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Smart Baseball Data AnalyticsAfter a grueling 162 games season and numerous post season pennant games, the world stage is about to unfold between the National league champion Los Angeles Dodgers and American league champion Houston Astros. The two formidable teams will face off for the 2017 World Series championship this week and stage an instant classic. But what is more impressive and remarkable are the exertions that each baseball team endures throughout the long season from training, coaching, strategizing, managing, traveling, all while operating effectively and collectively.

Baseball is truly a team sport. Although there are only 9 players on the field at a time, teams encompass a full army of pitchers, backup players, dedicated trainers, hitting/pitching coaches, managers, administrative staff, executive team, and even data specialists. Yes, data specialists. Baseball has always been heavy on statistics, but the sport has evolved systematically (literally) since the early 2000s and have become a synonymous with data gathering and analytics.

The value and usage of data has become insurmountable in baseball. Some purist may say it’s overkill, but tell that to any baseball management team and most would say otherwise. Made famous by the movie Moneyball, baseball has taken on a new approach to finding that winning formula. Spearheaded by Billy Beane (the master mind behind the data analytics) during the early 2000s, sabermetric was introduced to baseball. Briefly, sabermetric gathers and analyze unconventional baseball statistics. Traditionally, statistics in baseball were gathering of the general hit percentage, home runs, RBI, stolen bases, strike outs, and so on. It was more of individual based statistics. But with sabermetric, the data collection shifted toward more granular and to almost every aspect imaginable in baseball.

Sabermetrics began to change how baseball is played and managed. It allowed intricate analysis of how a player would perform based on specific situation. For example, the data would help a pitcher understand his pitches more accurately by analyzing the speed, velocity, rotation, location and even the humidity impact. In turn, this data can be used to help the player adjust his throw accordingly. But even more useful, management are using the data as a tool to scout and analyze players. Furthermore, this allows even predictive analysis that can assist teams play more competitively against other teams or specific players. The data science in baseball has become so relevant that all major league teams now use data analytics.

Data analysis is a major part of baseball and has directly impacted the way the game is played today. What is going on the playing field is overflowing into businesses as well.  Likewise, every business wants to gain that competitive edge. For example, Amazon are supposedly gaining better understanding of its customers from data collected over a period of time to a point where it can actually start predicting what item you may want to reorder and will make appropriate suggestion. This not only increase sales for Amazon, but consequently increase the convenience factor of its customers not having to worry or forget about restocking for a specific item.

Predictive behavior is a major feature of understanding big data and analytics, but another big feature is pattern or preventive measures it can assist with. You may have experienced an incident when a purchase was declined or were alerted of suspicious activity on your credit card. Recently I have. I was at a gas station pumping fuel for my vehicle. I had just used the card to pump fuel for my wife’s SUV about 20 minutes prior. Systematically, the card was declined. I wasn’t sure why, but it wouldn’t go through. Reluctantly, I used my other unrewarding credit card to finish the transaction. Upon checking my credit card app, there was an alert notifying me of potential unauthorized transaction due to recent use of the card at the same gas station within the past half hour. This was big data analytic at work!

Although there are endless analytics and even uncovered use of data, the most common reason to invest in data intelligence is to gain that competitive edge. Here is a short list of how data can be beneficial and used for businesses.

Cost Saving Measures: Data analysis can help smaller entities budget their needs more effectively by identifying areas where cost can be lowered with use of more effective workflow, time management, cost determination, and even forecasting.

Addressing Issues/Questions More Effectively: Data and business intelligence can be useful with information from raw data collection. Additionally, enables quick access to sales data, customer and contact information from system such as CRM to more accurately and promptly address issues or questions.

Customized Experience: With global business approach, having relevant data appropriate for each region, target audience, existing customers and logistics can be critical to business growth. Data analysis allows business can custom tailor products based on regional demand including colors, design, local culture integration, and so on to better fit the needs of the locals rather than targeting an audience with generic approach.

Visual Dashboards: As data collection and analysis become more complex, understanding and using the data can be overwhelming. However, many (if not all) of the data intelligence services now offer a dashboard display with visual simplicity to better understand the meaning of the data rather than trying to decrypt them. This enables far more simple and visual approach for business executives and ownership to help with their decision making process.

Data has become overwhelming over the past decade or so. As data collection grows, so does the analytics, usage, and the advantages. Large companies across the globe understands the value of the data and how it can literally give you the upper hand against your competitors. The biggest (no pun intended) misunderstanding of big data might be the word ‘big.’ Many small and medium size businesses believe big data are reserved for larger entities. This used to be the case, but now with more affordable access to cloud and data services, it is more obtainable than ever before. Data and business intelligence will be the driving force that catapults business to the next level and naturally gain competitive edge. For those who adopt earlier will have considerable jump start to further that advantage. Now, play ball!

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