Published in Jul-Aug 2022
ZEENAT CHAUDHARY: What will you be speaking about at the Corporate Leaders Meetup today? STEPHEN BROBST: Today’s session is mainly about innovation – it will be about the importance of why data technologies, such as machine learning and AI, are essential for business progression.
ZC: Has your specialisation always been business intelligence and data analytics?
SB: I would rather say machine learning since that is a more modern term than business intelligence (BI). BI refers to descriptive analytics (they tell us what has already happened, such as year-on-year growth, revenue per customer, etc.). I am emphasising the stage beyond that, which is machine learning: predictive and prescriptive technology. Consequently, my speciality is using data for better decision-making. I realised the importance of using analytics to help businesses after doing a PhD in Computer Science from MIT. When I entered the commercial world post-PhD, I decided to pursue an MBA, because although there are many PhDs out there and definitely enough MBAs, the combination of the two is a unique characteristic because it helps understand the capabilities of technology while being related to solving a real business problem.
ZC: What was your role as a member of Barack Obama’s Council of Advisors for Science & Technology?
SB: Our job was to make recommendations on how the US government should invest in big data and Obama gave us a number of different areas in which he wanted things to improve (stuff like quality of life, better education, better transportation, economic growth), and our job was to map big data and analytics into these categories. My focus was healthcare and software engineering, the result of which was an almost 180-page public report. Ten years later, some of those investments are now coming to fruition with the advent of IoT data, smart cities and investments by the government in healthcare and changing payment models.
ZC: What is the primary focus of Teradata Corporation?
SB: Teradata’s software, Teradata Verge. This is a connected multi-cloud data platform for enterprise analytics that allows companies to handle massive and mixed data and makes it easier for them to consume. Essentially, it unifies and analyses data from different sources (websites, social media, company books, vendor transactions etc.) to give a single source of truth (read: predictive and prescriptive technology).
ZC: How does this help customers?
SB: We have helped customers such as Groupon, Verizon and Unilever use their data to make better decisions by helping them understand their consumers better; not just what happened in the past but also predicting the future – for instance, what products will they need in the future or framing campaigns that encourage certain consumer behaviour. With telcos, Vantage can help them understand that consumers want to save money (for example) so that the telco can then offer consumers different packages or encourage them to convert from prepaid to postpaid if it is better value for money. We can also help telcos use data to optimise their network; for instance, where should they put new cell towers based on demand. This is a very important decision for them and it costs a lot of money to do it right. So we help them use their data to make better decisions.
ZC: How do you differentiate Teradata Verge from other data management platforms?
SB: Teradata believes in being ‘open and connected’. We do not say, “You can share data among the different areas/vendors/geographies your business connects with, but only if everybody buys our technology.” This doesn’t make sense. Let’s say I am in the manufacturing business and partnering with my suppliers. I am a large-scale business and use Teradata Vantage, but for my suppliers, the Microsoft SQL Server is more appropriate. There should not be any impediments to sharing data between the two. I should be able to share across different technologies. We take a very open approach, not a proprietary approach.
ZC: How does one convince companies that such software will benefit them?
SB: You need a certain scale for this approach to be useful because you have to have enough data. Every time small shop owners sell something, they put a little tick against it in their notes. That is their data. For their scale, it’s probably okay. But if you are a larger-scale enterprise, then you cannot be putting little ticks in a notebook, you need to analyse the data in a more sophisticated way. The use of data varies by scale, by industry and by country.
ZC: How important is this for a country like Pakistan?
SB: It depends on the industry. Many banks and telcos in Pakistan use Teradata’s technology; they are large-scale industries and they require data warehousing. However, an industry such as retail may not need such software because it is not competitive enough; there are many small players, but not enough large retailers. In the US, it is the opposite because retailing is large and we do not have as many mom-and-pop shops. Also, to use analytics, certain skill sets are needed and if you are a small business, you most likely will not be able to afford to have a full-time data and analytics person.
ZC: Which companies have you worked with in Pakistan?
SB: Telenor, PTCL, Ufone and Zong. Basically, all the major telcos, most of the banks and the government. Institutions that have a lot of data tend to work with us. We have been the leader in Pakistan for many years in analytics. However, we do not do transaction processing or bookkeeping – that is typically done by Oracle or SQL Server. However, if you want to analyse the data and make advanced decisions with it, that is where Teradata comes in. Previously, I worked with LUMS, NUST and other Pakistani universities; I taught a one-semester course (in one week) to professors (who customised it according to their own teaching styles) and helped create curriculums around data science, database design, etc.
ZC: How can further awareness be created about the importance of data analytics? Do universities have a role to play?
SB: A good MBA programme will have at least one course on data and analytics. We need to educate our future decision-makers on how to use data. They are the ones who will be challenging the (not to be ageist) grey-haired senior managers at the top who are not always comfortable using data, because they didn’t have it growing up. The new generation of MBAs is where the appetite for data is going to come from.