1. Introduction to Business Data Analytics

1.1 What is Business Data Analytics?

Guide to Business Data Analytics

IIBA.org KnowledgeHub Guide to Business Data Analytics 1. Introduction to Business Data Analytics 1.1 What is Business Data Analytics?

Business data analytics is a specific set of techniques, competencies, and practices applied to perform continuous exploration, investigation, and visualization of business data. The desired outcome of a business data analytics initiative is to obtain insights that can lead to improved decision-making. Business data analytics can be applied to investigate a proposed business decision, action, or a hypothesis or to discover new insights from business data that may result in improved decision-making.

The business data analytics cycle is the iterative research process that seeks to answer a well-formed research question. Data analysis then explores the results of this research.

Business data analytics can be defined more specifically through several perspectives. These perspectives include, but are not limited to, business data analytics as a:

movement,
capability,
data-centric activity set,
decision-making paradigm, and
set of practices and technologies.

1.1.1 Business Data Analytics as a Movement

Business data analytics as a movement involves a management philosophy or business culture of evidence-based problem identification and problem-solving. Evidence through data is the driver of business decisions and change. Rapid technological advances in the digitization of data and improved analytics methods are prompting businesses to adopt a data-driven management philosophy.

Example of Evidence-Based Problem Analysis in Insurance

For the insurance industry, generating better customer value has always meant getting a clearer picture of individual risk. By paying closer attention to the data people create daily, insurance companies can better anticipate needs, personalize offers, and tailor the customer experience. It is a shift from the practice of using demographics data to customize insurance products. Data such as telematics, social media, and lifestyle data can accurately reveal individual risk patterns through advanced analytics. The availability of such data has prompted insurers to change the way products are marketed and priced, and to better manage claims.

1.1.2 Business Data Analytics as a Capability

Business data analytics as a capability includes the competencies possessed by both the organization and its employees. Business data analytic competencies extend beyond those required to complete analytical activities, they include capabilities such as innovation, culture creation, and process design. This capability, or lack thereof, may define or constrict what the organization is capable of achieving through business data analytics.

Building Competencies for a Data-Driven Enterprise

Spotify is the largest on-demand streaming music provider in the world, with millions of users globally. As an experiment, Spotify wanted to send out a large number of emails that would tell customers if their friends have subscribed to the streaming service and the playlist they are listening to. The idea was to improve user engagement through by promoting it as a social experience. The initiative was a success. However, behind the scenes Spotify must have decided:

what the data infrastructure for their organization should look like,
how to source the relevant data about customers,
how to design a solution that should be capable of sending out relevant email content,
how to measure improved user engagement, and (above all)
how to create a business case to justify the entire initiative.

The ability to perform advanced analytics on the data customers generate is definitely a part of the shift in approach. However, to operationalize such an initiative, the organization needs to treat data as an extension of organizational culture which translates into creative ideation, process change, and the agility required to embrace the changes brought in by a data-driven enterprise.
https://labs.spotify.com/2013/05/13/analytics-at-spotify/

1.1.3 Business Data Analytics as a Data-Centric Activity Set

Business data analytics as a data-centric activity set includes the actions required for an organization to use evidence-based problem identification and problem-solving. Data analytics has been defined by expert practitioners as involving six core data-centric activities:

accessing,
examining,
aggregating,
analyzing,
interpreting, and
presenting results.

Business data analytics, in addition to the core data-centric activities, extends the activity set to analysis-oriented activities:

planning,
strategy analysis,
stakeholder collaboration and management,
solution designing,
recording and verifying analytics approaches, and
tracking and managing analytics recommendations.

These activities are executed in a more structured way to help organizations realize the business objectives behind analytics initiatives.

1.1.4 Business Data Analytics as a Decision-Making Paradigm

Business data analytics as a decision-making paradigm involves making business data analytics a mechanism for informed decision-making across the organization. Business data analytics is the tool of making decisions using evidence-based problem identification and problem-solving. Evidence from data is an enabler for informed business decision-making that is more persuasive than instinctive decision-making, which can be influenced by cognitive biases. Business data analysis strikes a balance between business experience and analytics results for effective business decisions through collaboration.

Examples of Collaborative Decision-Making

As deep analytics and artificial intelligence (AI) are becoming more prevalent in influencing decisions for enterprises, the underlying processes to arrive at a predictive or a prescriptive action are becoming more opaque. For example, the General Data Protection Regulation (GDPR) has provisions that give consumers the right to receive an explanation for any automated decision-making, such as the rate offered on a credit card or mortgage. The role of business data analytics becomes even more critical in this sense where evidence generated through data must be explained with the right business context to the decision-makers as well as end customers.

1.1.5 Business Data Analytics as a Set of Practices and Technologies

Business data analytics as a set of practices and technologies establishes the framework required to successfully execute analytics initiatives. These practices can be discussed in the context of six business data analytics domains:

Identify the Research Questions,
Source Data,
Analyze Data,
Interpret and Report Results,
Use Results to Influence Business Decision-Making, and
Guide Organizational-Level Strategy for Business Data Analytics.

These six business data analytics domains define the set of data-centric activities, as well as the business analysis practices that enable successful analytics initiatives.