Diving Into Data

Data is often something that is overlooked. The value of data as a product is highly valuable for companies, however. Unfortunately, while companies have started to learn and appreciate the value and investment in data, a lot of companies probably don’t spend time thinking about how data can make their teams better.

On this episode of Diving Into Data, Host TC Riley talked with Ryan Frederick, Principal at AWH, about data as a product, Frederick’s career, and the value of data to improve the bottom line.

Frederick has experience in starting and growing numerous software companies. He specializes in product building and is an analytics problem solver. At his first job at a small business, before the word startup entered the lexicon, he identified a problem that led to the birth of another company. This led him down the path to starting multiple companies. One thing he’s learned all these years is that things will go right and go wrong.

“It’s just the way it goes. You can do a lot of things right and still have it not go well,” Frederick said. “You can also do a lot of things wrong and have it go well. It is not for the faint of heart.”

Frederick has a lot of experience in startups and, in particular, data companies. An excellent place to start is that some companies aren’t thought of as data companies, such as Facebook and Uber. Instead, consumers are using their software to interface with the data.

“You can sort of go industry by industry by industry, and the biggest players from a software product perspective in those industries are really data companies because software is plumbing for data,” Frederick said.

Data. It’s one of the biggest buzzwords today, but it carries a lot of weight. It allows businesses to get real insights into their bottom line. So how do enterprises enable their end-users to interact with data, and how do companies bring business intelligence to the masses?

On this episode of Diving Into Data, Host Thomas Riley talked with Rob Nelson, CEO, Grow, a simple business intelligence (BI) software created specifically for growing companies. They are making BI accessible and affordable so that anyone can get answers unique to their business. The duo talked about data, analytics, and unlocking data in the workplace.

“Data is at the heart of really good decision making,” Nelson said.

The idea for Grow was born from a significant pain point from Nelson’s former company. They were having a hard time wrapping their arms around the data. They tracked KPIs in several spreadsheets and generated reports, but their process was clunky, and they were always looking at stale data.

“The process to log into all these different systems, pull the data, run the calculations, update the spreadsheets was kind of a nightmare,” Nelson said. “We only updated these spreadsheets once a month.”

He talked to some software providers, but he kept getting quotes for over $100,000. The companies also had high failure rates and long implementation times. It wasn’t accessible. He exited and went after the underserved BI market.

“That’s what really got me excited, was this big problem to be solved that everybody feels,” Nelson said. He elaborated that he wanted to create a simple, beautiful solution.

The price users pay for consumer electronics is usually not the primary source of revenue for those that sell them. What’s most valuable is the data they collect on users. If companies can gather and monetize data, consumers get more affordable prices, and tech companies enjoy large profits. But what happens if data privacy regulations throttle this? Will the economy take a nosedive? On Diving into Data, host TC Riley breaks down the economic consequences of data privacy.

“Consumer data is underrated and isn’t factored into the big economic picture. This data largely subsidizes the cost of consumer electronics,” Riley said.

Consumer data has a high value because it fuels ad revenue on digital channels. To illustrate the value of data, consider Microsoft’s acquisition of LinkedIn and Facebook’s purchase of WhatsApp had nothing to do with the tech and everything to do with the data.

Next, Riley offered a refresher on inflation, as it’s another economic force that ties into consumer data value. Riley made this hypothesis. “Inflation is being held artificially low due to the value of consumer data to many companies creating these consumer goods.”

For example, Apple sells an iPhone for $1000 and recoups its money through advertising revenue. The irony is that Apple is championing data privacy with its latest software update.

If data collection restriction becomes the norm, consumer data value will plummet. Should that happen, the economy could be in for a disruption. It may start as Facebook running more ads or no longer being free. Then stock prices fall for big tech, which now makes up around 20% of the S&P.

“If big tech companies are turned upside down with data privacy regulations, their stocks will tumble, as will the entire market. On top of that, consumer goods prices will rise, creating a further tailspin in the market.”

The data privacy battles are heating up, and many consumers are just now tuning in the discussion. That’s because Apple’s latest update will prompt users to opt-in to share data with third-party apps, marking significant changes to IDFA (ID for advertisers). Well, Facebook is upset, but are these tech giants worried about data privacy? That’s what TC Riley is diving into in this episode of Diving into Data.

“Are users more protected? That’s what Apple says, but it seems like more of a shift since they aren’t limiting the data they collect on you,” Riley said.

The commotion from Facebook is under the guise of small business impact, but Facebook may be more upset because most of their users are on iPhones. Small businesses may see some challenges, but they will weather them. “This is what happens when you operate in rented spaces instead of owned ones. Small businesses will adapt. They also have. That’s what capitalism is all about,” Riley commented.

What this change really means is that businesses need to consider a paradigm shift to first-party data. “That’s data captured within your ecosystem about your customers,” Riley explained. If organizations gather customer data through their owned avenues and media, they face no serious consequences when tech companies make changes.

Ultimately, Riley agreed that Apple wins this round because they have the most enclosed ecosystem. It’s their software and hardware. It should prompt companies to move into first-party data collection because everything else is not within their control.

“Everyone complaining is missing the bigger picture. Big tech has a lot of control, and we're caught in a firefight of trillion-dollar companies. It’s not ideal, but better for the free market to decide and not a state or party,” Riley added.

The Ever Given will go down in infamy, and not in a good way. Its blockage of the Suez Canal further crippled supply chains already at their breaking points due to the pandemic. How could one incident have such an impact? It’s all clear when diving into the data, and that’s what host TC Riley does in this episode.

“You can’t underestimate the importance of the Suez Canal to global trade. It cuts 3500 nautical miles and around nine days off the trip between Asia and Europe,” Riley said. The number of shipments that pass through it every day is incredible. Over 1,000,000 barrels of oil and 8% of the world’s liquified natural gas go through it daily. During the debacle, the media went in on the economics, most saying it cost the world billions.

The reality may look a little different. “It was a significant shock to global trade, impacting many businesses, but these numbers are drastically blown out of proportion,” Riley explained. It’s more likely that the true economic consequences won’t be known for some time. Riley called it “an excellent example of data not being incorrect but applied inappropriately.”

While this is an extreme example, businesses do this all the time. So, what’s the real impact? What experts can say is that it affected operating costs for shipping companies, primarily in fuel costs. Another area is insurance premiums, as insurance companies were hit hard by the blockage. For the consumer, it may be negligible or show up in temporary oil price increases.

“The biggest takeaway for me is the impact that global supply chains have on so many businesses and how fragile some of those chains are,” Riley remarked. The data won’t be in for some time, and that’s the story with most global emergencies. It’s a good reminder to take in the entire picture that data paints before drawing finite conclusions.

Data revolutionized the way sports are played and watched, and new technology makes this process even more exact and innovative. Diving into Data is turning the spotlight on LiDAR and its applications in the world of sports. Host TC Riley chatted with his MarketScale team member Shannon Dyer, an Engagement Analyst.

To start, Riley defined LiDAR. “It’s a method for measuring with lasers that’s incredibly accurate and creates a 3-D model with precise measurements.” It’s a growing industry and is in use in several major sports, including gymnastics and baseball.

Dyer spoke about its use in gymnastics, a sport she grew up in. “Fujitsu adapted its LiDAR technology to create something for gymnastics to assist in judging in 2019,” she said. The process included scanning athletes’ bodies then putting cameras at every event to see how the bodies move, helping with the degree of difficulty scores.

It’s also making an impact in baseball. Before the 2020 season, the MLB used LiDAR to create digital models for every park so broadcasters could drop a camera anywhere for various replay angles.

It’s also being integrated into Hawk-Eye technology to improve StatCast to build upon accuracy. “It can capture the position and movements of everyone in the field, including pose tracking. It updates 30 times per second at 18 different data points,” she added.

LiDAR is also playing a role in the in-person experience with sports, specifically social distancing. Companies are adapting LiDAR technology, initially designed for monitoring passenger traffic in airports, to provide real-time crowd density to stadium managers.

What’s next for LiDAR? One critical future use case is taking the human error out of judging, from gymnastics to offsides calls to determining if it’s a catch in football. Dyer noted that Dez Bryant did catch that pass, and that technology would have proved it!

Host TC Riley welcomed fellow Marketscale team member David Hidinger to discuss the data behind economies of scale. They looked at two unique use cases, beer and Girl Scout cookies.

First, Hidinger defined economies of scale. “The concept is that when an industry or firm grows larger, it receives benefits based on its size.”

Those benefits can hit almost every aspect of business, from lower prices for ingredients purchased in bulk to efficiency improvements. To simplify it, Hidinger said, “It’s why you go to Sam’s Club versus Walmart.”

Next, the two discussed beer and breweries. The data shows that macro breweries have shrunk significantly from 1975 to 2019, mainly due to consolidation. On the other hand, microbreweries have exploded in growth. However, they really aren’t direct competitors.

Riley said, “With macro breweries, it’s basically the same beer, so it’s branding and price that drives the purchase.”

Microbreweries aren’t trying to sell or produce at a large volume, so they don’t benefit from economies of scale. They compete on flavor, options, and brand identity. Macro brewers do, but that also means they can’t pivot to a new product without assurance they’ll sell enough to cover their investment.

Girl Scout cookies have a unique production and distribution. This industry also saw consolidation from 29 bakeries to only two. So, why do troops in the same geographic area have different cookies? “Regional councils each choose the bakery the contract with and negotiate separately based on volume,” Riley answered.

The volume of those councils has only data from their region, so forecasting isn’t always accurate. It could be more so if they had a larger data pool. However, they are selling $800 million in cookies each year, at around $5 a box. They probably aren’t leaning into scale as much because it’s a philanthropic model, not a profit-centered one.

Host TC Riley offered his thoughts on best practices, learning from mistakes, and more.

Riley said, “Data will tell the whole story most of the time, not all the time. Always consider what the data can’t show you.”

The first tenet of trust but verify is the source. There are many reliable sources for data, but it’s a good idea to be skeptical. Always verify accuracy for external data. That same approach applies to internal data, too. Riley recommends putting a routine quality control check for data systems. Doing this early and often ensures that you don’t end up with tainted data.

The next principle is to consider other factors. Data doesn’t lie, but it doesn’t always paint the complete picture. Riley shared some data errors he made on internal projects by not thinking about external forces. In one story, comparisons were off because the comparisons were not apples to apples.

The third and last area is don’t believe that simulation data always works in the real world. There are many times when decision-makers, analysts, and companies make this mistake. Riley noted that a good example is the recent Texas power grid challenges. “Many were convinced that considering the diversity of energy sources and large geographic spread along with backups, nothing could go wrong, but it did,” Riley added.

The significant outlier of a cataclysmic event wasn’t in the data mix. While organizations shouldn’t let extreme outliers paralyze them, they need to be aware that it’s a possibility so that they can mitigate the risk in the best way.

Using data to support and drive decisions is good; but only if you do it in the right way — in fact, data used the wrong way is more dangerous than not using it at all.

Throughout the article, as is typical of HBR, great research data, mainly from Gartner, is used to support overall points. However, two specific points demonstrate a lack of data understanding and don't connect to the central message and prediction.

Let's take a look:

68% of employers added 1+ wellness benefit during pandemic, so companies will implement collective mental health days

33% more skills listed on job postings vs. 2017, so employees won't focus on upskilling employees and instead will look to hire those skills or 'rent employees'

Though host Thomas Riley uses this article for an example on this episode of Diving into Data, he said he sees the phenomenon everywhere, all the time.

The takeaway is this: don’t fall into the trap that the author did and think that quoting valid data automatically validates your argument. Data can provide so many insights and be so powerful for any organization, but only if you're cautious about it and use it the right way.

"Data is really cool and can tell you a lot of really cool things. Just don't let it confuse you into thinking things are there that aren't really there," he said.

Data drives decisions of the worlds largest companies but in a world with constant data, how do you make sense of it? Host TC Riley, puts the world under the lens of data and analytics and explores current news, B2B trends, and popular topics.

While stats have always been part of the NFL—teams, analysts, and fans are obsessed with the data and what it means. And so is Diving into Data host TC Riley. TC invited fellow football and data fan Tyler Kern to talk about crazy stats from the 2020 season and what they expect in the Super Bowl.

Riley and Kern discussed some unique stats, some winners and some losers. First up was sensational Tennessee Titans running back Derrick Henry. Riley shared, “He became the eighth player in NFL to rush for 2,0000 plus yards. He also had as many 200-yard, two-touchdown games as any player ever had in his career.”

So how did Henry put up such incredible numbers? Kern said, “It has to do with balance and a better quarterback in Ryan Tannehill.” 

While Henry’s success at running back is special, it’s also one of few because Riley believes that the NFL is “a passing league now.”

Yet those teams overly reliant on passing or running, for that matter, didn’t translate to success. Another interesting stat is that punting is disappearing. “There were only 7.4 punts a game; it had never been lower than 8.4. Why? Because teams went for it on fourth-and-one 66% of the time, which shows teams are using analytics to make better decisions,” Riley added. 

Looking at some losers, Riley and Kern had to talk about the hometown team of MarketScale, the Dallas Cowboys. They gave up more than 30 touchdowns at home. “It was obvious the defense was not well organized, and they didn’t know what they were doing. It was a clear disconnect,’ Kern said.

With a new defensive coordinator and hopefully a healthy Dak Prescott, maybe those Cowboys can turn it around in 2021. 

What about stats that were great for the player but didn’t translate to wins? Deshaun Watson threw for 4,800 yards and 30 touchdowns, but the Texans had only four wins. That’s never happened before. “He had huge numbers, but there was no vision,” Riley said. Watson has asked for a trade, so maybe he’ll be able to win consistently in another system. 

Finally, Riley and Kern gave their predictions for the Super Bowl. While they both admire Tom Brady’s talent and career, they think the Chiefs have his number. “When Brady loses, it's because of pressure, so I’ll be looking at the pass rush of the Chiefs,” Kern said.

Riley added, “The key to the game for the Chiefs will be balance with running the ball. They can’t get too pass-happy.”