The summer is heating up here in the States, and baseball season is jumping into high gear. America’s pastime has been all about data since the first box scores were written down, but modern analytics are changing how pitchers and hitters interact. Check out how Major League Baseball (MLB) is using data to crack down on “sticky stuff.” And then dig into a security doubleheader of stories that caught our eye this month, as a concert hall in Latvia relies on analytics to protect this unique cultural institution, and we also look at how in-person retailers will evolve in the new era. 

Before we dig into those storylines, we also want to take a moment to celebrate another big story this month, the announcement of the Sisense Extense Framework. This powerful technology enables users in your organization to get actionable intelligence right where they spend their time, such as in Slack, Salesforce, and Google Docs and Sheets. They’ll be able to collaborate better around data and even automate steps in their processes. Sisense Extense Framework frees organizations from vendor lock-in and creates a variety of cohesive user experiences across homegrown, native, and Sisense-related applications. 

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Major League Baseball battles against pitchers’ use of “sticky stuff” — backed by data

Baseball’s relationship with data stretches back almost to its inception. The box score was developed by sportswriter Henry Chadwick in 1858, and over 150 years later, statistics, data, and analysis have revolutionized the sport. Sabermetrics and Moneyball are usually top of mind when people think of analytics in baseball, but more recently, analytics have been put to a different use by the league management, according to The Washington Post: preventing pitchers from putting excessive spin on their throws via the use of “sticky stuff.”

Pitchers have long used spit, rosin, and other substances (referred to by MLB simply as “sticky stuff”) to get a firmer grip on the ball, giving it increased spin, which can cause it to perform in unexpected ways that batters find confounding. While this is good for the team’s performance (more strikeouts), pitchers were maybe enjoying a bit too much success. A spike in strikeouts was spotted when poring over the league’s copious amounts of data, and umpires were ordered to start checking pitchers and equipment for any contraband substances. 

Beyond the spike in strikeouts (which would have been noticeable by sheer mathematics), researchers at The Post also relied on another time-tested sports-analysis method: watching tape. They studied hours of games to discern pitcher behaviors (reaching into a cap, touching hair, etc.) that could indicate the use of banned substances. It’s easy to see how an image-scanning AI system could do this task for them and flag human officials to take action if they see a particular pitcher engaged in red flag behaviors, before the game is over and the strikeouts are tabulated. Modern sports venues also boast more cameras and other connected equipment than ever before, making detecting excessive spin on a ball during play more possible. With actionable intelligence like this being generated on the fly during play, umpires could be notified to look into matters when they have the best chance of making a difference. That’s the true power of embedded analytics: giving people the information they need to take the right action at the right time, on the field or anywhere else in life. 

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More secure stores with analytics

Are you back to shopping in person yet? Vaccination rates in the U.S. and elsewhere are steadily climbing, and people are resuming in-person buying behaviors, eating in restaurants, and even enjoying films indoors. The pandemic has driven changes in almost every industry, and brick-and-mortar retail is no exception. As stores look to “reopen” (many front-line workers will tell you that they never really closed), exactly what the in-person shopping experience looks like is evolving. 

Much like the connected baseball stadiums mentioned above, the modern retail outlet is a veritable panopticon, teeming with cameras and sensors. While these technologies are mainly geared toward stopping “shrinkage” or theft of product, they can also be used proactively to measure occupancy in stores still wary of overcrowding during a pandemic phase where neither mask use nor vaccination is absolute. “Buy online, pick up in store” (or BOPIS) has become increasingly common in a variety of real-world shops, minimizing contact for shoppers and workers alike. In all these cases, real-time analysis of workforce numbers, store occupancy, inventory levels, and in-store/online commerce levels needs to be integrated into centralized analytical platforms. 

The increased amounts of data being generated by in-store sensors and coordinated with online shopping habits can help stores become not just safer but more productive, using heat maps and adjusting displays based on where shoppers spend the most time as well as rotating low-performing items out and more successful ones in. Data and analytics are key to evolving every kind of business. Equipping front-line workers in brick-and-mortar shops of all kinds with actionable intelligence based on changing conditions will help them do their jobs better, stay safer, and deliver better service. Relatedly, customer-facing apps fueled by their own versions of the same information can make product recommendations, surface deals, and handle customer service needs. 

Analysis protects Latvia’s cultural legacy

Ventspils is the fifth-largest city in Latvia, sitting on the shores of the Venta river. One of the country’s cultural centers, Ventspils is renowned for music festivals and classical concerts. So it made perfect sense in 2019 to open a beautiful new concert hall there. The facility’s primary acoustic concert hall seats 600, and its outdoor amphitheater has room for 1,000. It also boasts a smaller concert hall, recording studio, the Children’s Music School, and the Ventspils Music School. 

The concert hall and the associated institutions safeguard Latvia’s vibrant cultural history, but they also need to be protected. Since the onset of the COVID-19 pandemic, the building has been mostly empty, making it a perfect target for vandalism and theft. In a story that will only become more common as the pandemic rages on and security infrastructures become more developed, the security team at Concert Hall Latvia turned to analytics to more efficiently secure the facility.

“We formulated a solution which met the needs of the concert hall around the clock,” says Aleksandrs Šnevels, a Technology Solutions Director there. “A responsive system which could quickly pick up any potential threats to the building, which our team could respond to in a safe and timely way.”

The expense of employing security workers around the clock to protect an empty building is more than many organizations can afford (or want to spend). The security system uses AI to scan camera footage and can accurately discern between humans and animals, as well as figuring out if a human is just passing by or if they are behaving in a manner consistent with a threat to the building, especially vandalism or graffiti. When these behaviors are detected, human agents can be notified to react in time and handle the situation.

Much like in the shopping and baseball examples above, real-time analytics embedded into workflows can provide workers with the information they need, when they need it, and recommend next steps, thus empowering (but not replacing) actual humans. Whether it’s on a ballfield or in a concert hall, this world of data is for humans. 

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Jack Cieslak has written for and about the tech world for over a decade, having worked for Amazon, CB Insights, and others, writing on topics ranging from ecommerce and VC investments to crazy product launches and top-secret startup projects.

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