Many business and IT leaders understand the value that data analytics can provide but struggle to achieve the benefits. In some cases, organizations generate lots of data and create dashboards to visualize it, only to make an unfortunate discovery: They haven’t produced any insights that are actionable.

Deriving value from analytics requires insights around measuring specific changes or driving a particular action that the organization wants to take. This requires a few key steps.

As organizations look for opportunities to put data analytics to work, DevOps is one area that deserves attention. In many organizations, data scientists and software developers are still siloed, but bringing their talents together makes sense. Development informed by data can help teams in a number of ways.

The goal of DevOps is to shorten the time required to get ideas into practice by accelerating the development process in a quality-controlled way. Its methodology depends on a steady, reliable source of clean, organized and indexed data. Generating the right data during the DevOps process, and then using the resulting insights to inform the next iteration, can minimize error and increase the likelihood of success.

Analytics is a natural complement to the DevOps feedback loop, providing valuable insights that inform continuous improvement in decision-making. Collaboration, however, is essential. When developers know what data they need to collect, they can create code that will write logs to a file for analysts’ review. That requires not only joint planning but also clarity about what the goals are — both for development and for the business as a whole.

Surveillance cameras have been in use for decades, and organizations that employ them are able to collect a valuable record of what has happened in the area being watched by their cameras. But organizations that use smart cameras, video management software and data analytics can approach their surveillance video as data and gain far more value from it.

In the past, security teams have been in charge of surveillance, for obvious reasons, but by bringing IT professionals in to make use of the data that surveillance systems create, organizations open up a variety of use cases.

For example, the manufacturing industry has a wide variety of opportunities to apply enhanced video surveillance (EVS) technology to modernize operations, improve efficiency and enhance physical security.

To get started, a company should consider upgrading network connectivity throughout its facilities and connecting IP-based cameras to monitor business processes. By connecting these cameras to the data network and applying analytics software to the video data being collected, a company can unlock a number of valuable capabilities. Let’s take a look at some innovative ways that EVS technology can improve a company’s work.

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.