Co-founder Sona Mnatsakanyan tells us about ZEVIT’s aspirations for Data Pitch and beyond.
Describe your Data Pitch challenge idea
The challenge of making operation and maintenance processes more efficient, while being able to support cutting-edge analytical models, is becoming increasingly important for industrial asset management and field service businesses. At ZEVIT we know this because we are coming from the business side, with many of our team members having worked with global industrial players for years and leading their major digitalisation efforts. To help overcome this challenge, ZEVIT decided to put the best practice of the industry into a piece of software that will help its users to build, maintain and put into use predictive monitors in order to transition into predictive service operations and maintenance.
What does the idea set out to achieve?
ZEVIT’s aim is to achieve an effective operation of best practice predictive analytics, enabling industrial asset management and field service businesses to receive valuable insights from running machine learning algorithms, and optimise their assets’ reliability and maintenance.
What makes your idea different or unique?
In comparison with the few generic and IT-driven predictive analytics softwares available on the market, ZEVIT’s software focuses on the business needs of the user and then addresses them using predictive analytics. Our proven track record in operating expense-heavy industries allows us to quickly put the best practice and analytical methodologies into the predictive monitors running the analytics. A concrete training is then developed and tested with the user group.
Our software includes the maintenance recommendations corresponding to the detected equipment faults, ensuring that the maintenance processes have no information gaps. The software also provides clear framework for tracking the performance of the predictive monitors and measuring the benefits harvested from operating them.
Where did the idea come from?
The idea of building a software that would integrate our knowledge of how to make use of predictive analytics came about while we were driving back from a conference. At that conference we witnessed once again how big the gap is between what the industry demands for implementing advanced analytics and the existing software solutions. So we decided to create software that would serve the current needs of the industrial asset management and field service businesses.
What excites you about the challenge you applied for?
It is considered cool when businesses talk about Big data and AI. But people sitting in the operations department of those same businesses most likely do not think so because they tend not to see the impact of those buzz words on their daily work. This doesn’t excite us much either. However, we are excited to build a system that will disrupt the conventional operations and maintenance processes in industrial asset management and field service businesses. This will make them more efficient by putting advanced predictive analytics into their daily operations, which in turn will allow them to generate measurable business value.
How did your team meet?
Having spent years leading the digitalisation efforts of a major industrial company, our CEO Anders Hvashoj was about to found a startup that would help field service business to reach a new level. At that time, I was having fun experimenting with new machine learning algorithms in the service business of the same organisation. Having brainstormed together a few times, we found mutual points of interest that we could expand upon while running a startup. At the same time Frederik Østerbye, an IT architect and successful consultant, was attending meet-ups discussing novel but interesting solutions in machine learning and AI. We met at one of those meet-ups and realised it would be a great journey if the three of us could unite and work on projects together!
What’s the best thing about working with data?
Discoveries are what make scientists’ work exciting. We think uncovering patterns within data is the most motivating reward, and data scientists enjoy it too!
Anything else you want to tell us about your startup and why you do what you do?
We believe it takes a small team of the best specialists to secure results in flexible fashion. Our clients believe that we have added and still continue to add a lot of value in the growing industrial service industry. Our approach therefore has a proven record of efficient executions and success stories that we now want to replicate through sharing our knowledge with a wider audience via our new software.