By Gairika Mitra
Could you elaborate on data-centric research and contextual analysis at SG Analytics?
SG Analytics is quite strong in modern analytics stack, machine learning, data science, and processing of structured and unstructured data. However, what really sets us apart is that we lead with business outcomes: we take the time to understand the business goals of our customers, and then apply the right set of analytics technologies coupled with business context brought in by a team of domain experts to create compelling business outcomes for our global customers.
SG Analytics is also strong in primary and secondary research. We are uniquely positioned since we can cogently combine our research and analytics capabilities together, sprinkled with a good dose of domain context to enable outcomes that are hard to achieve otherwise.
Which industry sector is the most adept in your services?
SG Analytics has grown from an investment research focused company to a full stack data centric research and contextual analytics company. We are amongst the top research and analytics companies serving our clients in the BFSI sector, which is one of our core strength areas. We are the preferred partner of choice for our BFSI clients including global research and information platforms, top tier private banks, investment banks, hedge funds, wealth managers, PE funds etc.
Technology is another sector where we are seeing success. We are positioning our integrated research and analytics capabilities comprising some of the technology sector’s biggest names globally. We have recently onboarded the largest technology company in the world as our client.
Please share the company’s roadmap
SG Analytics has invested deeply in becoming a technology first company. We are in the process of identifying recurring patterns in our multiple services engagements and building reusable platforms /frameworks to accelerate our service delivery. We are taking it one step further by productising some of those platform capabilities – productisation is a key innovation driver for us at SG Analytics. A product mindset is also helping us differentiate ourselves from other services companies in the way we engage and deliver our services to many of the global product technology companies. We are also strengthening our software product development capability and partnering with data-oriented product platforms to become their partner across the spectrum of software development.
We are also investing heavily in automation capabilities – robotic process automation, DevOps automation and automation of complex business workflows across domains.
Do you think technology stands at par with its banes and boons?
At the end of the day, Technology simplifies life for all of us. The use of machine learning and data science is automating several aspects of our life that were not possible before. Having said that, building those machine learning and data science algorithms is becoming increasingly complex and it is become harder to find the technical experts who can deal with this complexity. While technology advancement in ML/data science has introduced that complexity, technology has come to the rescue via availability of data science platforms that are taking some of the complexities out of building and maintaining all those ML algorithms.
Do you have any plans on expanding globally?
We already have strong global footprint across the US, Europe and Middle East. While we are doubling down on our US presence more strongly than before, we are equally excited about the untapped opportunities in APAC.
How do you wish to scale up in future?
We are on an aggressive journey to rapidly move up the value chain via productisation as well as by positioning ourselves as business outcome focussed end-to-end consultancy firm. Productisation will put us on a non-linear scale up trajectory and will also fuel our services business. We plan to go deeper into the technology, healthcare and ESG sectors. We plan to further expand our geographic presence in the US, Europe and make inroads into the APAC region; part of that will be developing a talent pool that is global in nature.
Also, our investment in data has increased during these times, given the uptick in demand from our customers. We are also doubling down and investing much more aggressively on our data governance practice to build on top of the strong data management, data science and ML capabilities that we already have.