vat/gst analytics by deloitte - deloitte tax uat portal da - ucb... · 3 vat/gst analytics by...

VAT/GST Analytics by DeloitteUser Guide August 2017

2VAT/GST Analytics by Deloitte – User Guide

What is VAT/GST Analytics?

What is Qlik Sense?

• The Associative Model

How to access Qlik Sense?

Navigate through Qlik Sense

• A quick overview

• Making Selections on visualizations

• Example of a Selection via Filters

• Export Data to an Excel File

Use the VAT/GST Analytics Dashboard

• Capabilities through Menu Layers

• Data Quality Checks

• Dropdown Dimensions

• The Flagged, not Flagged and Error dimension and logic behind

Contents

Detailed Dashboard Explanation

• Overview (Summary – Tax Codes – Data Health Checks)

• Account Payable (Highlights – Analysis – Deep Dive – Trends)

• Accounts Receivable (Highlights – Analysis – Deep Dive – Trends)

• Master Data (Highlights – Analysis – Deep Dive – Trends)

• Customized Reports

• Company (Company set-up – Data Quality Checks – Security)

Some external helps


What is VAT/GST Analytics?

Tax analytics has quickly emerged as a mindset change from "what I need to do" to "what I need to know,"

using more granular enterprise data as the foundation for tax decisions.

VAT/GST Analytics enables businesses to rigorously review the quality of their VAT/GST data and assess deficiencies in

their compliance processes through a provisioned system of predefined checks and balances. The solution automates and

streamlines large data files into one central, intuitive data dashboard based on the Qlik Sense technology.

Key benefits:


Qlik Sense is a powerful data visualization tool

What is Qlik Sense?

Qlik Sense is a self-service data visualization tool allowing users to easily and quickly explore as well as discover information,

perform guided analytics, and take data-driven decisions.

The main capabilities of Qlik Sense are:

Smart and user-friendly visualizations revealing hidden insights

Smart and user-friendly visualizations between all data dimensions of the business, revealing insights traditionally hidden when using the

standard query-based reporting tools

Provide ultimate flexibility through Smart Search

Smart Search can help uncover data relationships and information in scope of a dashboard App and quickly lead you to the insights you are

looking for

Explore multiple data sources in a single application

Qlik Sense connects multiple data sources without compromising performance providing more comprehensive and collaborative views

through the entire business

Access analytics anywhere, anytime, on any device

Qlik Sense moves seamlessly from desktop to tablet to smartphone in real-time


The associative model (1/2)


The Associative Model exposes relationships in complex, multi-source data sets

that are otherwise hidden in hierarchical or query-based approaches. You can

then benefit from this feedback every time you make a selection or search,

allowing you to gain understanding and take next steps.

With Qlik Sense, users of any skill level are empowered to follow their own paths

to insight. Through the Associative Model, you can ask question after question,

from any object, in any direction, using simple selections and searches.

Qlik Sense provides instant feedback on associated and unrelated data and

updated analytics after every step.


The associative model (2/2)


The selected values turn to green. In this example “High” and “Non-IT/Systems” are two selected values.

Immediately, the filter panes “Priority” and “Case Owner Group” are updated and display the different

selections.

Alternative values are then displayed in light grey. The alternative values are values excluded due to the first

selection.

Once the first selection has been done, the Associative Model displays the other possible values related to

that first selection in the other filters and turn them in white. Therefore, the excluded values are values not

associated with the first selection and are displayed in dark grey.


Two Easy Steps to Log In

How to Access the VAT/GST Analytics dashboard?

1. Open your browser.

2. Type the specific URL : https://indt-smart-dashboard-test.deloitte.com/saml/extensions/UCB_Analytics_V2/UCB_Analytics_V2.html

1. Select your identification method which is “Log in with

username and password”.

1

2 2. A pop-up menu will be displayed

asking you to enter your E-mail

address and Password.

https://indt-smart-dashboard-test.deloitte.com/saml/extensions/UCB_Analytics_V2/UCB_Analytics_V2.html


A quick overview


1 2

3

4

1. In the Selection bar the following actions are

available:

• Step back or forward in selections;

• Clear all selections**;

• Smart Search to search in the entire data

set and visualizations.

2. You can easily navigate through the App thanks to

the navigation menu.

3. This button opens a filter panel with a range of

filters applicable to the App.

4. The main area where you can find visualizations.


Making selections on visualizations


A sheet view contains visualizations;

You can apply filter selections by clicking directly

on the visualizations;

The visualizations on a sheet will automatically

be adapted based on your selections;

The selection will be applied immediately to the

entire app.

1

2

4

3

Example of a selection on a visualization:

1. Select the visualization on which the selection*

should be done;

2. Select the value in the graph to filter on a specific

value;

3. Confirm your selection with the green button;

4. In the selection bar you can see your current

selections. New selections in a visualization are

added to the previous ones. Selections can be

removed one by one (i.e. deselect an item by

clicking it).


Example of a selection via filters (1/2)


When you click on the filter button on the left side a

pane appears. From this menu you have a

selection of filters.

When you click on one of the Filters (e.g. “Legal

Entity” or “ Reporting Country”), a drop down list

will appear allowing you to make one by one

selections. You can also click on

This will open up a pop-up Menu that allows you to:

Select all

Select possible

Select alternative

Select excluded(*)

(*)These different types of selections are explained under the

“Associative Model”


Example of a selection via filters (2/2)


You can save and name your selections by clicking

on “Save as Favorite”. This can be used when you

often apply the same selections.

All your bookmarks are available into the favorites

tab of the filter pane.

When you click on a “Favorite”, the saved selection

will be applied immediately to the entire app.


Export your data to Excel:

1. Two icons appears when you hover a

visualization:

• Click on to export only the data

related to this visualization.

• Click on to expand this visualization.

Export data to Excel


1


Capabilities through menu layers

Use the VAT/GST Analytics dashboard

1 2 43 5 6 7

1. The Overview contains a Summary view allowing the user to have a high level

view on both the total as well as the impacted AR and AP position throughout

the world per location, reporting country, legal entity and VAT number. Further,

the user can consult the list of transactional tax codes and via the Data Health

Check views the user is being provided insight in the level of completeness of

the data provided and possible impact this might have on the outcome of the

analysis performed.

2. The Account Payable section allows the user to get high level insight in the

supply chain, and provides an understanding on the VAT/GST issues following

the performed test, identifies root causes and issue trends over time.

3. The Account Receivable section allows the user to get high level insight in de

sales chain, and provides an understanding on the VAT/GST issues following

the performed tests, identifies root causes and issue trends over time.

4. The Master Data section provides insight in supplier, customer or material

master data related issues and trends over time.

5. The Customized Report is a powerful tool providing access to all underlying

data allowing for the user to create and export specific reports.

6. The Company Section displays the company structure, a list of the performed

data quality checks and an overview on users having access to the dashboard.

7. Online copy of the user guide.


Data quality checks (DQCs)


100+ data quality checks

The results on the data health checks can be found

under Overview – Data Health Checks; the results

on the AP, AR and Master Data checks can be

found under the respective Analysis screens; the

results on the reconciliation checks can be found on

the Reconciliation screen – e.g. for the Master

Data:

1. KPI’s show the number of “flagged”

master data out of the total master data.

2. Pie charts allow the user to see exactly

the repartition of flagged master data into

different categories.

3. The table is a detailed analysis ordered to

immediately select the DQC results with

the highest impact.

From this view on the user can decide which issue

to focus on first, select the result to be looked into

and move to the Deep Dive page to identify route

causes.

Issue trends for AP, AR and Master Data can be

found in the respective Trends pages.

32

1


Dropdown dimensions


The user will be able to select several dimensions

directly on the screen.

Once the user selects a dropdown dimension, this

will impact either all or some visualizations, on the

screen – e.g.:

1. For the Transactional Data the user can

switch between Net Amount, Tax Amount

and Number of Transactions. This

Dropdown dimension only impacts the

visualizations and not the KPI’s on the

top.

2. The dropdown dimension only impacts the

bar chart. By clicking on the dimension

Incoterm, the visualization and the title will

be immediately changed.

1 3

3


The Flagged, not Flagged and Error dimension and logic behind


The ‘Flagged – Not Flagged – Error’ dimension allows

the user to switch between three different values on

most of the dashboard screens:

“Flagged” represents the transactions that

didn’t pass at least one data quality check.

“Error” represents the transactions for which

at least one data quality check could not be

performed due to missing data.

“Not Flagged” represents the transactions

that passed all the data quality checks.

The ‘Flagged – Not Flagged – Error’ dimension impacts

all visualizations on the screen – e.g.:

As you can see on this screenshot, the KPI’s

show two numbers next to each other. In this

case, it means the amount in error out of the

total amount. Only the first number of each

KPI is impacted by the dimension.

Note that all visualization titles are flexible, meaning

titles change automatically depending the selected

dimensions – e.g.:

The pie chart displays the “Net Amount (€)

Error per DQC Category”.

When selecting the dimension “Flagged” the

title will change into “Net Amount Flagged (€)

per DQC Category”.


Overview - The Summary screen


Purpose of the Summary screen:

Dimension - All: High level overview on the

total AR and AP position on net amount, tax

amount or number of transactions to be

viewed per location, reporting country, legal

entity and VAT number visualized in various

interconnected graphs displaying info next to

each other in one view.

Dimension - Flagged: Overview on the AR

and AP transactions failing one or more data

quality checks, allowing for the user to

immediately dive into these legal entities,

locations, countries or VAT-numbers that

require attention by making selections on

screen and moving on to the more in-depth

analysis in the next screens.


Overview – Tax Codes screen


Purpose of the Tax Codes screen:

Overview on the number of client tax codes as

put in place by the business (i.e. master list of

tax codes), the number of tax codes used in the

transactional data set, split out for AP/AR and

compared to the number of Deloitte tax codes

where the client ones have been mapped to.

View on how the number of tax codes evolve

over time.

Graphs and KPIs are interconnected, mean

The user can consult the list of all the client and

Deloitte tax codes including their description

which can be exported to excel.

The graphs, KPIs and the list are

interconnected, meaning a selection within the

graphs will change both the KPIs and the list.


Overview - The Data Health Check screens


Purpose of the Data Health Check screens :

Provides insight on the impact of missing or non-compliant

transactional and master data.

Graphs and KPIs are interconnected meaning making a

selection in one graph triggers the KPIs and other graphs

to only show the information related to that selection.

The missing data fields have been categorized by severity

level - listed from high to low:

Severity level 1: missing / non-format compliant data

which are needed for the VAT/GST analytics solution to

run properly (i.e. mandatory fields - system).


which are needed for the data quality checks to run and/or

for the analytics dashboard to generate useful insights (i.e.

mandatory fields - test or mandatory fields - dashboard).


which do not have an impact on either the VAT/GST

analytics solution, the VAT/GST tests or the dashboard.


Account Payable (AP) - Highlights screen


Purpose of the AP Highlights screen:

High level overview on the AP position per net

amount, tax amount or number of transactions

by various dimensions – e.g. per supplier to

identify the top 10 suppliers; per legal entity to

identify the biggest purchasing entity in the

group simultaneously providing trends over time.

The graphs and KPIs are interconnected

meaning making a selection in the left chart will

impact the trends chart and the KPIs on top

which will only display the info related to that

selection.


Account Payable (AP) - Analysis screen


Purpose of the AP Analysis screen:

Pie-chart: summary of issues following the analysis

performed on the selected AP data set, grouped per

category.

Table: displays all data quality check results ranked

by their impact by quantifying the possible impacted

net amount, tax amount and number of transactions,

allowing the user to take an informed decision on

what type of issues to look into to identify root

causes.

The pie-chart and the table are interconnected

meaning selecting a category to the left means only

the DQCs allocated to that category are being

displayed in the table; the same is true for the KPIs

on top.

Once the user selected a given DQC result, the root

cause identification (cfr. Deep Dive) screen can be

accessed via the green button displayed on the

screen:


Account Payable (AP) - Deep Dive screen


Purpose of the AP Deep Dive screen:

Provides insight into where the issues following

a specific test performed stem from (e.g.

overview on the legal entities facing the issue )

The user can change the bar chart dimensions.

Each dropdown is allocated to the bar chart

below it.

The table at the bottom of the screen allows the

user to consult the underlying AP transactions

on screen or extract these into excel.


Account Payable (AP) - Trends screen


Purpose of the AP Trends screen:

High level overview on the impacted AP position

per net amount, tax amount or number of

transactions by various dimensions – e.g. per

legal entity ranking all legal entities from being

most to least impacted by any issues showing

from the performed data quality checks.

Overview on how the impacted net amount, tax

amount or number of transactions evolves from

month-to-month or year-to-year.

Graphs and KPIs are interconnected meaning

e.g. selecting a given entity on the left will

project the trends for that specific entity on the

right.


Account Receivable (AR) - Highlights screen


Purpose of the AR Highlights screen:

High level overview on the AR position per net

amount, tax amount or number of transactions

by various dimensions – e.g. per customer to

identify the top 10 customers simultaneously

providing trends over time.

The graphs and KPIs are interconnected

meaning making a selection in the left chart will

impact the trends chart and the KPIs on top

which will only display the info related to that

selection.


Account Receivable (AR) - Analysis screen


Purpose of the AR Analysis screen:

Pie-chart: summary of issues following the analysis

performed on the selected AP data set, grouped per

category.

Table: displays all data quality check results ranked

by their impact by quantifying the possible impacted

net amount, tax amount and number of transactions,

allowing the user to take an informed decision on

what type of issues to look into to identify root

causes.

The pie-chart and the table are interconnected

meaning selecting a category to the left means only

the DQCs allocated to that category are being

displayed in the table; the same is true for the KPIs

on top.

Once the user selected a given DQC result, the root

cause identification (cfr. Deep Dive) screen can be

accessed via the green button displayed on the

screen:


Account Receivable (AR) - Deep Dive screen


Purpose of the AR Deep Dive screen:

Provides insight into where the issues following

a specific test performed stem from (e.g.

overview on the legal entities facing the issue )

The user can change the bar chart dimensions.

Each dropdown is allocated to the bar chart

below it.

The table at the bottom of the screen allows the

user to consult the underlying AR transactions

on screen or extract these into excel.


Account Receivable (AR) - Trends screen


Purpose of the AR Trends screen:

High level overview on the impacted AR position

per net amount, tax amount or number of

transactions by various dimensions – e.g. per

legal entity ranking all legal entities from being

most to least impacted by any issues showing

from the performed data quality checks.

Overview on how the impacted net amount, tax

amount or number of transactions evolves from

month-to-month or year-to-year.

Graphs and KPIs are interconnected meaning

e.g. selecting a given entity on the left will

project the trends for that specific entity on the

right.


Master Data – Highlights / Analysis / Deep Dive / Trends


Purpose of the Master Data Section:

Many VAT/GST determination errors and compliance data gaps have their root cause in

missing, incomplete or incorrect master data:

Highlights screen:

Overview on the number of customer, supplier and material master data and how

these numbers evolve over time

Analysis screen:

Pie-chart: summary of issues following the analysis performed on the master data

set, grouped per category.

Table: displays all data quality checks ranked by impact.

The pie-chart and the table are interconnected meaning selecting a category to the

left means only the DQCs allocated to that category are being displayed in the table;

the same is true for the KPIs on top.

Once the user selected a given DQC, the root cause identification (cfr. ‘Deep Dive’)

screen can be accessed via the green button displayed on screen.

Deep Dive screen:

Provides insight into where the issues following a specific test performed, stem from;

each bar chart dimension can be changed. The table at the bottom of the screen

allows the user to consult the underlying master data.

Trends screen:

High level overview of number of impacted master data by various dimensions and

how this number evolves over time.

Graphs and KPIs are interconnected meaning e.g. selecting a given entity on the left

will project the trends for that specific entity on the right.


Customized Reports screen


Purpose of the Customized Reports screen:

Consult the submitted data sets providing full

access to all underlying master and

transactional data.

The selected set of data can be consulted on

screen or downloaded into excel.

In order to begin the table construction the user

has to select a report in the top left drop down.

The user can easily add and remove data fields

by clicking on the fields in the list.

The order of the selected fields can be changed

by dragging and dropping the fields to the

preferred location via the top selection bar.


Company – Company Setup screen


Purpose of the Company Setup screen:

Detailed overview on the number of legal

entities established per country as well as the

number of VAT/GST registrations per legal entity

and per reporting country.

View on how the number of legal entities,

reporting countries and VAT numbers evolves

over time.

List of all VAT numbers per legal entity which

can be exported to excel.

The graphs, KPIs and the list are

interconnected.


Company Section – Data Quality Checks screen


Purpose of the Data Quality Checks page:

• List of data quality checks (DQCs), including the

numbering, name and a description and test

outcome for each DQC which are run by the

Deloitte VAT/GST Analytics summing the total

number of tests per category.


Company Section – Security screen


Purpose of the Security screen:

List of users having access to the dashboard.

Line charts showing how many users have

accessed the dashboard by month and by day.


Some external helps

Learn more about Qlik Sense

Global smart searchVisual exploration Working with selection

https://community.qlik.com/docs/DOC-6995

https://www.youtube.com/watch?v=EaMxCPhcIyA

https://community.qlik.com/docs/DOC-7023

vat/gst analytics by deloitte - deloitte tax uat portal da - ucb... · 3 vat/gst analytics by...

Documents