Keith Dawson's Analyst Perspectives

Software providers have identified “openness” as a key consideration for contact center buyers. Since there is no generally accepted rule about what makes a system open, it makes sense for us to examine what components contribute to that quality, and why it should be thought of as a good thing. Contact centers have been dealing with the tension between so-called open and proprietary platforms for decades, ever since the development of computer-telephony integration (CTI), which first injected open computing standards into the closed telecom-based world. It has been recapitulated repeatedly ever since. Right now, the industry is exploring what it means to be open in the context of dramatically different technologies for artificial intelligence (AI) and automation. It helps to think of those three ideas as three related concepts: automation is the goal that businesses are striving towards; AI is the enabling technology that makes automation possible; and “openness” is the environmental prerequisite for having both AI and automation. Open platforms are vital for the rapid and broad adoption of generative AI (GenAI) in business because they offer a collaborative environment where ideas can be shared, costs are reduced and innovations are rapidly deployed. There are several important characteristics of an open system. It should be standards-based, rather than built to be proprietary, hindering integrations. It should be, to a large extent, provider-neutral with regard to where those integrations come from, and its working should be transparent, or visible to examination. Those qualities exist on a spectrum and are not always all achievable in every instance. AI tools are an example of systems that are not always perfectly transparent, for example. Buyers should start by equating openness with the ability to move and extract data from a system, to have that system clearly documented and to be able to move from one platform to another without extreme provider lock-in. An open system differs from one that is closed or proprietary in certain important respects: It allows the administrator (or the end users) to perform extensive customization without being limited by provider control. The business can adjust or change features and potentially aspects of the interface. Less open systems provide the business with less control over how the system evolves and how data is managed. Ample integrations are available by default, usually in the form of either built-in connections or extensive APIs. Open systems can have lower upfront costs than proprietary ones, with the caveat that costs rise as a business develops the platform and leverages those ample integrations. (It is also important to note that over time, too much customization can create as much lock-in as a closed system.) In contact centers, open platforms are primarily cloud-based and more recently developed. Open platforms make data about customers and interactions available for analysis by teams outside of the center to understand how to orchestrate outcomes. And openness should lend itself to an array of possible upgrades or enhancements that can be deployed without significant operational disruption or professional services engagements. Openness can also be seen as a proxy for how future-proof a system is. If a business’s goal is to increase the amount of process automation throughout the customer experience (CX), then using AI applications in an open environment creates a hedge against being caught flat-footed with outdated tools. By 2027, customer experiences will be largely driven by processes controlled by automated GenAI tools. The contact center automation process these days often involves efforts to remove variability and error from human work by augmenting people with real time information, agent guidance and other support systems. These work in tandem with front-end automation that speeds and contains interactions within self-service tools. These upgrades to the common operating toolkit are quickly becoming standard fare, but it’s important to remember that they are flatly not possible without the ability to share and move data around, something that was not the default mode of old-school on-premises ACDs and routing platforms. An open technology platform does more than allow for freedom of movement—it fosters flexibility and dynamism within an enterprise that serves to connect the contact center to the rest of the business. And that in turn allows for the development of enterprise CX strategies and programs that drive tangible business outcomes. For the most part, enterprises are adopting openness as a strategy because it provides more options in more contexts and provides a hedge against an uncertain future. Enterprises are not monoliths but are collections of groups and individuals with goals that can be at cross-purposes. So, the relationship between the three ideas (openness, automation and AI) needs to be understood and planned for. Contact centers have long been aggressive about adopting automation, where possible, and are now keen to accelerate that process because of the cost savings that can accrue. In the past, their automation efforts have been confined to their processes, hived off from much of the rest of the enterprise. When you add AI to the mix, though, you find enterprises looking at a much broader effort across departments, ratcheting up the influence of IT. The amount of disruption that enterprises can tolerate appears to be a bit higher than what contact centers are used to, but there appears to be a consensus that both the center and its enterprise must move more quickly to adopt changing tools in order to stay competitive. Moving forward, enterprises should lean into open platforms whenever possible. It may not be possible in certain cases, but those should be thought of as rare and exceptional now. We recommend that enterprises looking to adopt an open system insist that software providers explain clearly both what they mean when they declare platforms “open,” and what we evaluate in our ISG Buyers Guide research in adaptability, including: the extent of the API and integration capabilities; how the platform functions as an onramp to using other applications from that same provider; and how much internal development or customization work is required (or encouraged) to get the most use out of the platform. Buyers should strive to make balanced selections based closely on their real-world usage expectations. Regards, Keith Dawson

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