Why Enterprise Automation Projects Fail—and How to Succeed at Them
The benefits of enterprise automation include more rapid operations, reduced costs, and enhanced productivity. But most automation projects do not deliver on their promise of increased efficiency and performance. That's not because of the technology used—the issue lies elsewhere.
Most enterprises think that automation is all about replacing human labor with software. However, what really makes automation efficient is an in-depth knowledge of business processes, workflow, and human interactions with various applications.
The most common challenge when implementing automation is the lack of clear requirements. Engineers are often tasked with automating the processes that were never mapped out or documented before. The timeframes should be estimated without knowing the full extent of the problem.
A related challenge involves automating inefficient processes. If there are flaws in the process, and it is automated as is, businesses end up doing things poorly but faster. Before automation and AI solutions can be applied, organizations need to figure out bottlenecks, reduce unnecessary steps, and set performance goals.
At Aperture Venture Studio (https://apertureventurestudio.com/), we feel that automation needs to start with identifying operational challenges, not technology. It turns out that the best applications of AI involve addressing particular business challenges that have measurable value.
This is how Artificial Intelligence and Internet of Things (IoT) complement each other. IoT helps capture operational data, while AI uses this data to discover inefficiencies, forecast equipment failure, and improve workflows.
Instead of replacing workers, intelligent automation allows employees to do better work by getting rid of the repetitive work and giving them insights.
A couple of principles that companies can follow to make sure that automation projects succeed:
Identify a specific business challenge.
Validate processes prior to automation.
Apply AI to assist in decision-making rather than automation of work.
Measure success in operational terms like decreased downtime, increased efficiency, or decreased costs.
Continuously optimize the systems based on their performance.
Organizations that get the most value out of automation are those that think of AI in terms of an overall operational strategy.
Through Aperture Venture Studio, we are creating AI and IoT enterprises that convert operational data into insights in the areas of manufacturing, logistics, warehousing, and industrial operations.
Find out how we do things at https://apertureventurestudio.com/
Automation in the enterprise of the future is not about eliminating humans from operations. It is about making enterprises smarter.




















