Introduction
Education has always
been an important cornerstone of our social structure and economy. Higher
education institutions are a vital component of the educational landscape. They
need to keep changing to cater to the demands of the students as well be
efficient with their delivery. But have they been able to leverage data to
their potential especially in emerging countries such as India?
With our experience we
can conservatively say the shift has been happening with some institutions
ahead and others still grappling with the operational level issues.
Traditionally education institutions have been collecting data for operational
purposes or academic purposes but then is it the end of the value we can derive
from this treasure trove of data? The answer obviously is no. Business
Intelligence can not only show the reality through indicators but also convey
why a certain event may be happening, predict it and ultimately prescribe in
case required. On a systemic view, Business Intelligence helps decision makers
to not just see but act effectively.
Value Propositions
For our particular case, we will be showing high
level example usage of business intelligence and its impacts. Talking about the Indian context, a report by
Times Higher education in the year 2013 revealed that despite producing world’s
brightest students and academics, none of the universities featured in the
top-200. There were various metrics such as faculty research, employer
reputation, academic reputation, faculty-student ratio etc. which the
universities needed to track and take action. So how can Business Intelligence
help us?
Let us look pictorially at an education firm in terms of areas where
business intelligence can help out. The classification below is just representative
of the education domain and is in no way exhaustive.
Figure 1: Representative Classification
diagram of a typical higher education firm
The leaves of the classification diagram give an idea of the area of
application of business intelligence for a typical higher education firm. From
tracking Staff performance to understanding the performance of the students
there are opportunities waiting to be tapped at each of the leaves.
We will take one example each showing how both reporting and
analytics can help firms understand the academic as well as administrative
aspect of education.
Example1: Reporting Lead
Conversion from Leads generated
For a private education firm Student Leads are one of the
most important aspects to delve into. BI
Reporting can help you to keep track of your Lead and
show the nature of the leads generated and their conversion to actual students.
Student Conversion as a Key Performance Indicator can help to
understand campaign effectiveness, marketing staff performance, geographical
split of the potential students etc. This then helps you to decide where to
have campaigns; where to work on your campaigns and how to deal with interested
leads and convert them into full time students.
Reporting can cover each and every aspect of a higher education
institution with Key performance Indicators (KPIs). But again putting the “Key”
in KPIs is very important for reports to make sense. It could be a combination
of previously used indicators, industry standards and descriptive analytics.
Let us now turn
our focus purely to analytics.
Example 2: Predicting Student Performance
Analytics can play a very important role in understanding education
from both academic as well as administrative angle. Almost all the leaves in
figure 1 can be understand fully with the help of analytics. But as an example
let us take student performance.
We need to first understand Students through descriptive analytics
right through their life cycle in a campus. We can then use this analysis to
feed in to our predictive models to predict the performance of the students
before it actually happens!
There are various algorithms which can be employed to achieve this.
Once we predict the performance the next steps would be to employ prescriptive
analytics to decrease failure rates of the student. This in turn starts a loop
which can easily be shown below:
Figure 2:
Loops showing how predictive model can affect student learning and firm
revenues
The above loop R2 shows how student performance prediction is leading
to effective targeted student interaction which leads to decreased failure
rates which ultimately ends up increasing student grades and also increasing
revenues. Increased revenues can then be used again for increasing investment
on better predictive Models or infrastructure or faculty which keeps both the
loop R1 and R2 going. So we end up creating a loop which helps the firm to keep
growing with time.
If we take
another look at the figure, we find that it takes time even with increased
faculty standard and infrastructure to have effective targeted student
interaction in loop R1. This is represented by two parallel lines cutting
across the arrow towards effective targeted student interaction. But predictive
models can pin point on individual students with their performance and help the
faculty and administration to take right steps to help these students. The
effectiveness of the steps taken can then be easily be tracked by reporting the
right performance indicators.
Steps Ahead
These are just one of the many places where Business Intelligence
reporting and analytics can help an education institution to not only
understand students but help earn more revenues which in turn helps them to
grow effectively. With the data driving decisions in almost all the domains why
should not educational institutions aspire to be more efficient, effective,
follow benchmarks set by the best institutions and ultimately set benchmarks.
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