Modernization in the computer industry is an ongoing process. The term ‘modernization’ is about relativity. Theoretically, modernization is improved by replacing the established with something ‘new.’
That ‘new’ has benefitted from the passage of time that has allowed some level of improvement due to advances in fundamental elements; what is ‘new’ is somehow ‘better.’ However, only the fullness of time will accurately judge if it is better.
In the computing industry sometimes getting one’s mind around ‘new’ and ‘better’ is not always clear. As customer expectations continue to evolve, they will demand organizations to innovate and improve experiences, and technology infrastructure will need to be enabled for change.
Digital transformation initiatives over the last five years have brought many organizations forward in their modernization, but there is still work to be done. Cloud-based applications in particular in the contact center continue to lag. Some application segments quickly moved from on-premise to cloud-based deployments, such as marketing and sales applications, while others, such as contact centers, are only NOW truly embracing the cloud platform.
In fact, it was only in the 2022 market year that contact-center-as-a-service (CCaaS) applications revenue nudged over 50% of new revenue in the market, hitting an all-time high of 54%. Granted, the contact center environment is characterized by an enormous installed base of on-premises software, but that gives a sense of how much work is left to be done in terms of cloud-modernization. This fundamental capability will become increasingly important with the emerging capabilities coming to market through generative AI offerings.
Concurrently, while platform shifts have been occurring, the strategy and go-to-market portions of organizations have also been modernizing and have been evolving into a ‘customer experience’ orientation. According to the IDC MaturityScape Benchmark: Future of Customer Experience in the United States, 2022 study:
‘If brands can’t meet customers where they are, then customers will quickly find the next best brand that exactly meets their needs. Differentiation then will require brands to mature and transform along critical CX dimensions that include organizational elements of customer centricity and, crucially, contextual application of the intelligence gathered about customers in a virtuous cycle of empathetic experiences that consistently address the customer’s desired outcomes.’
The concept of creating an ‘empathetic’ relationship with a customer is one in which the organization understands who the customer is and what that customer needs and wants.
These two areas are intrinsically linked in their requirements to modernize. The vision of an empathetic relationship cannot be achieved without an environment in which the data about the customer can be collected, assimilated, shared, and accessed democratically. The modernization of an organization’s architecture to one that is inherently cloud-based brings many architectural and functionality capabilities needed to treat a customer holistically. At the top of that list are interoperability and integration. Systems that can work together and share data and context about the customer. Modernization of the architecture enables the modernization of customer handling.
With generative AI impacting every market, and the power in particular of what it can do to improve customer handling, now is the time to focus on an architecture that enables the organization to harness generative AI in its pursuit of being a customer-centric organization.
Having an application architecture that democratizes data in a way that ensures fidelity and accessibility will be essential moving forward for the following attributes:
- Insight across the entire customer relationship that is not bound by a single functional area.
- Inclusion of all corporate roles that may have historically been left out of customer-focused initiatives.
- Rapid Insights through real-time capabilities and not batch.
Digital environments for customer handling – think Web-chat, SMS, and mobile applications – are in rapid evolution as customer channel preference expands. This shift is exacerbating the data volume and obscuring insights. However, these disparate data sources must be tracked and reflected in the customer records to enable consistent and contextual customer handling. All require a dynamic data environment.
In an ironic twist, COVID-19 was a needed cold-water bath for environments that had not embarked on the modernization of internal platforms to cloud-based platforms that would allow for the rapid deployment of work-from-home (WFH). For all organizations, those not far along on their digital transformation journey, and those that were, COVID-19 moved those ‘nice to do in time’ to ‘do it now!’ The problem with paradigm shifts is that there is no warning. Luckily, those DX initiatives have helped prepare for today’s next modernization initiative.
We are now on the cusp of the next evolution that requires a platform that allows for GenAI to operate safely and accurately. That will mean many levels of ‘modernization’ that revolve around the accuracy of data stores, the completeness of data across channels, across departments, across history, and accessibility to furnish real-time interactions that are informed and in context. Generative AI will mean a major revamping of how we interact with many things.
We can see that new paradigm forming and it will reveal if the new is better. In the meantime, modernization will mean organizations are prepared to incorporate this new stage in the customer experience.
