Why Organizations Struggle with Intelligent Automation (and How to Overcome It)

Why Organizations Struggle with Intelligent Automation Gartner predicts that the total global business value derived from artificial intelligence (AI) is projected to total $1.2 trillion in 2018, an increase of 70 percent from 2017. Further, AI-derived business value is forecast to reach $3.9 trillion in 2022. The driving force behind this trend is that intelligent automation enhances the customer experience, produces new revenue and drives cost reduction. But if this technology is so lucrative, why aren’t more organizations fully on board?

The simple truth is that many companies struggle with what to automate and where to begin. According to Research Vice President at Gartner, Milind Govekar, IT organizations must shift from opportunistic to a more systematic automation of IT processes: “Most current use of automation in IT involves scripting,” said Mr. Govekar. “Scripts are more fragile than agile. What you end up with is disconnected islands of automation, with spaghetti code throughout the organization when what you need is a systematic, enterprise-wide lasagne.”

Why Enterprises Struggle

One of the most common yet critical mistakes IT leaders make is automating the application release while ignoring the components behind it. As a result, things ultimately break down, diminishing automation’s value proposition. Another common error is automating simply for the sake of automating.

When deciding which tasks, workflows and processes to automate, the organization’s objectives should be the first thing considered. From there, one can then identify the specific ways that automation can support those objectives. Furthermore, all objectives and outcomes from the intelligent automation process should be identified and fully understood by all project stakeholders.

To put it simply, project leaders should calculate how much it costs to perform a task manually as well as how costly it will be to automate that effort. This will determine how much money can potentially be saved in the way of time and other resources. (Here’s a strategic framework for measuring ROI of your intelligent automation initiative.)

Another area where organizations struggle is in a lack of strategy. As Mr. Govekar explains, ““The more you standardize the environment before automating it further, the better placed you will be,” said Mr. Govekar. “Don’t automate the mess – get rid of the mess first.”

First and foremost, project managers must identify where intelligent automation might be applicable in their organization and develop a strategy around those areas. Mapping this out will create a framework to keep the project on track.

What to automate and where to begin

According to researchers at McKinsey, there are five distinct factors in determining which activities to automate. These factors are:

  • Technical feasibility
  • Costs of automating
  • Relative scarcity, skill and cost of workers who might otherwise do the activity
  • Benefits of automation beyond labor-cost substitution
  • Regulatory and social acceptance considerations

Gartner’s Research VP, Cathy Tornbohm says companies can secure a good return on their investment by automating back-office activities that are too laborious and/or impractical to be performed manually. There are a great number of back-office tasks – such as data entry and processing – that do not require human thought, judgment or cognition.

It’s important to point out, however, that mapping out tasks should involve not just those that can and should be automated, but also those that shouldn’t. The only thing worse than not automating at all is trying to automate too much.

Every project needs a champion

Successful intelligent automation should go far beyond simply removing or reducing human effort. Rather, it focuses on transitioning human capability to higher-skilled areas by eliminating rote, repetitive work and automating manual tasks. While this may seem wise in concept, it is often met with strong resistance, particularly from human workers who view automation as a threat to their livelihood.

As Mr. Govekar points out, “Automation maturity cannot, and will not happen when the team required to implement automation technologies is resistant or reluctant. You need to incent the desired behavior by rewarding automation efforts and efficiency improvements, and instead of reinforcing the ‘hero’ culture, create a culture of the process definition.”

This is why it’s so imperative that organizations identify champions who are proactive about adopting, embracing and evangelizing automation’s features and functionality. These champions become integral in breaking down barriers and gaining buy-in from others across the enterprise.

A world of possibility

In the context of this article, we’re not speaking only of streamlining processes and replicating workflows. We’re talking about leveraging the power of artificial intelligence and machine learning to support decision-making and solve business problems. Cognitive technologies are revolutionizing the way organizations operate and it all starts with automation.

If you are struggling with what to automate and how to get started, an interactive demo of Ayehu can be the first step in your journey. The future is bright – get on the right path today.

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