The work environment today demands that your organization advances the efficiency to execute business processes for continuous operations to have a positive impact on business performance. The capability to be responsive to any range of minor to disruptive business events is required to support business continuity and level of organizational readiness to meet the needs of digital business. Ventana Research asserts that in 2025, one-quarter of organizations will remain digitally ineffective in achieving the business priorities for customer-, product- and people-related processes. It is essential to eliminate bottlenecks and become an organization that places action and decision-making at is center to optimize the execution of business processes.
Topics: Customer Experience, Voice of the Customer, embedded analytics, Analytics, Business Intelligence, Cloud Computing, Contact Center, Data, Digital Technology, Operations & Supply Chain, Enterprise Resource Planning, Digital transformation, natural language processing, AI and Machine Learning, continuous supply chain, agent management, Digital Business, Experience Management, Field Service, Process Mining, Streaming Analytics
When artificial intelligence emerged from the labs and vendors started offering it as a component of their software, many contact-center buyers shied away from it. From their point of view, AI and machine learning tools were new, expensive, relatively untested and had an uncertain use case. This stance was understandable, as contact center professionals are traditionally expected to be risk-averse when deploying technology into their operations. Contact centers are, by design, supposed to be hardened, mission-critical sites of high reliability. There has historically been a bias towards avoiding new technology, deploying only when it has been thoroughly vetted across the industry.
Tools for contact center agent management have changed considerably in the past few years. The suite of software applications has grown from those that perform core functions in scheduling and quality control to include more advanced solutions for agent guidance, integrated desktops, and workflow and automation design. One area of intense investment by vendors has been analytics, specifically for assessing customer satisfaction and hearing the “voice of the customer.”
The primary effect of the pandemic on agent/workforce management beginning in 2020 was a rush to re-site and re-equip contact centers and agents. This was achieved with a surprising speed and smoothness industrywide. But once achieved on a “temporary” or “emergency” basis, it became clear that this shift was going to be semi-permanent. Even if the majority of the agent population moves back into standard centers, there is now a consensus that some portion of the workforce will work from home. As a result, the industry’s vendors have focused their messaging and short-term roadmaps on enhancing workforce engagement, or what we call agent management. These include promoting tools for measurement, management, and supervisory tools like mobile interfaces into workforce systems.
Customer support operations increasingly rely on automation and complex workflow processes to reduce costs and improve experiences. Automation also allows organizations to make their service processes richer, incorporating information and staff from back offices, for example, or embedding conversational tools into contact center processes.
Topics: Customer Experience, embedded analytics, Analytics, Contact Center, natural language processing, AI and Machine Learning, agent management, Customer Experience Management, Field Service, Process Mining, Streaming Analytics, customer service and support