Gonzalo San Millan Lopez Lopez

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In the early stages of basketball, the use of data analytics was very low with points and assists as the main stats recorded. Partially this was due to the difficulty to collect the data and gather it. Things changed in 2009 as the league introduced data to the game. Since then the NBA has started tracking the movement of players and the ball during games, with more insights on passing stats, converted points inside and outside the base line and much more granular information such as how frequently does a player shot with his right or left arm. But how did data analytics get so important?.

Three-point era and Houston Rockets

One of its most noticeable changes to the game since its introduction is the increase of three points per game. Analysis showed that if a player has a decent conversion rate (35%) of threes, it is worth taking the risk of shooting a three instead of a two pointer. But why? Because the analysis showed that on average three points led to more points than a two-point shot. The findings fuelled a drastic change in how coaches and players viewed and played the game. Great examples of such are Houston Rockets and Golden State Warriors. Houston Rockets’ general manager is Daryl Morey, a statistician rather than a basketball player. In 2017-2018 NBA season the team set a new record for the number of 3 pointers taken in a season.

Houston Rockets

On the other hand, GSW made it two five consecutive finals, in large thanks to data analytics and to having two of the best three pointers the game has ever seen, namely Steph Curry and Klay Thompson. In the 2015 playoffs, Steph Curry scored more 3 pointers than the entire NBA league combined in 1980. If that was not enough his conversion rate was well above the one of the 1980 NBA league (26% versus 43%). The importance of three pointers have changed the way teams approach the game, with some fans and NBA commentators criticizing the lack of personality and the high level of predictability that statistics bring to a team.

Step curry

Current Landscape

Now days most teams have a data analytics team which work with coaches as well as players to maximize the performance of players and identify those that are key to a team. Currently, data analytics is used in three ways: 1. Designing winning strategies 2. Predicting and avoiding player injuries and 3. Scouting.

Designing winning strategies

The NBA has welcomed data analytics into all its stadium with 6 cameras to keep track of the game to collect a variety of insights during the game. The data is later analysed through machine learning and its output is used by coaches to create new strategies. The insights have made teams better defensively as there is a better understanding of the opponent.

Predicting and Avoiding Injuries

Teams collect information about their players through wearables and even some monitor player’s sleep. This has helped coaches create specific trainings according to a player’s physical condition and fatigue.

Scouting

Perhaps one of the most predictable uses of data analytics. Given the importance of draft picks to NBA teams, coaches use data analytics to better make decisions on which player would be more suitable to create synergies given their current squad strengths and weaknesses. Hence, it has allowed teams much better profile players according to their potential strengths.

Critics Due to Boredom

While data analytics has made teams stronger and reshape the game, many criticize the effects that it has had on teams such Houston Rockets arguing that they have made them predictable. The NBA is all about the suspense and the drama, with teams focusing so much on specific stats it makes player somewhat robotic.

Deep calculation and analysis has also lead to questionable decisions such as the choice of Philadelphia 76ers manager to purposely lose game to not avoid being a mediocre team. The reasoning behind is that the NBA rewards the last teams with a top draft pick which can re-shape the team to the point of becoming a contender to the playoff conference finals.

Source:

https://towardsdatascience.com/nba-data-analytics-changing-the-game-a9ad59d1f116

https://qz.com/1104922/data-analytics-have-revolutionized-the-nba/

https://www.theatlantic.com/entertainment/archive/2015/06/nba-data-analytics/396776/

https://digital.hbs.edu/platform-digit/submission/how-data-analytics-is-revolutionizing-the-nba/#:~:text=Teams%20have%20been%20using%20high,granular%20data%20on%20players’%20movements.

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The global landscape is undoubtedly changing at a relative fast pace for the airline industry. An industry which has been constantly growing year after year. In 2019 there were more than 68 million flights representing 188000 flights per day and a 10% increase in comparison to the 2018. 2019 was a rather weak year for the global airline industry in terms of net profits, with 25.9 billion US dollars generated in comparison to the optimistic forecasts predicted in 2018 of 18 billion US dollars.

COVID-19 and Airlines

The International Air Transport Association forecasted in December 2019 a global net profit of 29.3 billion US dollars for the upcoming 2020 in the airline industry. Unfortunately, the industry has been hit with perhaps the most devastating event in the history of the airline industry. Since the start of the worldwide COVID-19 pandemic airlines have been pushed to their limits financially. The International Civil Aviation Organization (ICAO) has measured the impact of the worldwide pandemic by comparing it to a hypothetical 2020 without the side effects of the pandemic. The ICAO has estimated that 50% to 52% of the global transit has ceased. Less people traveling means less available revenue to airlines. The ICAO determined the global loss in revenue to be in the range of 386 to 399 billion US dollars. It is yet nearly impossible to determine when this situation will be reverted, and airlines will prosper once again Aviation 2020

MCAS and Boeing 737

However, this is not the only critical phase the airline industry has experience in the last years. 2019 a sequence of failures in the MCAS software lead to two tragic crashes involving the Boeing 737. Manoeuvring Characteristics Augmentation System (MCAS) sensor readings are fundamental to assist pilots in correctly stabilizing the plane. However, if the readings are wrong the system will continuously push the plane’s down or upwards to try and stabilize the plane. Reports concluded that the system has not been properly tested and lead to wrong readings which consequently got pilots fighting against the computer over control of the plane. The MCAS system’s failures lead in big part to a tragic event and took the life of 347 passengers. The influence of the MCAS in the crash lead to further investigation over the software. Months later, reports of Boing outsourcing the software engineering of the MCAS software to engineers at 9 US dollars per hour, as an attempt to reduce costs fuelled the doubts regarding the safety and integrity of the company.

What technologies and IT trends might help reverse the declining stage of the Airline Industry?

AI and ML

While none of these technologies will help directly to reverse the current situation regarding the COVID-19 pandemic. There are arguably several technologies which could have an added value to the product offering of airlines and/or the way airlines conduct operations. One of them is AI and Machine Learning. From a customer-oriented perspective, AI could create better recommendations unique to the customer based on their specific needs during a trip, reducing baggage delays and providing real-time updates. Furthermore, AI could potentially disrupt the marketing strategies by tailoring offerings based on the user previous history, demographics, needs etc. KLM is one of the airlines alongside AVA that taken steps towards a digitalization strategy. KLM has implemented AI in their operation systems which has led to better decision making and more robust schedules.

One of the key steps to harvest the benefits of AI and Machine Learning is correctly leveraging data. Although there is currently a use of data analytics, it is relatively low in comparison to other major industries. Moreover, the use of data can be perceived as a natural step forward given the vast amount of data that is available to airlines.

Digital Twins

Digital Twins is another topic which is receiving more attention in the airline industry. The technology encompasses a 3D design of an airport collecting real-time information about planes arrivals and departures, delays, number of people in transit and much more. The technology is to be implemented in the operations room as a touch screen for controllers to have access to the current stage of the airport as well as tracking back historical events and replay them as it happened.

Sustainability and Fuel

Perhaps, an even more disruptive force than the COVID-19 is the rising concerns surrounding sustainability in the airline industry. Aviation currently contributes to 2% of the world’s carbon emissions and it expect to double by 2037. However, it is not only the carbon emissions emitted by plains but also the plastic waste both inside the plane and outside. It is expected that airlines will be pressured by multiple stakeholders, namely: customers, governments, corporate governance, and investors. Although some attempts to fight the negative effects of aviation have been put in place, such as CORISA, which is global target to reduce one third of the current greenhouse emissions by 2040, this attempts only aim to partially offset the effects of the major environmental player: Fuel.

While improvements in Biofuels and efficient engines can decrease a portion of current greenhouses emitted, it is only a partial part of the grand total to achieve the desired stage. Sustainable aviation fuels (SAF) is one of the main drivers to reduce the gap between the target stage and the current one. However, SAFs are only at an early stage of development and they will not be made available in the short to medium future. Furthermore, Biofuels and efficient engines are still overpriced which further put a toll on airlines net profits.