From a lone statistician toiling over narrowly defined problems for the marketing department, to a C-level executive overseeing a mission-critical area impacting every function of the company, the meaning of “data and analytics professional” has changed a lot in recent years. A. Charles Thomas’s career has reflected those developments.

Thomas, who is General Motors’ first-ever chief data and analytics officer, shared where corporate data analytics has been, where it’s going, and the evolution of chief data officer roles, in a keynote at the recent Wharton Customer Analytics conference “Successful Applications of Analytics.” He spoke from his experience not only at GM, but also other major companies, including Hewlett Packard, the United Services Automobile Association (USAA), and Wells Fargo.

During the late 1990s, he said, data analysts were typically individual contributors working with transactional data involving marketing, credit, and retail. “The [data analyst’s] reputation was ‘a smart guy,’” said Thomas. “You want an answer, you come to Charles.”

Manufacturers are constantly tweaking their processes to get rid of waste and improve productivity. As such, the software they use should be as nimble and responsive as the operations on their factory floors.

Instead, much of the software in today’s factories is static. In many cases, it’s developed by an outside company to work in a broad range of factories, and implemented from the top down by executives who know software can help but don’t know how best to adopt it.

That’s where MIT spinout Tulip comes in. The company has developed a customizable manufacturing app platform that connects people, machines, and sensors to help optimize processes on a shop floor. Tulip’s apps provide workers with interactive instructions, quality checks, and a way to easily communicate with managers if something is wrong.

Managers, in turn, can make changes or additions to the apps in real-time and use Tulip’s analytics dashboard to pinpoint problems with machines and assembly processes.

Alfalfa, oats, and red clover are soaking up the sunlight in long narrow plots, breaking up the sea of maize and soybeans that dominates this landscape in the heart of the U.S. farm belt. The 18 by 85 meter sections are part of an experimental farm in Boone County, Iowa, where agronomists are testing an alternative approach to agriculture that just may be part of a greener, more bountiful farming revolution.

Organic agriculture is often thought of as green and good for nature. Conventional agriculture, in contrast, is cast as big and bad. And, yes, conventional agriculture may appear more environmentally harmful at first glance, with its appetite for synthetic pesticides and fertilizers, its systems devoted to one or two massive crops and not a tree or hedge in sight to nurture wildlife.

As typically defined, organic agriculture is free of synthetic inputs, using only organic material such as manure to feed the soil. The organic creed calls for caring for that soil and protecting the organisms within it through methods like planting cover crops such as red clover that add nitrogen and fight erosion.

It’s 1 p.m. on a sunny afternoon in July—smack dab in the middle of summer break—and a perfect 75° outside, but Jonathan Park is laser-focused. Though he could be strolling down a beach, or at home browsing social media, this 16-year-old is bent over a lab bench, intently pipetting reagents to run an Amplex Red assay.

Park, a soon-to-be junior at Dublin High School, is part of the 2019 cohort of the Introductory College Level Experience in Microbiology (iCLEM) summer intensive, hosted and run by the Joint BioEnergy Institute (JBEI) in Emeryville, California. First launched in 2008, iCLEM immerses local Bay Area students in the biological sciences—and gives them a taste of day-to-day life as a scientist—through an eight week-long blended curriculum of instruction, hands-on basic laboratory skill training, and in-depth tours of working labs within JBEI, Lawrence Berkeley National Laboratory (which manages JBEI), and local biotech companies. The students, who receive a stipend so that they may attend the program in place of a summer job, utilize their newfound knowledge by conducting independent research projects and presenting their findings at the end of the program.

In manufacturing, standardization in production and process control leads to increased profitability and cuts down on many siloed problems that can plague even the most quality-focused organization. But when you have multiple, disparate plants around the country or the globe, standardization can seem unattainable, as each site operates more like an island with its own way of doing things.

I previously worked with one company that had numerous plants throughout the United States and Europe. Over time, each site had developed unique practices. One specific issue that came up was whether to use the metric system for quality data collection. Unfortunately, the company did not standardize. So, when it was time to run cross-plant reports, the results were in different units, presenting a challenge to comparative analysis.

In contrast, I worked with a separate organization that was very adamant about using a standardized approach and implementing the same quality management system at every site. Standardization made it easy to deploy the system to approximately 80 plants in merely 18 months. In addition to streamlining deployment, standardization enabled the company to perform enterprisewide reporting for better decision-making.