Jeff Lipniskis describes his role at PPG as having line-of-business IT responsibilities. As global director information technology, architectural coatings & Latin America, he reports to the corporate CIO and has accountability for IT globally in the company\u2019s architectural coatings business, leads IT for its protective and marine coatings, and has oversight for IT within the company\u2019s research and development organization.\n\nA 21-year veteran at PPG, Lipniskis has experienced a significant portfolio transformation and globalization of the company. In his two decades at PPG, the company has made over 60 acquisitions and has roughly doubled in size in terms of sales. Today, PPG is the world\u2019s largest manufacturer of paints and coatings, operating in 65 countries around the world.\n\nIDG\u2019s Derek Hulitzky sat down with Lipniskis at IDG\u2019s Data and Analytics Summit to discuss how data enables business strategy at PPG.\n\nFollowing are edited excerpts of that conversation. Watch the full video of the conference session for more insights.\n\nOn balancing standardization and flexibility:\n\nJeff Lipniskis: [A]s you look at a transformation built around acquisition, you have a lot of infrastructure diversity, different ERP platforms, a more complex application portfolio. And most importantly, a lot of variation in business process, as you bring these organizations together. And it is at that business process level where data intersects, where our data is generated, where it\u2019s managed. So we, as an organization, are spending a lot of time focusing on standardization.\n\nAnd if I continue on that journey, to think about how do we optimize that supply base as we bring organizations together?\u00a0 How do we optimize our manufacturing and lab footprint and consolidate that and have it at the right size?\u00a0 How do we create a customer experience that never feels like you\u2019re doing business with sixty companies that came through acquisition, but you deal with one PPG.\u00a0 And data is a key part of that, that drives that experience.\n\nBut, at the end of the day, we need to be flexible on the IT side, to be sure we\u2019re hitting the mark on these business outcomes.\n\nOn good governance:\n\nThe core for us starts around governance and governance globally, having a good master data management and data enrichment program and process standardization and continuing to evolve that. \n\nThen we looked at the next pillar of that strategy, which is around that data architecture development, getting to a common view of data and definition, while you have sources across disparate systems.\u00a0 How do you tie that together, and across multiple lines of business?\u00a0\n\nOn the right tool(s) for the job:\n\nWe, as a Microsoft client within Azure, we\u2019ve worked with Microsoft toolsets around reporting and analytics and so forth.\u00a0 But then, as you move to the AI\/ML world, what you will see, from our perspective anyway, is you\u2019ll start to see some variation, because it becomes more fit for purpose than one size fits all.\u00a0 I mean it\u2019s about what is the most ready model or most ready tool.\u00a0 And that can get you into a multitude of different suppliers and sometimes you\u2019re connecting multiple clouds here, multiple solutions to build out that model or capability.\u00a0\n\nOn investing in data architecture:\n\nI would be the first to say we came from a very low level of maturity, and we arrived at the current architecture by bringing in outside expertise to assist us.\u00a0 Our architecture continues to evolve.\u00a0 We are building internal talents and capabilities today, so we\u2019re continuing to keep that architecture current and grow it.\u00a0 I will say if we could turn back the clock, investing more up front in architecture would have helped us in the long term.\n\nOn data readiness:\n\nWe\u2019re really focusing on all new system implementations, to be sure we\u2019re not creating more data and more legacy that\u2019s not AI ready.\u00a0 And you need to create data quality metrics, you need to do audits, and validate from day one, that even if you aren\u2019t putting the data in a model, it will get you to where you want to go, in one year, two years, three years, so you don\u2019t get a bad surprise down the road.\u00a0\n\nOn what\u2019s next for PPG\u2019s data strategy For us it\u2019s going to be one of continuing to mature the foundation that we have in place, and I think we have a good base to build upon. And building upon this by learning and adapting and continuing to be flexible. But if I look on that horizon, we will definitely increase the focus and see more impact from AI and machine learning, and we\u2019ll see that continuing to grow rapidly, if not, I\u2019ll even use the word \u201cexponentially,\u201d as we have more data readiness. I think really that\u2019s the next horizon is AI\/ML at scale.