‘Big Data’ is Revolutionizing the Parking Industry
December, 2014
By Subhash Gowda
“Big data,” “analytics” and “predictive analysis” are buzzwords in online and print media. Thanks to Facebook and Google, they have become ubiquitous across many industries, even in professional sports, where MLB and NFL teams leverage analytics to guide game strategy and to create budget-efficient teams with the ideal player composition. (Some of this trend is a result of Michael Lewis’s book “Moneyball: The Art of Winning an Unfair Game.”)
The success of Facebook and Google, whose business models are underpinned by predictive analysis, can be regarded as an impetus for other industries to pursue new revenue streams through the use of data and analytics.
Despite its obvious revenue potential, the definition of big data is still abstract to some extent. Generally speaking, big data is a large and complex set of data. Yet, on a more detailed level, each company coins its own definition of big data and analytics in alignment with its respective business model.
Big data can be large sets of collective and inter-related data (terabytes or even more per day), which can be used to derive meaningful information to meet a business need. This could be in the form of data to drive decision-making, to build a new revenue stream or to sell aggregated data to
another company.
While data-based business models are not a new concept, what is unique is the interest in big data irrespective of the size. Large retailers, U.S. defense contractors and mobile phone companies have been using data as a key tool in their business models for some time.
However, as the cost to store data has decreased, and the ease of gathering data from multiple sources has increased, coupled with the advancement of complex algorithms to derive patterns from large amounts of data, have helped make big data a reality across all industries.
As technology evolves and advances further, companies are spending less time creating and maintaining a data mart and more time learning about and understanding data. Big data has also created new revenue opportunities as companies monetize data by creating new services or by using data as the foundation for decision-making or to reduce risk.
Big Data’s Role in Parking
The parking industry remained relatively unchanged for many years. But with the evolution and adoption of cellular technology, which allowed parking meters to wirelessly communicate data from the parking meter to a centralized data mart, the role and relevance of big data and analytics increased.
Today, parking programs are data-rich, comprising inter-related data points, such as payment transactions, occupancy data, sensor data, enforcement data, length-of-stay data, meter status data and more. With the appropriate technological blend, these data can be analyzed and organized into usable information, which customers then use to understand and predict customer behavior patterns.
These, in turn, help cities to adjust and refine their parking programs in the following areas: Efficiency Management, Revenue Management and Meter (Device) Management.
Efficiency Management
The main goal of many cities is to improve the efficiency of their program in order to minimize the stress often associated with parking. Efficiency is mainly evaluated by a city’s ability to manage its parking capacity, generate turnover, and predict and address fluctuations due to events and unexpected variables such as accidents or construction.
Big data and analytics can help cities by providing predictive occupancy patterns based on past data and planned events (sporting events/parades/street fairs, etc.).
Capacity data with relation to payment percentage will help the city adjust enforcement staff numbers accordingly to meet the demand. Payment types composition (coin vs. credit card) help collection processes to streamline schedule and frequency of collections. Data on capacity patterns allow the city to adjust rate structures and maximum time stays, which benefits both motorists and retailers/businesses.
Revenue Management
Tracking revenue trends and variations in revenue cycles provides insight into useful patterns that can be refined with changes to program variables such as maximum parking time, rates and enforcement hours. Occupancy trend vs. paid parking spaces could help the city increase its revenue.
Meter Management
Efficient meter management is key to the overall efficiency and success of a city’s parking program. Big data on real-time meter status and faults, in combination with data on past trends, can help meter maintenance personnel mitigate device failure risks, thus reducing impact to capacity and revenue.
Collecting and analyzing user key strokes can help a city to understand meter user interface navigation patterns, while power consumption data based on location can reduce failures.
Looking Forward
The future of many industries will depend on their ability to leverage big data and analytics to improve operational efficiency, generate new revenue streams, and incorporate data-driven decision-making into their organizations.
Parking, which has become a data-rich industry, must also embrace and understand the role of big data and analytics, and in doing so, will help cities implement more efficient and intelligent parking programs.
Contact Subhash Gowda, a software developer for IPS Group, at subhash.gowda@ipsgroupinc.com.
The success of Facebook and Google, whose business models are underpinned by predictive analysis, can be regarded as an impetus for other industries to pursue new revenue streams through the use of data and analytics.
Despite its obvious revenue potential, the definition of big data is still abstract to some extent. Generally speaking, big data is a large and complex set of data. Yet, on a more detailed level, each company coins its own definition of big data and analytics in alignment with its respective business model.
Big data can be large sets of collective and inter-related data (terabytes or even more per day), which can be used to derive meaningful information to meet a business need. This could be in the form of data to drive decision-making, to build a new revenue stream or to sell aggregated data to
another company.
While data-based business models are not a new concept, what is unique is the interest in big data irrespective of the size. Large retailers, U.S. defense contractors and mobile phone companies have been using data as a key tool in their business models for some time.
However, as the cost to store data has decreased, and the ease of gathering data from multiple sources has increased, coupled with the advancement of complex algorithms to derive patterns from large amounts of data, have helped make big data a reality across all industries.
As technology evolves and advances further, companies are spending less time creating and maintaining a data mart and more time learning about and understanding data. Big data has also created new revenue opportunities as companies monetize data by creating new services or by using data as the foundation for decision-making or to reduce risk.
Big Data’s Role in Parking
The parking industry remained relatively unchanged for many years. But with the evolution and adoption of cellular technology, which allowed parking meters to wirelessly communicate data from the parking meter to a centralized data mart, the role and relevance of big data and analytics increased.
Today, parking programs are data-rich, comprising inter-related data points, such as payment transactions, occupancy data, sensor data, enforcement data, length-of-stay data, meter status data and more. With the appropriate technological blend, these data can be analyzed and organized into usable information, which customers then use to understand and predict customer behavior patterns.
These, in turn, help cities to adjust and refine their parking programs in the following areas: Efficiency Management, Revenue Management and Meter (Device) Management.
Efficiency Management
The main goal of many cities is to improve the efficiency of their program in order to minimize the stress often associated with parking. Efficiency is mainly evaluated by a city’s ability to manage its parking capacity, generate turnover, and predict and address fluctuations due to events and unexpected variables such as accidents or construction.
Big data and analytics can help cities by providing predictive occupancy patterns based on past data and planned events (sporting events/parades/street fairs, etc.).
Capacity data with relation to payment percentage will help the city adjust enforcement staff numbers accordingly to meet the demand. Payment types composition (coin vs. credit card) help collection processes to streamline schedule and frequency of collections. Data on capacity patterns allow the city to adjust rate structures and maximum time stays, which benefits both motorists and retailers/businesses.
Revenue Management
Tracking revenue trends and variations in revenue cycles provides insight into useful patterns that can be refined with changes to program variables such as maximum parking time, rates and enforcement hours. Occupancy trend vs. paid parking spaces could help the city increase its revenue.
Meter Management
Efficient meter management is key to the overall efficiency and success of a city’s parking program. Big data on real-time meter status and faults, in combination with data on past trends, can help meter maintenance personnel mitigate device failure risks, thus reducing impact to capacity and revenue.
Collecting and analyzing user key strokes can help a city to understand meter user interface navigation patterns, while power consumption data based on location can reduce failures.
Looking Forward
The future of many industries will depend on their ability to leverage big data and analytics to improve operational efficiency, generate new revenue streams, and incorporate data-driven decision-making into their organizations.
Parking, which has become a data-rich industry, must also embrace and understand the role of big data and analytics, and in doing so, will help cities implement more efficient and intelligent parking programs.
Contact Subhash Gowda, a software developer for IPS Group, at subhash.gowda@ipsgroupinc.com.
