Improving postal services with data analytics
The outlook for government-funded postal services has been pretty dismal over the last few years. Operating budgets are tightening while organizations are still expected to provide timely and reliable delivery services at an unrealistically low cost. These policies have resulted in record losses among the world's postal agencies. The United States Postal Service, for example, reported a $15.9 billion loss for the 2012 fiscal year, prompting its officials to scale back delivery services.
Although funded by governments, mailing agencies are not much different from private businesses. They need to provide customers with satisfying products, reduce wasteful practices and effectively market services in order to make a profit. Many companies have used big data tools to address these issues and there is no reason that postal services could not do the same.
CIO reported that Australia Post launched a data analytics program in 2011 in order to monitor cash flow and predict revenue forecasts. The project was successful, with officials reporting as much as a 98 percent accuracy rate. With this information in hand, postal service authorities can predict monthly cash flows for up to four years, giving them ample time to prepare for the financial future.
Discovering more cost-saving applications
According to ZDNet, officials were so impressed with the effectiveness of the data analytics software that they began exploring other applications. Australia Post is currently working on a method to determine public interest in potential products and services. With a better understanding of their marketplace, postal officials can ensure that they do not waste resources investing in unpopular products.
Data analytics can also be used to mitigate customer churn, which has become a major concern for postal agencies recently. With more consumers using parcel services, the logistics and delivery market has become more competitive. Data analytics software can identify the circumstances that lead to a customer dropping services and predict the likelihood that an individual will do just that. With some big data foresight, Australia Post officials could intervene before their customer bolts.
The organization has identified other potential cost saving benefits from its predictive analytics program, including making their armored car cash pickups more efficient. Instead of spending resources on time-based pickups, Australia Post can use data analytics to automate the process and only dispatch vehicles when the amount of money at a location has reached a certain threshold.
As postal service budgets continue to tighten, more cost-effective practices are needed. Using data analytics software built upon a Hadoop architecture, organizations can glean fresh insight into their operations and determine the most effective way to move forward.