Paul Burton
Analyst · Sidoti & Company. Please proceed
Thank you, Vivek and good morning to everybody. It's a pleasure to speak with you today about something as exciting as data and analytics. By way of background. I've been involved with technology for over 20 years and with data and analytics for a great majority of that time. I've spent considerable time with Hewlett-Packard, IBM and Genpact. With both IBM and Genpact I led global data and analytics businesses and in both roles had the opportunity to live and travel extensively in developed and developing markets. This experience has given me a perspective on technology, data and analytics that I believe is valuable and that serves me well in my work here at Mastech. And in the next couple minutes I want to talk about the journey we've been on as Mastech with the Data and Analytics business. I will briefly remark on our view of the data and analytics marketplace. The team, we've put in place to go after this market, lines of business we go to market with, the importance of alliances, our competitive positioning and some thoughts on the pandemic currently gripping the world economy. So let's get started. Today the data and analytics marketplace is vibrant. The data and analytics market is estimated by IDC to be $275 billion by 2023 growing at a 12% CAGR. Gartner offers a similar estimate. Every day we see businesses waking up to the need to leverage the entire corpus of their enterprise data. And in many cases some desire to go even further by integrating open source and syndicated data with their enterprise data. We believe that data is the blood of the modern enterprise. Because increasingly, it's data that carries oxygen and nutrients throughout the enterprise that allows the enterprise to perform at peak fitness. We are seeing that businesses that are able to mine high volumes of data for knowledge and glean insights from this knowledge that can be acted on smartly, especially in real time are the most competitive enterprises in their respective industries. This is because data is the foundation of all enterprise learning. Said another way, enterprises that can consume data at volume and scale in real time simply learn faster relative to others that can't do this. Consequently, they adapt to their environment and evolve faster than their slower peers. The digital era, we are knee-deep in at this point lays bare for most enterprises the need to have data and analytics programs that work synergistically to drive enterprise learning. Enterprises that do not learn simply fail. At Mastech, we focus holistically on our clients' data and analytics capabilities with an eye towards accelerating enterprise learning. We help our clients bring disparate sources of data together to construct data products that reveal novel insights, infuse intelligence into business processes and assist decision-making, especially with regard to strategy choices. To drive this agenda forward, in the last 18 months, we've assembled a team of professionals with great experience in working with clients to help them develop and enhance their data and analytics capabilities. We've added senior members in Singapore, the Middle East, Europe, Africa, and of course in North America too. The team comes with great experience from significant Fortune 100 companies. We've brought onto the team deeply skilled professionals with PhDs in cognitive science, neuroscience, physics, mathematics, statistics and computer science. We have done this with the intention of being thought and content leaders in our chosen market segments. As we extend the capabilities of our team to embrace our clients, we are proud of the value we are creating and delivering and how it's enabling our clients' businesses to perform. To this end, we are engaged in building new service offerings that are finding expression in intellectual property we are creating and that we believe will meet the needs that our clients are conveying to us. We go to market across three service lines. First is our Data Management service line. Our Data Management service line is the foundation of our business, because without properly curated and managed data, it's impossible for businesses to mine for insights that drive the enterprise learning process. Good quality data is the one indispensable resource for every business. Second is our Data Engineering service line. This service line exists to ensure that the enterprise is wired to support the high-velocity ubiquitous flow of data throughout the enterprise. Many businesses suffer because of an inability to access the data they possess in a timely effective manner. The mission of this service line is to solve that problem, and thereby expose the entire corpus of data to the business for exploitation. Third is our Data Science service line. This service line brings state-of-the-art computer science and data science techniques to bear on specific client problems that heretofore have been intractable because of data access issues or simply an inability to deal with data at velocity and scale commensurate with the digital age we find ourselves in. These service lines dovetail nicely with the capabilities of our partners. So, let me say a word about our alliance strategy. We can report that we are not going it alone. We continue to build strong partnerships with significant technology companies. For example, IBM has named us as one of their 11 global elite partners. And we continue to solidify other partnerships that complement and enhance our capabilities. The purpose of these partnerships is straightforward. We bring our professional services to market along with the product and infrastructure capabilities of our partners to offer best-in-class data and analytics solutions that help our clients increase the learning velocity of their enterprise. Enterprise learning driven forward by the consumption of data at velocity and scale is one of the competitive advantages available to all businesses. By partnering with leading technology companies, we are able to deliver this advantage to our clients, because we are able to deliver a comprehensive solution: hardware, software, cloud, professional services. At Mastech, we believe we are different, because we focus squarely on delivering what all businesses need. We help our clients architect enterprise intelligence. We help our clients learn at velocity and scale from the voluminous amounts of data they have at their fingertips that have heretofore been unable to fully exploit. At Mastech, we believe, our approach is unique. By focusing on learning as a function of data consumption, especially in this digital age where data volumes continue to grow exponentially, we help businesses adapt more quickly to their environment and therefore evolve more quickly. By linking the consumption of data to learning and the consequent production of superior business outcomes, we are able to help clients re-architect their entire enterprise to be data driven. That is to say, we help our clients fully embrace the digital era they find themselves squarely in. It goes without saying that as we help our clients accelerate their enterprise's learning we help them become more agile and competitive in an interconnected world that is increasingly sensitive and vulnerable to unexpected events. Now, let me conclude by saying a brief word about the COVID pandemic. The repercussions of the COVID pandemic have been systemic. At first, our clients paused because of the understandable economic uncertainty they were confronted with. With each passing day, however, we have seen our clients adapting to what can be perhaps, best described as a new, if only temporary normal. Prior to the pandemic, we posted five consecutive quarters of growth with improving gross margins. Four of those quarters represented records for us. The pandemic interrupted this streak. But, as I said a moment ago, there is reason to believe that things are beginning to return to normal. We believe the prospects remain positive for our Data and Analytics business. Thank you for your attention. I'll now hand it back to Vivek for his closing comments.