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132 Big Data Analytics for Connected Vehicles and Smart Cities What Are Analytics? 133

6.7 Analytical Performance Management for a Smart City

As discussed in Section 6.5, the use of analytics will go beyond reporting to
provide smart city managers with the ability to influence the performance of the
city from a transportation perspective. This could be viewed as an extension to
existing approaches to performance management and transportation. The use
of analytics not only adds an extra dimension but also reinforces the need to
consider the entire performance management process and not simply measure-
ment. Analytics places a focus on the conversion of data to information and
the use of information to create actionable strategies and insights. The use of
analytics provides an extra layer in the analysis process of big data in the smart
city. Analytics differ from KPIs or performance measures that are typically used
for transportation service evaluation.
In the field of performance management, the term KPI is used to describe
the parameters or data that are collected in order to measure performance. As
discussed earlier, that is the difference between an analytic and a key perfor-
mance indicator. Figure 6.3 [2] shows a list of KPIs from a European report that
was designed to provide input into a cooperative framework for the application
of advanced technology to transportation. It should be noted that the European
experience with respect to analytics-driven performance management for trans-
portation is slightly ahead of that of the United States at this point.
Note that each of the seven KPIs focuses on one aspect of transportation
data. In comparison, an analytic typically draws on multiple data items and
creates the relationship between them. For example, the analytic equivalent of
KPI N1 would combine the change in peak period journey time data with addi-
tional data regarding the investment in intelligent transportation systems along
the corridor to provide a characterization of the effectiveness of the investment.
The analytic would be the percentage change in peak hour journey time per
dollar invested in intelligent transportation systems along the corridor. Note
that Figure 6.3 contains both long-list and short-list KPIs. The long list of KPIs
was the result of a series of interviews with transportation stakeholders in Eu-
ropean Union member states and industry experts. The short list represents an
amended version of these KPIs, taking into account the inputs provided during
a stakeholder workshop.
In fact, the name KPI provides insight into its use. The last word in the
expression, indicator, conveys that these parameters are designed to indicate
performance rather than provide insight into trends, patterns, and relation-
ships. While analytics are not a substitute for KPIs or performance measures,
they are a valuable addition to the tools that we can use for performance man-
agement in transportation and the smart city.