While the outset of Covid-19 outbreak has transformed how organisations used to operate, accelerating digital transformation is something that every corporate honcho believes.
In a conversation with ETCIO, Muraleedhar Ramapai, Executive Director- Data at engineering services firm Maveric Systems busts some myths about traditional ways of working, leveraging data analytics and much more.
Ramapai believes that the good-old theory of human work motivation and management, which assumes the typical worker has little ambition, avoids responsibility, and is individual-goal oriented, is simply not true.
The senior management at Maveric had early discussions on possible productivity snags and remedial counter methods. To their surprise, the leadership found when goals are clear and projects that do not require elaborate white-boarding, the productivity actually increased while working from home.
In terms of capacity building approaches, Ramapai feels that organizations would not be in a hurry to build, say a 200-member team under one roof.
“Irrespective of how great an impact Agile methodology has had over the Industry, I feel, it has done a disservice to one of the most admirable achievements of human collaboration – the ‘Open Source movement’. Moreover, across organizations, future workflow examinations will include rethinking the importance given to face to face collaboration. Pre-lock down quite a few companies practiced 4:1 rhythm (work from office: work from home). I will not be surprised if we see that ratio inverted post lockdown,” he maintained.
Fueling growth with data analytics
It is imperative for any enterprise to acquire clients for growth. And to pursue this, Maveric Systems is now leveraging advanced analytics and data engineering to derive the nuances of voice of our clients’ customers.
“We listen keenly for insights, we understand the customer’s pain points, and we spot features and offers which give our clients the competitive edge. Let me describe this in a little detail,” said Ramapai.
Before Maveric approaches its clients, it works out the many parts of this equation, via advanced analytics.
At the outset, the company employs the three-way analytic assurance framework. It starts by using automation to collate banks customers’ historical feedback from all public domain and social media qualified-sources and separate out key themes using NLP and machine learning.
“The key dissatisfiers and delighters are validated through our detailed engineering analysis of the channel technologies. First-hand experience of the channels is scientifically analysed to complete the third leg of analytics,” he added.
According to Ramapai, the Chennai based Maveric Systems’ core belief is that ultimately data analytics should be tangibly usable and should be converted into actionable decisions.
AI for finding suitable candidates
Continually finding appropriate talent and making sense of the changing workforce trends is high on Maveric’s agenda. The company is experimenting with ML and AI to locate appropriate candidates for various roles.
Initial screening is being done by machines and data. Resumes are scanned and relevant technical assessments are then served over the cloud for candidates to participate and submit for evaluation. However, this initiative is currently in its infancy.
“Joining the dots for a robust and fool proof-talent recruitment program will happen as we replace the ‘all-powerful human-selection-mindset’ with objective decision-making models on AI, ML platforms. The expectation is that algorithms will enable us to complete role fitment through situational analysis,” added Ramapai.
According to Ramapai, all of the company’s computing and storage needs are federated and distributed. The systems are built to scale up by up to 25% of its capacity anytime as per the requirements. Maveric Systems embraced the cloud as a natural evolution strategy much before COVID took over.
Talking about application modernization plans for data centres, Ramapai said, “Luckily for us, we have been in a rather modernized (low-legacy) position. Most of our corporate applications (like code repositories etc.) are ‘SAAS-ified’ and already hosted on the cloud. Some labs were local, for which remote access was provided. We took an internal decision that future capacity enhancements (be it data-storage or compute) for R&D purposes, will happen only on the cloud.”