been talking about and trying to build useful repositories of relevant enterprise data for decades) is the source of these repositories. In some cases, the big-data solutions are new applications that were created or enhanced to collect and deliver the information needed to power an AI initiative. In other cases, companies are repurposing knowledge bases (KBs) that were compiled to support customer service or knowledge management (KM) initiatives. While the data in outdated KBs has to be addressed, the power of new-generation cloud-based KM solutions with amazingly fast processing and search speeds, supported by open-source database and other technology and tools, is a game-changer. After 40 years of trying to find its place in the market, KM has finally found its enterprise purpose, starting with seeding contact center-based AI initiatives.
4. Digital-First Solutions – The inevitable has occurred: contact center voice seats have reached their peak and are starting to decline. Digital-only servicing solutions are growing at a rapid rate. Like it or not, we have become a digital economy, and servicing organizations/contact centers must follow suit. (Some of the larger contact centers in the world are still voice-only.) The argument for adding digital channels to servicing organizations and contact centers is easy to appreciate, even if it’s not so easy to get a rapid payback. Once interactions are digital (which is happening voluntarily for a growing percentage of customers and prospects worldwide), they can be automated. (This returns us to emphasizing the advantages of a digital transformation.)
5. Cloud Servicing – All of these trends are overarching but none more so than the cloud. Sure, the cloud is a very practical acquisition and implementation model and comes with many quantifiable benefits for enterprises. But this is only a small part of the benefits of moving to cloud-based systems. The power (a word that I have used frequently in this column) of the cloud is nothing short of amazing. It enables companies to cost effectively and easily implement systems and applications without investing in hardware or a lot of IT resources. It gives companies tremendous processing power – well-designed and configured cloud solutions are generally architected to handle at least 100% more capacity than average usage, and sometimes even more. When applications are run from public facilities, such as Amazon and Microsoft, capacity, scalability, speed, redundancy and resiliency are massive. These benefits, enabled by a decreased cost of processing power, are essential for AI and big-data initiatives, and helpful for RPA and digital-first. The cloud has changed the cost equation and the way companies look at software initiatives and implementations. It is true that there are many institutions that are not yet willing to move to the public cloud or multi-tenant environments, but even these companies are moving to “hosting,” which gives them many of the same benefits of the cloud but on a dedicated basis. In short, the cloud removes from the equation many system and IT resource limitations and plays an essential role in the future of processing, including for service and contact center initiatives. 

Final Thoughts

2019 was a great year for service and contact center initiatives, and 2020 is expected to be even more exciting as the digital transformation reaches deeper into organizations to touch their service, sales and collections functions. The technology trends above are foundational to the future of service and contact centers, and they will continue to be enablers of essential changes and enhancements that will prioritize customer needs, changing the service dynamic in a lasting way that will benefit the economy, customers and enterprises.