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Chapter 2. Database Analyses
The study team collected and conducted various data analyses during this study.
This chapter documents the findings of data analyses, including NEMO-Q
database, DLD High-Value Dataset (HVD), and county office VTR transactions.
2.1. NEMO-Q Database Analysis
The NEMO-Q queuing system was implemented to manage and improve customer
service and waiting time experiences. In this self-service system, customers are
issued a numbered ticket based on transaction type. The system also creates a
database that stores all the transaction data categorized by service type (e.g.,
original driver license or ID card application or renewal) and customer type (e.g.,
in person, by phone, or online). The system provides information to DPS regarding
the wait time and transaction time. Both walk-in customers and customers who
scheduled online (and arrive at the appointed time) will get a numbered ticket with
timestamp. Estimated wait time can be printed on the ticket as well so that the
customer knows the progress of the wait queue. The NEMO-Q system cannot
record the wait time a customer spent outside DLO or mega center offices.
The study team obtained NEMO-Q data from DLD for the period of January 2017
to March 2020. One of the main purposes of NEMO-Q data analyses is to evaluate
the effectiveness of the new LPS employees who were hired starting September
2019. The study team divided the NEMO-Q data into a ‘before period’ and ‘after
period.’ Considering the time needed to post jobs, conduct interviews, check
backgrounds, and perform training prior to facing customers, the study team
selected October 1, 2019 as the split point. The study team used data from January
1, 2019 to September 30, 2019 as the before period to reflect the most recent
statistics, and October 1, 2019 to March 18, 2020 as the after period.
The detailed NEMO-Q data cleaning process can be found in Technical
Memorandum 4. After examining and eliminating invalid records from the NEMO-
Q database, the study team calculated the number of short transactions (i.e., license
or ID renewal) and long transactions (i.e., original license or ID transactions),
average wait times, average service times, average transaction times, and the
percentage of transactions under 45 minutes and 30 minutes for the 73 DLOs
equipped with the NEMO-Q system. The comparisons were made for both
completed transactions and incomplete transactions. Incomplete transactions are
marked in the NEMO-Q database, including duplicate tickets, no-shows, etc. The
comparison results of complete transactions, incomplete transactions, and total
(completed + incomplete) transactions are presented in Table 2.1, Table 2.2, and
Table 2.3, respectively.