Efficiency alone doesn’t ensure success, but inefficiency is a sure way to fail. You know who knows about efficiency? Ants. Yep, these tiny creatures, though infamous for ruining picnics, operate in an incredibly systematic and effective way. The data scientists at Swish.ai, a Tel Aviv-based AI startup, draw their inspiration from these ant colonies’ models of efficiency for their machine learning model. And it works! Swish.ai’s Delivery Intelligence platform has already helped large enterprises to increase the efficiency of aspects of their operations by 80%, and their customer circle among Fortune 2000 companies is constantly growing.
Despite the broadening adoption of new delivery methodologies such as Agile or Scrum, all large IT organisations are facing the same challenge: how to efficiently organize the work of hundreds or even thousands of IT employees and software developers who work on tons of projects, each with their own unique considerations. To cope with this, IT leaders and their project managers spend more time planning than facilitating actual progress. And in today’s crazy IT reality, unexpected events always sneak up and reshuffle everything, meaning that it can take weeks and sometimes months for IT leaders to really get on top of their work.
Not so for the ants. The University of Halle-Wittenburg’s study on ants indicates that when an unexpected event such as an increase in food resources occurs, the ants strategically change their behavior and rearrange themselves so that they remain productive, all within a few seconds. Inspired by this behaviour, Swish.ai’s cutting edge technology leverages the computing power of AI to make sure work is always as efficient as possible, while taking into consideration dependencies and key business parameters such as due dates, workload, and the urgency of projects.
This innovative technology is called IPA (Intelligent Process Automation). As the next generation of RPA (Robotic Process Automation) and Augmented Analytics, IPA is a major revolution for companies who wish to take their organisation efficiency to the next level.
Another genius ant trait that influenced Swish.ai was the specialization within these colonies that speed up the process of operation without compromising the quality. Specialization is a core economic principle and a catalyst for efficiency and productivity for ants and enterprises alike. In an ant colony, every individual is given the right task for their own skill set, whether it’s resource acquisition, building, or even just staying idle. Similar to this, and thanks to its powerful automatic skillset mapping, Swish.ai is able to map the strengths and weaknesses of every employee, and assign them to the most fitting tasks. This ensures that workload is evenly distributed, and that no task ever runs overdue.
Prediction is key to prevention. That said, in large groups, preventing a risk requires the whole group to always be in sync in order to react quickly. When ants detect a predator approaching their colony, they band together to form a sort of ‘superorganism’ to productively ward off their threats. Likewise, Swish.ai’s platform connects to every existing delivery management tool and monitors progress, creating a real time overview of all IT work. Acting as a control tower overseeing the whole organisation, Swish.ai’s platform uses predictive algorithms to predict impending problems and recommend ways to mitigate them.
So, the next time you’re at a picnic with all your favorite food laid out in front of you and a pesky little colony of ants comes along, take a moment to consider which of their incredibly efficient capabilities you might want to emulate in your own business. But don’t think for too long or these critters will polish off your last chocolate chip cookie. They’re just that efficient.
Want to know more about ITSM optimization? Check out Swish.ai’s Economic Impact Report analyzing data from 400 enterprise companies, with insights, statistics, and solutions to reduce ITSM cost and ticket volume while increasing customer satisfaction and efficiency.