UPI #1 Metrics Matrix : e-Governance Student Online Services -

Metrics matrix for the given services data, we want to transform the qualitative and selection-based inputs into quantifiable metrics that can be measured and analyzed. This will help in assessing the digital services offered by the university in a structured manner.

Proposed Metrics Matrix for University E-governance Student Services

Metric Name	Description	Measurement Type	Possible Values / Scale	Weight	Calculation / Interpretation
Service Availability	Whether a service is offered or not	Binary	YES = 1, NO = 0	2	1 if YES, 0 if NO
Year of Implementation	The year in which the service was implemented	Time / Year	2020-2021 → 1, ... 2023-2024 → 4	1	Higher is better (recent implementation = higher value)
Number of Requests Handled	Volume of requests processed through the service	Numeric	Input number (e.g., 0 to n)	3	More requests indicates higher usage / importance
Payment Required	Whether the service requires payment	Binary	YES = 1, NO = 0	1	0 preferred for student-friendly services
Online Payment Available	Whether online payment is supported	Binary	YES = 1, NO = 0	2	1 indicates better usability for fee payment
Action Performed	If an action was taken related to the service data (e.g., Update, Delete, None)	Categorical	Could be coded as No Action = 0, Updated = 1, Deleted = -1	1	Positive action = +1, No action = 0, Deleted = -1
Screeshot/URL Provided	Whether screenshots or URLs are provided as proof/presentation	Binary	YES = 1, NO = 0	1	Provides evidence of implementation

Sample Metric Calculation for a Single Service (Example)

Alumni Forum
- Service Availability: YES → 1 x 2 = 2
- Year Implemented: 2022-2023 (3) x 1 = 3
- Number of Requests: say 100 → 100 x 3 = 300
- Payment Required: NO → 0 x 1 = 0
- Online Payment: NO → 0 x 2 = 0
- Action: No action (0) x 1 = 0
- Screenshot Provided: YES → 1 x 1 = 1

Total Score = Sum = 2 + 3 + 300 + 0 + 0 + 0 + 1 = 306 (This could be normalized later)

Additional Notes:

Weight values can be adjusted based on priority (e.g., availability and usage may weigh more).
Numeric fields like "Number of requests" may need normalization (e.g. min-max scaling) before aggregation.
Can be extended to calculate Overall Digital Readiness Score for all services combined.
For CAS Guidelines issued: can be a Yes/No metric to assess policy compliance.

If you want, I can help you build an Excel template or pseudo-code for calculation based on this matrix! Would you like me to?

Below is a simple Excel template structure you can create for calculating the Metric Scores for all your e-governance student services based on the metrics matrix discussed earlier.

Excel Template Structure for Metric Calculation

Service Name	Available (Y=1, N=0)	Year Implemented (2020-1 to 2023-4)	Number of Requests	Payment Required (Y=1, N=0)	Online Payment (Y=1, N=0)	Action Taken (Updated=1, None=0, Deleted=-1)	Screenshot/URL Provided (Y=1, N=0)	Weighted Score Calculation (Formula)
Alumni Forum	1	3	100	0	0	0	1	=B22 + C21 + D23 + E21 + F22 + G21 + H2*1
Digital Academic Calendar
Digitisation of Library
Online Admission System
Online Attendance Mgmt.
Online Courses LMS
Online Examination
Online Fee Payment
Online Grievance Redressal
Online Issuance Certs
Online Leave Mgmt.
Scholarship Portal
Student Dashboard

Instructions for Use

Fill in columns B to H for each service as per your data (for example, "Alumni Forum" is filled as shown).
Use the formula in the Weighted Score Calculation column to compute the total weighted score of each service.
Weights used are:
- Availability (B) × 2
- Year Implemented (C) × 1
- No. of Requests (D) × 3
- Payment Required (E) × 1
- Online Payment (F) × 2
- Action Taken (G) × 1
- Screenshot Provided (H) × 1
You can adjust weights in the formula to suit your priorities.
Normalize “Number of Requests” (column D) if values vary greatly among services. For example, apply min-max scaling in a helper column before using it in score calculation.
Expand the sheet by adding additional columns if you want to track more indicators or dimensions.
Create summary tables or charts to visualize total digital readiness or compare services.

Optional: Summary and Overall Score

You can add a summary section calculating:

Total weighted score for all services (sum of weighted scores)
Average score per service
Dimension-wise scores (if you classify services into groups)

To help you get started quickly, you may download and customize free Excel dashboard or KPI templates from sources such as:

MyExcelOnline free templates1
Smartsheet free dashboard templates3 4
Template.net Excel dashboards6

You can incorporate the above table as raw data and build dynamic dashboards with charts and slicers for interactive insights.

If you want, I can provide this template as an Excel file or show sample formulas for min-max normalization and dashboard setup—just let me know!

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The Overall Digital Readiness Score (DR Score) is typically calculated as a weighted composite score representing multiple dimensions and indicators of digital capabilities and infrastructure. This approach is exemplified by the DigiReady+ Framework developed for Higher Education Institutions (HEIs), which is a data-driven model using institutional data rather than subjective questionnaires13.

Key elements of the Overall Digital Readiness Score based on DigiReady+ Framework and similar models:

Step / Component	Description
Dimensions	Digital readiness is broken into several broad dimensions (e.g., technology infrastructure, human capital, process management). DigiReady+ uses 7 dimensions13.
Indicators per dimension	Each dimension includes multiple measurable indicators (e.g., number of digital services, online payment availability, cybersecurity readiness). Indicators are data points collected from institutional information systems1.
Calculation per indicator	Indicators are scored numerically, normalized, or scaled appropriately. Example: availability (1 or 0), volume of transactions normalized, or Likert scales if survey-based14.
Topic and Dimension scoring	Indicators in each topic are aggregated with weights to form a topic score; multiple topics form a dimension score via weighted sum13.
Overall Composite Score	Dimension scores are combined using weights (reflecting importance) to produce the overall digital readiness score of the institution13.
Visualization / Dashboard	These scores are often visualized for actionable insights with dashboards showing trends, dimension-wise strengths/weaknesses15.

Example simplified formula (per DigiReady+ concept):

\text{DR Score} = \sum_{d=1}^D w_d \times \left(\sum_{t=1}^{T_d} w_{t} \times \left(\sum_{i=1}^{I_t} w_i \times \text{IndicatorValue}_i\right)\right)

Where:

$D$ = number of dimensions (e.g., 7)
$T_d$ = number of topics in dimension $d$
$I_t$ = number of indicators in topic $t$
$w_d, w_t, w_i$ = weights at each aggregation level to reflect relative importance
$\text{IndicatorValue}_i$ = normalized value of the $i^{th}$ indicator

How to apply this to your student e-governance services matrix:

You could assign:

Dimensions as thematic groups, e.g.,
- Digital Service Availability (whether core services exist)
- Service Usage (number of requests/transactions)
- Payment and Financial Transactions (payment required, online payment)
- User Interaction & Support (actions taken, grievance redressal)
Indicators as specific data points you already have, e.g.,
- Service Availability (YES=1, NO=0)
- Year of Implementation (scale or recency weighted)
- Number of requests (normalized)
- Payment Required (binary, with student-friendliness preference)
- Online Payment (binary)
Normalize or scale each indicator for comparability, then multiply by assigned weights reflecting strategic priorities.

Additional points:

Weights can be customized based on institutional priorities—e.g., online fee payment ease may have higher weight.
Data normalization (min-max or z-score) helps combine different indicator units (binary, counts, years).
Using a dashboard visualization as recommended in 5 facilitates monitoring over time and comparing multiple services.
Other digital readiness models for countries or enterprises follow similar composite scoring principles, confirming the validity of this methodology27.

Summary

The Overall Digital Readiness Score is a weighted aggregate of multiple normalized indicators grouped under key dimensions reflecting an institution’s digital maturity and capacity. Applying a similar algorithm to your e-governance student services data enables you to score and track readiness quantitatively, aiding strategic decisions and improvements1 35.

If you want, I can help prepare a sample scoring template or demo implementation based on your specific data for computing an Overall Digital Readiness Score.

I can’t directly send files, but I’ll give you detailed steps and sample formulas to create the Excel template including min-max normalization and a basic dashboard setup.

Step 1: Create the Data Table

Open Excel and create this table starting from A1:

A (Service)	B (Availability)	C (Year Impl.)	D (No of Requests)	E (Payment Req)	F (Online Payment)	G (Action Taken)	H (Screenshot)
Alumni Forum	1	3	100	0	0	0	1
Digital Academic Calendar
Digitisation of Library
Online Admission System
...

Step 2: Min-Max Normalization Formula for Column I (Normalized Requests)

This formula rescales No of Requests into 0–1 range.

Assuming your data rows start from row 2 to row 20, put this in cell I2 and drag down:


text
=IF(D2="","", (D2 - MIN($D$2:$D$20)) / (MAX($D$2:$D$20) - MIN($D$2:$D$20)))

Explanation:

Calculates normalized number of requests relative to min and max in the range
Blank if no data in D2

Step 3: Weighted Score Formula for Column J

Use normalized requests in scoring, weights as:

Availability (B) × 2
Year Implemented (C) × 1
Normalized Requests (I) × 3
Payment Required (E) × 1 (preferably 0 for student friendly)
Online Payment (F) × 2
Action Taken (G) × 1
Screenshot Provided (H) × 1

In J2, enter:


text
=IF(B2="","", B2*2 + C2*1 + I2*3 + E2*1 + F2*2 + G2*1 + H2*1)

Drag down for all services.

e-Governance / Digital Ready Excel Template File UPI Metrics Matrix

Step 4: Basic Dashboard Setup - Summary Table

Some ideas on what to add somewhere in your worksheet (say starting at L1):

Metric	Formula
Total Digital Readiness Score	`=SUM(J2:J20)`
Average Service Score	`=AVERAGEIF(J2:J20,"<>")`
Count of Available Services	`=COUNTIF(B2:B20,1)`
Count of Services with Online Payment	`=COUNTIF(F2:F20,1)`

Bonus: Simple Bar Chart of Service Scores

Select A1:A20 and J1:J20
Insert → Charts → Bar Chart
Chart shows services vs weighted digital readiness scores

Summary

Enter your data in columns B-H
Normalize requests with formula in column I
Compute weighted score in column J
Create summary metrics for aggregate insights
Use charts for visualization

STATE INSTITUTIONAL RANKING FRAMEWORK - Tamlinadu

Wednesday, July 23, 2025