Everest Group’s digital services research indicates that 89 percent of enterprises consider customer experience (CX) to be their prime digital adoption driver. But we believe the digital experience needs to address all stakeholders an enterprise touches, not just its customers. We touched on this topic in our Digital Services – Annual Report 2018, which focuses on digital operating models.
AI Will Usher in the New Era of the Digital Experience Economy
Given the deluge of data from all these stakeholders and the number of parameters that must be addressed to deliver a superior experience, AI will have to be the core engine powering this digital experience economy. It will allow enterprises to build engaging ecosystems that evolve, learn, implement continuous feedback, and make real time decisions.
AI’s Potential in Transforming CX is Vast
Today, most enterprises narrowly view the role of AI in CX as implementing chatbots for customer query resolution or building ML algorithms on top of existing applications to enable a basic level of intelligence. However, AI can be leveraged to deliver very powerful experiences including: predictive analytics to pre-empt behaviors; virtual agents that can respond to emotions; advanced conversational systems to drive human-like interactions with machines; and even to deliver completely new experiences by using AI in conjunction with other technologies such as AR/VR, IoT, etc.
Digital natives are already demonstrating these capabilities. Netflix delivers hyper personalization by providing seemingly as many versions as its number of users. Amazon Go retail stores use AI, computer vision, and cameras to deliver a checkout free experience. And the start-up ecosystem is rampant with examples of cutting-edge innovations. For instance, HyperSurfaces is designing next-gen user experiences by using AI to transform any object to user interfaces.
But focusing just on the customer experience is missing the point, and the opportunity.
AI in the Employee Experience
AI can, and should, play a central role in reimagining the employee journey to promote engagement, productivity, and safety. For example, software company Workday analyzes 60 data points to predict attrition risk. Humanyze enables enterprises to ascertain if a particular office layout supports teamwork. If meticulously designed and tested, AI algorithms can assist in employee hiring and performance management. With video analytics and advanced algorithms, AI systems can ensure worker safety; combined with automation, they can free up humans to work on more strategic tasks.
AI in the Supplier and Partner Experience
Enterprises also need to include suppliers and other partners in their experience management strategy. Using predictive analytics to automate inventory replenishment, gauge supplier performance, and build channels for two-way feedback are just a few examples. AI will play a key role in designing systems that not only pre-empt behaviors/performance but also ensure automated course correction.
AI in the Society Experience
Last but not least, enterprises cannot consider themselves islands in the environment in which they operate. They must realize that experience is as much about reality as about perception. Someone who has never engaged with an enterprise may have an “experience” perception about that organization. Some organizations’ use of AI is clearly for “social good.” Think smart cities, health monitoring, and disaster management systems. But even organizations that don’t have products or services that are “good” for society must view the general public as an important stakeholder. For example, employees at Google vetoed the company’s decision to engage with the Pentagon for use of ML algorithms for military applications. Similarly, employees at Microsoft raised concerns over the company’s involvement with Immigration and Customs Enforcement in the U.S. AI can be leveraged to predict any such moves by pre-empting the impact that a company’s initiatives might have on society at large.
Moving from Customer to Stakeholder Experience
As organizations make the transition to an AI-enabled stakeholder experience, they must bear in mind that a piecemeal approach will not work. This futuristic vision will have to be supported by an enterprise-wide commitment, rigorous and meticulous preparation of data, ongoing monitoring of algorithms, and significant investment. They will have to cover a lot of ground in reimagining the application and infrastructure architecture to make this vision a distinctive reality.
Intelligent Sourcing magazine recently hosted a dinner in collaboration with Teleperformance in London where Mike Havard, CEO of Ember Group, and Julian Herbert from Everest Group discussed the future of the customer journey. The team from Teleperformance was also there to give feedback on the role of the customer experience (CX) supplier in managing modern customer journeys.
Demand for CX services is disrupting the Contact Center Outsourcing market, pitting traditional models based on labor arbitrage and scale with digital-first strategies.
Customer experience (CX) is king, dominating the strategic focus of a growing number of enterprises seeking to build a loyal customer base. These enterprises are taking a digital-first approach, aggressively shopping for service providers with next-generation, digital capabilities that can help them gain in-depth customer understanding, deliver personalized CX and establish highly qualified talent pools for managing CX. According to new research from Everest Group, digital CX, which currently represents 4-6 percent of the overall contact center outsourcing (CCO) market, is expected to grow at a compound annual growth rate of 20-25 percent for the next five years.
“Traditional CCO approaches are rapidly evolving to those focused on delivering customer experience services,” said Skand Bhargava, practice director of Business Process Services at Everest Group. “In fact, the digital outsourcing drivers for enterprises—such as CX consulting, omnichannel platforms and digital capabilities such as automation and analytics solutions—are increasingly becoming more important than in the past. Enterprise buyers expect their service providers to be customer-centric and to provide innovative solutions that can help them meet and exceed the expectations of digital-native customers.”
The global contact center spend stands at US$320-350 billion, of which third-party outsourcing accounts for approximately 26 percent. The global CCO market grew at approximately 4 percent in 2017 to reach US$81-83 billion, driven by the growing interest among new buyers for outsourcing and the emerging growth avenues for service providers around consulting and digital CX solutions. The CCO market is expected to grow further at a rate of 4-5 percent to reach US$91-93 billion by 2020.
The adoption of chat and social media has increased significantly over the past two years, compared to email and voice; chat has become the most preferred channel among millennials.
Robotic process automation (RPA) and rule-based chatbots are increasingly adopted across multiple use cases in contact centers to solve key business problems such as longer average handle time (AHT), average waiting times, and navigating through multiple systems and applications. Artificial intelligence (AI) is largely leveraged to unlock customer insights, predict customer actions, and make personalized recommendations.
The operational analytics solutions such as desktop analytics and agent performance analytics have witnessed high adoption in contact centers. The adoption of business analytics solutions that include customer analytics, sentiment analytics, and Voice of Customer Analytics (VoCA) is expected to increase over the next few years.
The delivery model for customer service management (CXM) services is evolving with a balanced mix of onshore, offshore, and nearshore agents, augmented with the Work-at-Home Agent (WAHA) model and next-generation technology solutions. The WAHA model continues to grow in CXM services, with around 93 percent of the total WAHA agents based out of the United States.
GE’s search for a buyer of GE Digital, its apparent “non-core” business, and UBS’ sale of its Smart Wealth digital wealth management platform are causing the old guard to rejoice and claim that digital businesses are bogus and hogwash. Even Everest Group’s research suggests that 78 percent of enterprises fail to scale their digital initiatives, and don’t realize the benefits they envision.
It is easy to naysay the naysayers. But these developments do merit a discussion. Many enterprises are investing in digital transformation initiatives, and they have a lot to lose if they don’t do it well.
So, what is plaguing enterprises’ digital transformation agenda?
Not Moving the Revenue Needle
Most of the industrial enterprises we engage with as part of our research believe that, even in the coming two decades, 80-90 percent of their business will come from their so called “core” products. Though they acknowledge that their core products are not static and continue to be increasingly connected, software-driven, and service oriented, the incremental impact on revenue is not yet clear. Their business modeling and simulations provide numbers that are sufficient to fund digital initiatives, but are insufficient to move the revenue needle.
Enterprises are realizing they have overdone some of their digital initiatives. Because business impact continues to be hazy, leadership is asking difficult questions. Our research suggests that 45 percent of enterprises fail to get funding for digital projects as the decision makers and purse string holders consider them vanity pursuits. Moreover, even strategic initiatives are struggling as the return on investment horizon is becoming longer as time progresses. Leadership is losing patience.
Challenges in CX to Business Attribution
Our research suggests that 89 percent of enterprises believe digital initiatives improve customer experience (CX). However, they struggle to attribute this improvement to business success. Therefore, business success becomes a secondary metric for such initiatives. Moreover, many enterprises confuse customer service – e.g., contact centers – with customer experience, which thwarts their ability to drive meaningful digital transformation.
We discuss another major reason for the gaps in digital promises versus reality in our research on digital operating models. Various enterprises assumed that digital transformation would create completely different businesses or business models for them. A prime example for comparison was about Google, a search and advertising company, getting into autonomous vehicles. Another was Amazon, an online retailer, getting into cloud services. These enterprises also assumed that they would disrupt their entrenched competition in their own and allied industries, just as Uber and Airbnb did.
However, I believe enterprises need such a dose of reality in order to separate the chaff from the wheat. As tech vendors, consultants, and system integrators brand everything digital, enterprises need a solid business case for digital transformation lest they spend precious money on worthless pursuits.
Enterprises’ needs of the hour are to develop a realistic digital transformation plan, rely on incubating multiple projects, be willing to fail fast, and leverage broader industry ecosystem. They must also remember that technology disruption always come with high risks.
Not acting is not an option, as the cost of doing nothing significantly outweighs the initial failures your enterprise may experience. Failing today is better than becoming irrelevant tomorrow.
What has been your digital journey experience? Please share it with me at [email protected].
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