Analytics is the study of analyzing data to derive business insights and tangible action steps.Business Analytics makes a distinction between relevant and irrelevant knowledge. Business Analytics is thus all about business relevancy, actionable insight, performance measurement and value measurement.
2.Types of Business Analytics
Descriptive Analytics answers the questions: What has happened in my business? Why has it happened? What do I know about my customers, competitors, suppliers, etc.? Examples of this are Business Intelligence, Reporting etc.
Predictive Analytics answers the questions: What is likely to happen? What is likely to be true about my customers, competitors, suppliers, etc.? Examples of this are forecasting, regressions, data mining etc.
Prescriptive Analytics answers the questions: What should I do? What is the best course of action given what I know and what I think will happen? Examples of this are optimization, mathematical programming, heuristic algorithms etc.
3.Basic Domains Within Analytics
- Behavioral Analytics
Behavioral analytics is a subset of business analytics that focuses on how and why users of ecommerce platforms, online games, & web applications behave. Behavioral analysis allows future actions and trends to be predicted based on all the data collected.
Types of Behavioral Analytics:
- Ecommerce & Retail
- Online Gaming
- Application Development
- Cohort Analysis
- Collections Analytics
Credit cards and consumer and business loans have been experiencing vacillating delinquencies and losses over the last few years, resulting in an overall increasing trend in delinquency and write off rates. Losses will be mitigating by understanding customer behavior, customer communication preferences, and the effectiveness of various channels in increasing response rate and maximizing recovery.
- Financial Services Analytics
The opportunity for the sector is to unlock the potential in the data through analytics and shape the strategy for the business through reliable factual insight rather than intuition. Many Financial institutions are seeing improved data quality and the use of analytics as an opportunity to fundamentally change the way decisions are made and to use the data for commercial gain. Financial services analytics includes Risk management, Treasury Analytics and multi-Channel customer Management.
- Fraud Analytics
Data analytics technique have a significant role to play in the early-warning, detection and monitoring of fraud. These techniques can allow your organization to extract, analyze, interpret and transform your business data to help detect potential instances of fraud and implement effective fraud monitoring programs.
- Marketing Analytics
Marketing analytics is the practice of measuring, managing and analyzing marketing performance to maximize its effectiveness and optimize return on investment (ROI). It can offer profound insights into customer preferences and trends. Marketing Analytics, considers all marketing efforts across all channels over a span of time- which is essential for sound decision making and effective, efficient program execution.
- Pricing Analytics
Pricing decisions have a major impact on the profitability index of an organization. Prizing Analytics enables proactive management of pricing policies and strategies, and guides you to arrive at the right pricing that is in-line with your market positioning and business strategy.
- Retail Sales Analytics
Retail Analytics help retailers to effectively collect, analyze and act on both customer and organization data in near real time, across all the channels they function in. Retailers view retail analytics as an effective tool to increase customer wallet share, gain higher margins, increase complimentary store sales and reduce wasted marketing budget.
Risk & Credit Analytics
A credit risk is the risk of default on a debt that may arise from a borrower failing to make required payments. Many financial institutions seek assistance from external parties due to internal limitations in required expertise, presence of resources, analytical capabilities, and availability of data. They also view the application of risk management analytics and methodologies as “best practice” in their daily operations.
- Supply Chain Analytics
All businesses with a supply chain devote a fair amount of time to making sure it adds value, the new advanced analytic tools and disciplines make it possible to dig deeper into supply chain data in search of savings and efficiencies.
- Talent Analytics
Human resources analytics, also called talent analytics, is the application of sophisticated data mining and business analytics (BA) techniques to human (HR) data. Talent Analytics provide tangible and quantifiable insights needed to understand and help you direct workforce and organizational performance to achieve your business strategy and build a strong value-centered organizational ethos.
- Telecom Analytics
Telecom analytics encompass sophisticated business intelligence (BI) technologies that are packages to satisfy the complex requirements of telecom organizations. The adoption of analytics in telecommunications is intended to improve visibility into core operations, internal processes and market conditions, discern trends and establish forecasts.
- Transportation Analytics
- Driving efficiency ,reducing congestion, getting people where they need to go faster
- Understanding the Trends
Transportation analytics aims at covering diverse data ecosystem in order to release the potential of multimodal transportation systems.
Benefits of Business Analytics
- Improving the decision making process (quality & relevance)
- Speeding up of decision making process
- Better alignment with strategy
- Realizing cost efficiency
- Responding to user needs for availability of data on timely basis
- Producing a single, unified view of enterprise information
- Synchronizing financial and operational strategy
- Increase revenues
- Sharing information with a wider audience
Skills required to succeed in a Business Analytics Career
Popular Tools for Business Analytics
“Analytics and Big data” is increasingly becoming a key skill-set in manager’s arsenal. CEOs and business leaders want to understand what they can do with data, organizations want to know how they can train and recruit people with relevant analytical skill-sets.
Analytics is not just about generating insights and getting those to the right people. To sustain the long-term success of data-driven innovation, it is necessary to continually revise one’s analytical approach in order to generate insights that lead to new innovation and competitive advantage.