Many organizations are shifting their contact centers to the cloud, often as a way to take advantage of the superior security, reliability, flexibility, location independence and real-time updates offered by Contact Center as a Service (CCaaS) solutions.

However, as often happens with new technology rollouts, too many companies are skimping on training programs for their employees and managers that can aid in the effective use of the new systems. This oversight is highly likely to create difficulties down the road.

Effective training programs are important not only to smooth the rollout of a CCaaS solution, but also to ensure that companies are positioned to unlock all of the value from their new tools. Without effective training, a cloud contact center can create confusion among agents and managers and leave company leaders in the dark about some of their most important customer data.

Use cases for the Internet of Things have diversified quickly, but most applications are designed to achieve one (or more) of the following objectives: obtaining data for data-driven business decisions; having the capability to remotely control and monitor assets, such as digital signage or city lighting; and automating operations, such as a manufacturing production line.

Traditionally, the network infrastructure that supports business is focused on indoor switches, routers and access points. With the IoT revolution, often that’s the initial plumbing required to connect sensors, physical machines and wireless devices to the network. In recent years, companies have begun to expand the enterprise infrastructure and reach outside of the four walls of the business, leveraging IoT technology to work in new spaces that were previously unconnected — for example, with switches and routers hardened for outdoor environments connecting mobile devices back to business applications. Whether it’s controlling, monitoring or automation that’s needed, we’re no longer limited by building boundaries.

Advancing IoT yet again brings up three major challenges, and that’s where we’ll see a new wave of technological evolution.

Increasingly, the power of data analytics is within reach for small and midsized businesses, even if they lack the in-house expertise to launch these efforts on their own. Modern data platforms, coupled with expert guidance, enable SMBs to take advantage of data-driven insights.

The caveat? Implementing sophisticated analytics is a process. Here are some key considerations for SMBs as they work to derive customized, prescriptive insights.

As localities slowly begin to reopen, technology will be an essential part of the process. The digital infrastructures at the heart of many modern cities may prove critical to keeping the coronavirus at bay. There are many other potential coronavirus-related applications for video in digitally connected cities and the organizations within them. Some, such as using facial recognition for contact tracing, may be controversial, and there are certainly privacy and security issues that municipalities must address. But the fact that a device as simple as a mounted camera combined with powerful analytics software might be used to accomplish in just a few seconds what would otherwise be quite difficult — that’s something localities and other organizations must consider.

Given today’s unique environment, companies are looking to technology, current and emerging, to help navigate the business landscape that exists before them — and the one that is to come in the near term. To help our customers through this constantly evolving environment, we’ve identified three key phases that organizations are moving through as a result of the pandemic. In mapping out this journey with our customers, CDW’s Consulting Services has determined where organizations should focus their technology investments.

For organizations to realize the potential value of AI, according to McKinsey, their AI strategy must align with their corporate strategy. They need a “clear data strategy that supports and enables AI,” and they must invest in staff and technical training to ensure they have the skills to implement AI at scale.

I keep those imperatives in mind when I work with business and IT leaders who wonder how AI might help their organizations. My advice to them: To get the most out of the technology — to make AI work for you — it pays to take a phased approach to implementation.