VISTO: An operational tool to visualise the duration of public investment projects

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Carlo Amati
VISTO: An operational tool
to visualise the duration of
public investment projects

Outline
 An introduction on public investments
 VISTO: An operational tools for the interactive
visualisation of project length estimates
 VISTO behind the scenes: analytical insights
 Examples

Public investments – What are we talking about?
Roads
and
motorways
Industrial
areas
Water
treatment
plants
Airport
terminals
Restoration
of historical
buildings
Railway
systems
Archaeological
sites
Acqueducts
University
facilities
and
more

Public investments verification unit (UVER)
Project
Verification
Audit Authority
On-site inspections
Assistance & support
Investment analysis
Monitoring and
Statistics
Forecasting models
Monitoring systems
Effectiveness
Appraisal
Assessment of results
UVER’s
three areas
act as a
bridge
between
data and
policy

Public investments – Analysis framework
Data
Collection
System
Data
Collection
System
Data
Analysis
System
Data
Analysis
System
Data
Interpretation
System
Data
Interpretation
System
Relevant dimensions
Implementing
parties
Implementing
parties
Socio-economic
context
Socio-economic
context
Nature of
project
Nature of
project
Financial
resources
ICT SYSTEMSICT SYSTEMS
Reality /
Policy
achievements
Policy, rules
and decision
making

The main stages of a project’s implementation
Preliminary
Design
Detailed
Design
Executive
Design
Tender Works
The main purpose
of the Preliminary
Design is to
define the
dimensions of the
structure, in order
to obtain a clear
picture of the
structural action
and make
estimates of the
project’s cost.
The main purpose
of the Detailed
Design is to
define all the
elements required
to obtain the
necessary
permissions.
The main purpose
of the Executive
Design is to
define all the
details of the
project in terms of
costs and type of
works.
The Tender stage
refers to the
period between
the advertisement
of the tender on
public gazettes
and the selection
of the firm that will
be contracted for
the completion of
the works.
The Works stage
refers to the
period between
the handover of
the site to the
contractor and the
completion of the
works.

VISTO at a glance
A tool for:
selection
benchmarking
early-warning
performance
assessment
VISTO is:
simple in its interface but based on predictive models built on complex data
transparent to stakeholders and citizens
universal for a “clinical diagnosis” of investment projects

VISTO: Application features
 VISTO yields an estimate of the time length of each
implementation stage of an investment project depending
on its main attributes (cost, location, sector, type of project,
category of implementing body, tender procedure).
 VISTO yields the above estimates for each combination of
attributes, regardless of whether such a project really
exists or not.
 Predictive models used for VISTO produce an estimate of
the complete theoretical distribution of the time length of
each stage: the median is chosen as central value and a
variation interval is associated to it.
 The length of each stage lasts until the start of the
following one, except for the “Works” stage, ending at
works completion.

VISTO: Panel description – Project features
The left-hand panel contains the project features
that users can select interactively: the estimated
length of each stage depends on the specific
selected combination.
The available features are: amount, sector, type of
project, category of implementing body, tender
procedure, location at the provincial level.
The amount is the only quantitative feature and its
value is typed in, all other features are selected
with their combo box. Provinces are organised
hierarchically and are selected within their region.

VISTO: Panel description – Length of stages
A button that produces a pdf output of the
estimated lengths is available in the top right
corner.
The upper part of
the right-hand
panel contains 5
dials where the
estimated lengths
of each of the 5
stages of a project
with the selected
features are
represented
together with some
measures of the
associated
variability.

VISTO: Panel description – Dial elements
The black needle
shows the
estimated median
value for the length
of each stage,
which is named
“central length”.
The yellow band
highlights a range
of lengths, centred
across the median
value. The default
width is set at 50%
(25th-75th
percentiles). The
extremes are
named “short” and
“long” lengths.
The green sector
marks the 35th
percentile of the
nationwide
distribution (i.e.
location is ignored)
and can be used
as a benchmark.

VISTO: Panel description – Overall project length
Below the summary chart, a green bar highlights
the interval corresponding to the best 35% of
projects with given features at national level, which
may be considered as a benchmark.
The lower part of
the right-hand
panel contains a
chart with the
summary of the
short, central and
long lengths of the
overall project,
which are
calculated as the
sum of the lengths
of the 5 stages.

VISTO: Potential users
A public officer can use VISTO as an additional tool
for project selection during strategic planning of
investments, or as an early-warning system in
order to monitor the behaviour of on-going projects,
or as an appraisal measure to evaluate the
performance of a completed investment project.
A project manager can use VISTO to identify a
reasonable target for his/her project, finding
stimulus to push his administration towards the
best practices at the national level.
A citizen can use VISTO to be aware on when a
new public investment is most likely to be
completed and available in his/her
neighbourhood.

VISTO: Architecture
HTML version
(compliance
with web
accessibility
regulation)
Results
Error page
Pdf output
Web server
Microsoft IIS
broker.exe (SAS)
SAS IntrNet
SAS Code
broker.exe
Application server
IBM AIX
SAS 9.2 (+IntrNet)
CGI
SWF version
Model
parameters

VISTO: How it works – Homepage

VISTO: How it works – SWF version

VISTO: How it works – HTML version: Start page

VISTO: How it works – HTML version: Results
...

VISTO: How it works – HTML version: Error page

VISTO: How it works – HTML version: Pdf output

Analytical insights
1. Qualitative information: classification through
text-based clustering
2. From micro to macro: the importance of
survival models
3. Does location matter? Analysis of regional
effects and provincial dimensions

1. Text-based clustering – Categorical variables
Projects are not
always classified
correctly in monitoring
databases, but the
proper classification
may be recovered
from other fields.

1. Text-based clustering – Sectoral categorisation
………
……………
…………………..
……….
……….
………………….
……
……………….
... and apply it to a
large number of cases.
“Restoration
works of Trevi
fountain”
“Restoration
works of Trevi
fountain”
The aim is to reproduce the categorisation process
performed by the human mind ...
Works
ROADS
HOUSING
WATER SYSTEMS
CULTURAL HERITAGE
HOUSING
CULTURAL HERITAGE
…Restoration
TOURISM
CULTURAL HERITAGEFountain
Trevi
ROADS
HOUSING
CULTURAL HERITAGE
…

1. Text-based clustering – The procedure (EM 5.2)
In Phase 1 data pre-processing
is applied to a reference
dataset where classification
variables are known. It
comprises the selection of
project descriptions that can be
used for the classification
process (non-missing
sector/type).
Original description is enriched
with sector description.
Data are partitioned in a
training and a test set (90-10).
Phase 1
Data pre-processing
PROJECT
DESCRIPTIONS
BY CATEGORY
DATA
PARTITION
In Phase 2 the “textual” project
descriptions of the reference
dataset are transformed into a
“numerical” space with the Text
Miner Node. The Memory-
Based Reasoning Node
identifies similar cases by the
k-NN algorithm and builds the
classification model that can be
applied to new cases.
Phase 2
Information processing
TEXT MINER MBR
In Phase 3 the Scoring Node
allows the application of the
classification model to new
cases, i.e. project descriptions
in the dataset that will be used
for VISTO models.
Classification is based on the
proportion of “neighbours” of a
new project description in each
category (probability of
classification).
Phase 3
Scoring
NEW PROJECT
DESCRIPTIONS
SCORE

2. Survival models
Advantages
 The analytic estimates are based on a model
that takes into account completed stages as well
as on-going ones (censored cases)  Maximise
the use of available information on stage lengths
 Offer a complete estimate of the survival
function, i.e. the probability that the length of a
certain stage is exactly t, given the values of the
descriptive variables

2. Survival models – Formulation
Let Ti be a random variable representing the (possibly
unobserved) survival time of the i-th unit. Since Ti must be
non-negative, its logarithm can be modelled using a
conventional linear model:
where εi is a suitable error term, with a distribution to be
specifed. This model specifes the distribution of log-survival
for the i-th unit as a simple shift of a standard or baseline
distribution represented by the error term.
In SAS this can be easily coded as follows:
iinnii xxT εβββ ++++= ...log 110
proc lifereg data=ds;
class x2 x3;
model y*cens(1)= x1 x2 x3;
output out=res p=median;
run;

2. Survival models – The role of censored data
The length of censored
stages is the output
estimate of the model.

2. Survival models – The role of censored data
The width of the bars
of the series “Only
completed stages” is
proportional to the
ratio of “# completed”
over “# completed and
censored”.
The mean length of “Works” for the most costly projects increases by 20% when
censored cases are included in the analysis. Their class (“More than 50 M€”)
accounts for approx. 50% of the total financial value of all projects.

3. Does location matter?
Two approaches:
 Territorial representation with highest available
detail, economic interpretation of effects:
• Descriptive variables at the provincial level
+ dummy variables at the regional level
 Measure of overall territorial efficiency
• Dummy variables at the regional level
......log +++= ∑∑ r rrk kk xxT ββ
......log '
++= ∑r rr xT β
:rx Regional dummies
:kx Provincial variables

3. Location matters: the effect of provincial vars
Variable (at the provincial level)
Economic Development Index 0.93 ** 0.95 * 1.09 ***
Environmental Condition Index 0.93 ** 1.05 ** 0.97 ***
Organized crime 0.86 *** 0.94 ** 1.05 ***
Crime aganist people 1.04 ***
exp(β ) exp(β )exp(β ) exp(β ) exp(β )
Tender Works
Preliminary
design
Detailed
design
Executive
design
Better economic and environmental conditions are associated with
faster completion of the first two stages, which mainly deal with
administrative permissions, while are associated with longer time spent
in defining the fundamental details of the projects: longer durations
may indicate greater accuracy and efficiency.
There is also a positive correlation between “Crime against people” and
the length of the “Works” stage.

3. Location matters: overall regional efficiency
0
1
2
3
4
5
6
EMILIA-ROMAGNA
PIEMONTE EVALLED'AOSTA
FRIULI-VENEZIA GIULIA
LOMBARDIA
MOLISE
VENETO
TRENTINO-ALTO ADIGE
ABRUZZO
MARCHE
PUGLIASARDEGNA
CALABRIA
LAZIO
LIGURIA
TOSCANA
CAMPANIA
UMBRIA
SICILIA
BASILICATA
Regional mean for regional set Regional mean for national set National mean

3. Regional
efficiency
in other
words
Very efficient (over 15% less than average)
Moderately efficient (3-15% less than average)
On average (±3%)
Poorly efficient (3-15% more than average)
Not efficient (over 15% more than average)

References
For further details on the above analytical insights:
1. C. Amati, F. De Angelis, F. Romani
“Textual data classification for a sectoral categorisation of
public investments” in Proceedings of Textual Data
Statistical Analysis – JADT 2010, Rome, Italy.
2. C. Amati, F. Barbaro, C. Carlucci, F. De Angelis, A.
Guerrizio
“Survival analysis: an application to italian data on public
investments” in Proceedings of Stochastic Modeling
Techniques and Data Analysis International Conference –
SMTDA 2010, Chania Crete, Greece.
3. C. Carlucci, A. Guerrizio, C. Amati, F. De Angelis, F.
Barbaro “I tempi di attuazione delle opere pubbliche” in
Proceedings of 30th
Annual Scientific AISRe Conference –
AISRe 2010, Aosta, Italy.

VISTO: Where it is, and... why “VISTO”?
Soon available at:
http://www.dps.tesoro.it/VISTO
Working demo:
http://uver.altervista.org/VISTO_en.swf
Feedback:
dps.visto@tesoro.it
VISTO, beside being an
acronym, is also the
Italian for “visa”: the idea
is that a project whose
stage lengths lie within
the ranges indicated by
VISTO can be
acknowledged to specific
benefits.

Example 1: A completed project (MAXXI)
MAXXI
National Museum of
the XXI Century Arts

Example 1: MAXXI timesheet
 International design contest in 1998
 Start of works in March 2003
 End of works: 2009
 Cost: 150 million euros
 Overall length: 11 years
MAXXI:
- falls beyond benchmark interval
- corresponds to the 40th
percentile

Example 2: A new project (football stadium)

Example 2 (cont.): Hypothesis for an historical
comparison
Started by Vespasian in 72 a.C.
Completed by Titus in 80 a.C.
With an overall implementation length of
8 years, Colosseum:
- would fall within benchmark interval
- would correspond to the 28th
percentile

Thank you
web: www.dps.tesoro.it/UVER
mail: carlo.amati@tesoro.it
Public investments verification unit
Department for development and economic cohesion
Ministry of Economic Development
Via Liguria 26
00187 Rome, Italy

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