The three pillars of successful enterprise automation.

Today’s IT landscape requires CIOs to do more with less. To manage workloads and maintain efficiencies, CIOs can turn to automation platforms. Trevor Francis, CEO and founder of 46 Labs, discusses common challenges of orchestrating connectivity and highlights three keys to successful enterprise automation.

The number of companies embracing automation is growing; according to a McKinsey global surveyOpens a new window , 70 percent of employees across a variety of industries say their workplace is piloting automation technologies for one or more business functions. That’s up from 57% just five years ago. Two-thirds of those utilizing automation reported benefits like reduced operational costs, greater efficiency and better customer satisfaction.

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70 percent of employees across a variety of industries say their workplace is piloting automation technologies for one or more business functions

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Among tech companies, the automation of global IT workloads has become a necessity; McKinsey Technology Council recognized automation as a top technology trendOpens a new window across all industries in 2022. A tight job market and budget constraints require CIOs to perform more work with fewer people.

The additional team workload causes burnout and reduced overall performance, further exacerbating the problem. Now required to do more with less, CIOs have turned to automation to manage workloads and maintain efficiencies.

While the teams managing these workloads may span multiple geographies, automation platforms can serve as a glue that binds them together.

Like any new business process, automation brings with it some challenges; among the most common challenges are needing to know where the opportunities for automation exist and the growing demand for new and advanced cognitive thinking skills to maximize results.  

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The key to successful enterprise automation requires that the CIO follow these three steps:

• Clearly defining the problem the automation is trying to solve,
• Choosing the right solution or tool and
• Identifying and engaging the IT teams that will be involved with implementing the solution.

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Defining the Problem

CIOs must start any automation process with a plain-language summary of the problems they are trying to solve and the desired outcome they want to achieve. Describing the situation in human-speak versus IT-speak has a way of cutting through the complexity. It also acts as a compass to the team that ultimately has to launch and complete the project.

For example, a global airline in Latin America experienced connectivity challenges. They relied on different integrators in each country to manage the local carrier relationships that ultimately connected their business. Implementing automation into such a segmented and siloed scenario would be time-consuming and costly.

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“Short of a natural disaster, I want our customer’s calls to make it to the proper place in our network, anywhere in the world.”

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Asked to explain the problem they were trying to solve in plain language, the airline said, “Short of a natural disaster, I want our customer’s calls to make it to the proper place in our network, anywhere in the world.” Once the tech team knew it was automating voice, it determined a hub and spoke deployment was the appropriate solution. The airline’s simple description allowed the tech team to accelerate implementation by over 50%.

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Choosing the Right Tool

The second key to a successful automation implementation is choosing the proper tool for the domain. There are excellent broad-scope Robotic Process Automation (RPA) vendors in the space that can provide a robust platform for automation.

However, most industries have particular automation needs better suited for domain-specific platforms. Standardizing on a single automation platform for an entire company is risky. It may also require IT teams to shoehorn solutions rather than implement native integrations provided out of the box by more tailored platforms.

Further, sensitive markets like those in China, India, and Europe have regulatory considerations that providers with specific experience should address. CIOs should select automation tools that solve their specific problem and not just any problem.

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Identifying and Engaging Teams

The third key to leveraging automation to magnify IT performance is identifying the relevant IT teams that must participate in any automation project as early as possible. Rarely does an automation project involve a single IT team. Infrastructure, network, and security teams must often work together to accomplish an assignment.

Including team-specific automation as part of an overarching scope provides an incentive to motivate participating teams. If they feel that the project will lessen their workload in addition to the collective, they are far more eager to implement it. Identifying and engaging teams early in any automation project allows CIOs to strike the right motivation out of the gate.

See More: Building employee engagement in the workplace

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The Role of AI in Enterprise Automation

In the very near future, enterprise automation and Artificial Intelligence (AI) will become synonymous, with enterprises following one of two paths with their application of AI.

A natural language model-based AI leverages a tool like ChatGPT to replicate human-to-human interaction. This type of AI model has a number of current applications: it is and will continue to be, used in the contact center space, in customer support, in document review and/or anything that follows a natural language or dialogue-based flow.

Decision-making-based AI is more narrowly-focused. As it’s specific to a particular workload, it’s generally trained using best practices within that particular domain. Examples of enterprise applications include automation of IT workloads, security, connectivity management, network management or anything that requires an automated decision based on best practices.

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...automation aims to drive efficiency, reduce errors, lessen workloads, enhance security, and lower costs.

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For enterprises to be successful in either model, they have to have a grasp of what the privacy considerations are for training these models and a clear understanding of which workloads they want to apply to which model.

Ultimately, automation aims to drive efficiency, reduce errors, lessen workloads, enhance security, and lower costs.  A step-wise approach that focuses on the process rather than the outcome will empower CIOs to create a culture of automation, which will serve them long into the future.

IT teams that integrate automation into their operations now will see tremendous value as the use cases for enterprise automation continue to expand.