Passing the Ball: 3 Lessons in Analytics Collaboration from Basketball
Content Marketing Manager, Sigma
2020 has been a tough year for sports fans everywhere. The rise of the global coronavirus pandemic has left the world without its favorite sporting events. From cancelling baseball to soccer, to basketball and now even the Olympics, sport associations have taken necessary precautions to help lower the spread of COVID-19 and “flatten the curve.” In times like these, we’re all faced with unparalleled challenges — and must work together to rise above and overcome adversity.
Those who follow basketball know that without the coronavirus, today would be the finale of college sports’ most exciting tournaments: NCAA March Madness. We’d be watching the highlights on SportsCenter and recounting our favorite plays with colleagues. Instead, entire offices have gone remote, something none of us expected just a month ago.
But even in the midst of a global emergency larger than any of us have ever experienced — where our lives feel very different and societal norms seem all but forgotten — we can learn from our favorite sports teams and players currently on hiatus. Lessons in collaboration that may help us get through the challenges we face in both our personal and business lives during an era of remote working and social distancing. Right now, governments, businesses, and citizens are working to curb the spread of COVID-19. Along the way a mantra has emerged: “we’ll get through this together.” While sports may be on hold, this collaborative attitude is one sports teams know well.
So, in light of the NCAA March Madness cancellations, let’s take a look at some past moments and lessons basketball has to offer us in a time where collaboration is needed most.
Lebron James and the tournament that got away
Basketball fans often discuss who the best basketball players are, and what makes them so great. The answers have changed over time. Today, most picture Lebron James in their head when asked about the best player in the game. And the data backs that up. He’s paralleled Michael Jordan (the GOAT to beat) in almost every category, and King James’ reign is far from over.
Lebron has racked up some impressive wins and championships during his career. But one series sticks out in everyone’s head, and that’s the 2017 NBA Championships. That series was as divisive as they come for basketball fans. The Golden State Warriors and Cleveland Cavaliers went head to head again after James and the Cavs took home the championship in 2016. While people have strong opinions on that series, some exciting things happened during those games that shouldn’t be forgotten.
After an already fantastic season, Lebron chalked up his eighth triple-double and helped the Cavs break NBA Finals point records. But the Warriors still walked away with the trophy despite playing against the best player on the court. So how did the Warriors do it? The Warriors played exceptionally well as a team together and outshined Lebron and the Cavs.
Sure, there’s no doubt that the Warriors had a more than impressive starting lineup that year after snagging Kevin Durant as a free agent. But there’s no way a single member on the Warriors could have gone toe-to-toe with Lebron that year and won. And before you write off the win as a Yankees-style talent strategy paying off, or that the Warriors built an unbeatable team, many would argue it was great teamwork that won those games.
Obviously, the Warriors can lose, having lost games since then, including to the Cavs and another NBA Championship to the Raptors. However, in 2017, their on-court collaboration — through excellent ball-handling and selflessness — was what ultimately helped them take home the championship.
That series was a great example of what makes basketball winners win: talented people working together, passing the ball, and communicating effectively. There are so many valuable lessons we can learn from those games (and other moments in basketball history) and apply to our work, especially when it comes to data analytics. Analytics is a field that is growing increasingly collaborative as companies expect business teams to act on data insights, and use those insights to drive better cross-functional decisions daily.
Why top talent isn’t enough
A team roster flooded with individual talent isn’t always enough to guarantee success. History shows us that there are a lot of reasons talent doesn’t always define success. Whether it’s an individual player chasing a record, thinking they’re the only ones who can put points up while others remain open and ready to score, or taking risky shots when a safer play is available.
Talent wins games, but teamwork and intelligence win championships.
American basketball player
There is often a tradeoff between top talent and teamwork. At a certain point, individual ability may affect intrateam coordination. Research from Columbia University shows that in basketball, teams with the highest levels of top performers had fewer assists, defensive rebounds, and lower field-goal percentages than their peers. Added up, these shortcomings in strategic, collaborative play undermined a team’s effectiveness over time.
Compared with other sports, such as baseball, which experts claim involves less interdependent play, concentrated levels of top talent don’t produce the same effects. These findings help paint a picture: In areas that require coordinated, strategic efforts, teamwork — not just high levels of individual talent — is needed to get the job done. These lessons apply beyond the court to corporate teams, financial research groups, and brainstorming exercises.
When it comes to analytics, your company has probably concentrated its top data talent on the data team, which makes sense. But keeping all the data talent on one team leads to bottlenecks, and may even be hurting your ability to become data-driven. If there is anything we can learn from basketball, it’s that it pays to increase collaboration and work as a team to tackle challenges. That way, everyone can work together with data to solve business problems.
Here are three lessons we can learn from basketball to help us function better as data-driven companies.
Hone your court vision
Those familiar with basketball know all about “court vision.” Court vision is the ability to focus and keep track of everything happening in real time on the court. Players that hone their court vision can see what others can’t — and they can use it to make the next great play or score against the competition.
The epitome of excellent court vision will forever conjure memories of Jason Kidd. Known for having “eyes in the back of his head,” Kidd could spot open teammates, make unforgettable passes, and create plays where they otherwise wouldn’t have existed. His court vision was unparalleled.
The ability to focus on what’s happening around you and make the right play at the right time doesn’t just make a great basketball team — it also makes a great company. Today, data analytics and business intelligence solutions give companies the ability to see what’s happening in real time across the entire organization. By connecting multiple data sources, eliminating information silos, and surfacing insights, the right teams can make the right decisions at the right moments. This might mean targeting a specific market poised for growth ahead of the competition, releasing new products customers want, or catching an issue early — before it grows beyond containment.
Data teams need to invest in their own court vision while also helping other groups find it. As more companies seek out data-driven strategies, departments traditionally reliant on dashboards or reports now need to analyze data themselves. With the right mix of domain knowledge and court vision honed through data literacy, data teams and business teams can work together to guide important decisions, understand challenges, and ultimately create the play that nobody saw coming. A sharp court vision can help make the quarter — or even the year — a win for your department and the company.
How can your company hone its court vision when it comes to analytics? Ensure you’re investing in solutions that make data accessible and approachable to business teams. Go beyond dashboards and provide self-service analytics tools that put them in the driver’s seat. You’ll also want to make sure you’re speaking the same data language across the company, and providing analytics training to boost data literacy. Together, these go a long way in building a collaborative data culture that stands out above the pack.
Don’t dribble, pass
If you ever played a pickup game on the playground as a kid, you’re probably familiar with the “ball hog.” Nobody likes a ball hog, and being one doesn’t help the team win.
In basketball, teams that advance the ball up court faster than their opponent tend to be the winner. There are two ways to get the ball up the court: dribble or pass. Passing is 2X faster and more effective than dribbling when you’re trying to move the ball and make a play. Any good basketball player knows that a great passing game is about getting the ball to an open teammate so they — not you — can score.
Even when you’re the greatest at what you do, passing the ball to your open teammate so they can score is usually the right choice. Think back to watching the ‘90s Chicago Bulls. They had two of the best players in the game, Scottie Pippen and Michael Jordan. Both, of course, were phenoms on the court. But it wasn’t just their skills that helped them bring home six titles in eight years during the ‘90s. It was their ability to play as a team and pass the ball to make plays when it mattered most. They never let their talent get in the way of teamwork — and the entire team won as a result.
In business, the ability to “pass” and collaborate effectively is worth its weight in gold. Everyone has a specific talent and people are experts at what they do. But sometimes the hardest play to make is admitting you may not be the best person to take the shot. In these cases, you shouldn’t be afraid to pass, collaborate, and encourage others to go for the goalpost.
The latest self-service BI and analytics software is helping data teams pass the workload — and the data — to other business units. These “assists” are driving up the scoreboard faster than ever before. The players traditionally left on the bench are finally joining the game. Meanwhile, BI bottlenecks are breaking down, questions get answered sooner, insight sharing is at an all-time high, and people are making better business decisions because of it. A great example is the evolution of data modeling, which has traditionally fallen on the data teams. New approaches to data modeling like automation and visual interfaces have made it possible for domain experts to play a more significant role in shaping data models, effectively adding calculations, definitions, and overall business context to data sets. This innovation is in no small part thanks to lower technical barriers and a greater data context these tools deliver.
Innovations in BI and analytics solutions are helping spread the workload, boost productivity, and decrease time to data insights. This is teamwork at its best. Consider asking yourself how you might be able to up your company’s data game by passing the ball more often, and bringing in players from the bench.
Stay humble and share the credit (and the insights)
Rick Pitino has coached basketball teams for the better part of 50 years. He’s coached in the NBA and NCAA — most notably serving as head coach at the University of Louisville for 16 years. In that time, he led multiple schools to the NCAA Championship, won 700+ games, and wrote a book. His teams were considered some of the most consistently high-performing players, and always tough to beat. In a 2013 interview, he shared that “humble people share the credit and wealth, remaining focused and hungry to continue the journey of success. Humility allows that true meaning of sharing credit toward others, preserving the inner dignity that we all need.”
In basketball, talent can help you win games, but collaboration is needed to win championships. A team that plays selflessly and remains humble on the court is one that can look beyond individual scorecards with a greater vision for the future.
Success in business (like basketball) requires people to cooperate and work toward goals that are beyond the capability of any one individual. Many business units must come together to support a shared vision to compete and thrive in the market. How a company treats its employees and builds an internal culture is at the foundation of that success. When people believe they are part of something greater than themselves, they act differently, and the effects of those actions can have a profound impact. By building a company data culture that encourages teamwork over individual success, you can accomplish great things together.
To me, teamwork is the beauty of our sport, where you have five acting as one. You become selfless.”
Duke University Basketball Coach
Like credit on the court, analytical insights are only useful when they get shared. But for too long, data has been kept in an ivory tower, out of reach from those most likely to benefit. Thankfully, that is finally starting to change. Business intelligence used to be reserved for the few, mostly in the C-suite, but today people in every department are integrating data analytics into their workflows. Not only is this driving smarter, more informed decisions, but it’s also keeping us humble.
We can more accurately measure what’s working, identify failures, and turn things around faster than ever. As more data-driven companies emerge every day, we’re quickly moving to a future where entire organizations can think as one, share better information, and make the right play at the right time, together.
The rise of collaboration in data analytics
The art of collaboration is nothing new in business, but it is in analytics. Traditionally, individuals dominated the arena. That’s changing, though. Companies now expect more people to become comfortable working together with data to make discoveries and inform strategy.
Collaborative analytics tools like Sigma are leading the charge to a more insight-driven, collaborative future of business. The same teamwork principles that basketball teams employ to win championships can apply to analytics.
In a time when people around the globe are working remotely — and data is being used to help understand the viral threat, rework business strategy, and contingency plan for the unknown ahead — these lessons in collaboration may be more important than ever.