Introduction

The following article discusses how to take a good functional dashboard to the next level. It mentions the relevant Sisense features available to help achieve your next goal.

Introduction
Table of Contents
Dashboard Complexity

Dashboard Complexity

In previous articles, I've discussed how you should plan your dashboard (Link), and later, how to assess and monitor its performance (Link). But once one is ready and being used - Can you still somehow enhance it?

The "Dashboard Complexity" term refers to the added value a dashboard provides aside from answering the business question. The name suggests that the dashboard should be more complex. However, the "Complexity" term refers to the amount of data and transformation required to create it.

A "More Complex" dashboard:

Provides more valuable insights
Required more data for processing/training
Requires more dashboard design and data modeling work

To emphasize this, think about a BI Dashboard designed to answer the business question of "Financially, How is the company doing." The following three insights answer the business question, however, provide different benefits:

Insight #1: Company sales dropped by 15% in the last quarter
Insight #2: Company sales usually drop by 25% during wintertime. However, they only dropped by 15% this year
Insight #3: Company sales are currently dropping, you should increase your investment in export by 20K$

While the first insight seems negative, insight #2 provides a perspective and lets you understand the real numbers are positive. The last insight provides actionable instructions on what to do next.

The article will take you through a journey of five different approaches to "Dashboard Complexity." Each provides you with a different focus, challenges, and insights:

Descriptive BI
Diagnostic BI
Predictive BI
Prescriptive BI
Assisted Intelligence BI

The "Descriptive BI" Approach

The "Descriptive BI" approach (a.k.a. "Reporting") focuses on the question of "What Happened."

This type of dashboard can be generated by:

Displaying simple figures (such as an annual revenue)
Displaying simple facts (such as a month-over-month revenue drop)
Displaying anomalies (such as a sudden revenue drop in the last quarter)
Displaying simple trends (such as a gradual growth in monthly revenue)

Let's assess the "Descriptive BI" dashboard:

Data Complexity: The information required for generating these statements is very easy to generate
Data Transformation: Data requires simple aggregations (sum/average/etc.)
User Benefit: The information answers the business question. However, It can't help a user explain the figures shown or help them decide what should happen next.

Available Tools for Implementation

Sisense offers the following tools to generate "Descriptive BI" dashboards:

Feature	Description
Simple Out-Of-The-Box visualizations	Visualize data graphically (a.k.a. widgets)	Link
Dashboard and Widget Filters	Enable focusing on the data of interest	Link
Conditional Formatting	Add visual aids to help convey a message about the data	Link
AI Exploration Paths	Automatically generate visualizations and insights that anticipate your Viewers' questions.	Link
Narratives	Use natural language generation (NLG) to make your data more accessible and easy to understand	Link
Trend Lines	Highlight tendencies in your data and get insights quickly	Link
Break By	Segment data into groups of interest
The "Switchable Dimensions" add-on	Easily toggle between dimensions displayed in a single widget	Link
The "Blox" add-on	Create custom data visualizations by the use of code	Link

The "Diagnostic BI" Approach

The "Diagnostic BI" approach (a.k.a. "Analysis") focuses on the question of "Why did it happen."

This type of dashboard can be generated by:

Displaying a root cause (the "A" event took place due to the "B" event)
Displaying a correlation between variables (the variable "A" has a positive correlation to "B")
Displaying an insight ("A" is better than "B")

Let's assess the "Diagnostic BI" dashboard:

Data Complexity: The information required for generating these statements is harder to generate
Data Transformation: In addition to earlier requirements - Requires teaching Sisense business rules of how to draw a conclusion
User Benefit: The information answers the business question. However, it provides minimal benefit as it only shows simple correlations (not the "full picture"). A user cannot make educated decisions based on this minimal data.

Available Tools for Implementation

Sisense offers the following tools to generate "Diagnostic BI" dashboards:

Feature	Description
Drilling	Get an in-depth view of a selected value	Link
Hierarchies	Create logical hierarchy paths for an in-depth view of a selected value	Link
Break By	Segment data into groups of interest
Explanations	Find the root causes that contributed to a data anomaly	Link
Narratives	Use natural language generation (NLG) to make your data more accessible and easy to understand	Link
The "Blox" add-on	Create custom data visualizations by the use of code	Link

The "Predictive BI" Approach

The "Predictive BI" approach focuses on the question of "What will happen next."

This type of dashboard can be generated by:

Displaying an interactive What-If analysis
Displaying a forecast based on historical data
Displaying an optimization recommendation

Let's assess the "Predictive BI" dashboard:

Data Complexity: The information required for generating these statements is harder to generate (more history, more variables, etc.)
Data Transformation: In addition to earlier requirements - Requires AI/ML modules to predict forecasts and interactive dashboard widgets to allow a what-if analysis
User Benefit: The information answers the business question. In addition, it allows simulating various scenarios to help the end-user make educated decisions on what has to happen next.

Available Tools for Implementation

Sisense offers the following tools to generate "Predictive BI" dashboards:

Feature	Description
Forecast	Forecast future values based on historical data	Link
The "Advanced Parameters" add-on	Add user input boxes to enable "What-If" analysis	Link
Custom Code	Run Python code from your Jupyter Notebooks to transform and cleanse data	Link
The "Blox" add-on	Create custom data visualizations by the use of code	Link

The "Prescriptive BI" Approach

The "Prescriptive BI" approach focuses on the question of "What should be done next."

This type of dashboard can be generated by:

Displaying an actionable operation

Let's assess the "Prescriptive BI" dashboard:

Data Complexity: The information required for generating the right action plan is hard to generate (more history, more variables, more business rules, etc.). The person designing this dashboard will have to conduct strict due diligence and be familiar with every factor and consideration of the decision-making. In addition, the dashboard will require serious UAT.
Data Transformation: In addition to earlier requirements - Requires teaching Sisense all possible business logic.
User Benefit: The information answers the business question and tells the user what to do next. However, with power comes responsibility. By providing a firm action plan, the dashboard would become accountable for the result of that action. A positive outcome will result in stickiness, and people will start to depend on it. A negative outcome may result in a lack of trust or complete neglect of the dashboard.

This type of system requires constant maintenance and testing to make sure its data is correct, and its decision-making rules are up to date.

Available Tools for Implementation

Sisense offers the following tools to generate "Prescriptive BI" dashboards:

Feature	Description
Custom Code	Run Python code from your Jupyter Notebooks to transform and cleanse data	Link
The "Blox" add-on	Create custom data visualizations by the use of code	Link
Pulse Alerts	Create alerts to notify you when certain thresholds are met, or anomalies in your data are detected	Link

The "Assisted Intelligence BI" Approach

The "Assisted Intelligence BI" approach focuses on automated processing.

This approach doesn't necessarily require a dashboard as it will trigger the actionable operation on its own. The system will collect the data, process it, generate insights, and act upon it.

Let's assess the "Prescriptive BI" dashboard:

Data Complexity: The information required for generating the right action plan is the same as in the "Prescriptive BI" approach.
Data Transformation: In addition to earlier requirements - Requires building interfaces to communicate with external systems (such as an email server, slack bot, or an application via a webhook).
User Benefit: This approach is fully automated and provides the best user benefit - The user has to do nothing! However, it is also very dangerous as a person learns to trust the system and might neglect to verify the data or update the business rules.

Available Tools for Implementation

Sisense offers the following tools to generate "Assisted Intelligence BI" dashboards by interacting with external applications:

Feature	Description
Pulse Webhooks	Send notifications through additional 3rd party channels	Link

Introduction

Table of Contents

Table of Contents

Dashboard Complexity

The "Descriptive BI" Approach

Available Tools for Implementation

The "Diagnostic BI" Approach

Available Tools for Implementation

The "Predictive BI" Approach

Available Tools for Implementation

The "Prescriptive BI" Approach

Available Tools for Implementation

The "Assisted Intelligence BI" Approach

Available Tools for Implementation