Business Analysis Là Gì
Trong thời đại công nghệ 4.0 hiện nay, nền kinh tế Việt Nam đang có những bước chuyển mình vô cùng mạnh mẽ và dần có chỗ đứng trên thị trường quốc tế. Chính vì vậy, nghề Business Analysis đang ngày càng được biết đến nhiều hơn tại Việt Nam giúp tối ưu hóa hoạt động kinh doanh cho các doanh nghiệp quy mô lớn, từ đó cho ra đời các sản phẩm công nghệ chất lượng nhất.
Business Analysis vs. Business Analytics: Distinguishing Factors
While both business analysis and business analytics are integral to informed decision-making within an organization, they serve distinctly different functions.
Business analysis focuses on understanding the current state of the business, identifying improvement opportunities, and defining requirements for implementing changes. The primary goal is to bridge the gap between business needs and technological solutions, ensuring that the implemented changes align with the organization's objectives.
On the other hand, business analytics is primarily concerned with exploring data, discovering insights, and predicting future trends. The focus is on leveraging data to improve decision-making, optimize processes, and gain a competitive edge. Business analytics provides organizations with a data-driven approach to uncovering patterns, correlations, and opportunities for growth.
While both disciplines rely on data, they differ in terms of data usage and scope. Business analysis involves gathering and analyzing data from various sources, including customer feedback, market research, and internal processes. The data analyzed in business analysis is often specific to the organization's operations, stakeholders, and industry.
In contrast, business analytics encompasses a broader range of data sources. It involves leveraging large volumes of structured and unstructured data, including customer data, market trends, social media interactions, and industry benchmarks. Business analytics utilizes advanced tools and techniques to extract insights from diverse data sets, enabling organizations to make data-driven decisions.
A business analyst operates at the intersection of business needs and technical solutions. They function as a conduit between diverse stakeholders - including management, operations, IT, and even customers - working to understand, communicate, and address business requirements.
Their responsibilities can span from defining business requirements, and process mapping, to designing functional solutions for problems or opportunities identified. They often play a pivotal role in driving change within an organization, ensuring that any implemented solutions align with the organization's strategic goals and deliver value.
Conversely, business analytics professionals are chiefly concerned with data - its analysis, interpretation, and the insights that can be gleaned from it. They primarily work with data sets, employing various analytical models and tools to extract valuable information. They transform raw, often complex, data into actionable insights that can influence strategy and decision-making.
Their role is heavily focused on predicting future outcomes and trends, allowing organizations to anticipate market movements and customer behaviors, thereby driving competitive advantage and growth.
Business analysis produces deliverables such as business requirements documents, process models, and functional specifications. These documents serve as blueprints for implementing changes and are vital in ensuring alignment between business needs and technology solutions.
In contrast, business analytics generates insights, reports, and visualizations that facilitate data-driven decision-making. These outputs help stakeholders understand complex data patterns, identify key performance indicators (KPIs), and uncover actionable insights. Business analytics empowers organizations to make informed decisions and respond effectively to market changes and customer preferences.
What types of data are used in business analytics?
Business analytics encompasses a broader range of data sources. It leverages large volumes of structured and unstructured data, including customer data, market trends, social media interactions, and industry benchmarks. Advanced tools and techniques are used to extract insights from diverse data sets.
Example: Addressing Shopping Cart Abandonment for an Ecommerce Company
Let's imagine a large ecommerce company experiencing a high rate of shopping cart abandonment.
A Business Analyst would first look to understand the underlying reasons behind shopping cart abandonment. They might interview customers, review user feedback, and collaborate with different stakeholders like customer service representatives, sales teams, and technical staff. Their goal would be to understand the customer journey from start to finish and pinpoint where and why potential customers are dropping off.
Upon identifying the issues - it could be a complicated checkout process, hidden costs that become apparent only at the final stage, or a lack of trust badges on the site - the Business Analyst would work with relevant teams to design and implement solutions. For example, they might suggest streamlining the checkout process, making pricing transparent from the start, or adding security badges to increase consumer trust.
A business analyst, on the other hand, would approach the problem through a detailed analysis of the company's data. They would utilize analytic tools to dissect shopping cart abandonment rates, customer demographics, and customer behavior data. Their aim would be to find patterns or trends that might be contributing to the problem.
Through their analysis, they might discover that a high percentage of customers abandon their carts on mobile devices, indicating a potential issue with mobile optimization. Or they might find that abandonment rates spike at certain times, suggesting a possible server overload or poor website performance during peak hours. Based on these findings, they would make data-backed recommendations to address the identified issues.
What types of data are used in business analysis?
Business analysis involves gathering and analyzing data from various sources, such as customer feedback, market research, and internal processes. The data analyzed in business analysis is often specific to the organization's operations, stakeholders, and industry.
What is the difference between business analysis and business analytics?
Business analysis focuses on understanding the current state of the business, identifying improvement opportunities, and defining requirements for implementing changes. It bridges the gap between business needs and technological solutions. Business analytics, on the other hand, explores data, discovers insights, and predicts future trends. It leverages data to improve decision-making, optimize processes, and gain a competitive edge.
What are the deliverables of business analysis?
Business analysis produces deliverables such as business requirements documents, process models, and functional specifications. These documents serve as blueprints for implementing changes and ensuring alignment between business needs and technology solutions.
Example: Optimizing Pricing Strategy for a Global Retail Chain
Consider a global retail chain that wants to optimize its pricing strategy.
A Business Analyst would first aim to understand the current pricing strategy of the global retail chain, its strengths, weaknesses, and the factors impacting it. They might review internal processes, consult with stakeholders such as sales, marketing, supply chain, and financial teams, and analyze competitor strategies.
Once they gather enough insight, they may identify potential areas of improvement. For example, if they find that pricing decisions are mostly made based on cost-plus pricing, they might suggest incorporating value-based pricing for products with unique value propositions. If they identify that price adjustments are slow in response to market changes, they might recommend more dynamic pricing strategies. Their goal would be to ensure the pricing strategy aligns with the company's overall business objectives, market conditions, and customer perceptions.
A Business Analytics professional would take a more data-driven approach to optimize the pricing strategy. They would analyze historical sales data, customer purchasing behavior, pricing elasticity, and other relevant data to derive insights. This could involve predictive modeling to forecast how price changes might impact sales volume, or segmentation analysis to understand how pricing preferences vary among different customer groups.
For instance, through their analysis, they might identify certain products that are less price sensitive and could therefore withstand a price increase without significantly impacting sales volume. They might also uncover that customers from a certain geographic region are more willing to pay higher prices for premium products, suggesting an opportunity for regional price differentiation.
How can organizations leverage business analysis and business analytics together?
By leveraging business analysis and business analytics together, organizations can effectively harness their data assets, optimize processes, and gain a competitive edge. Business analysis identifies specific improvement opportunities and proposes solutions, while business analytics provides the data-driven insights to inform decision-making and drive strategic planning.
What are the outputs of business analytics?
Business analytics generates insights, reports, and visualizations that facilitate data-driven decision-making. These outputs help stakeholders understand complex data patterns, identify key performance indicators (KPIs), and uncover actionable insights.
How can a marketing analytics platform like Improvado help with business analysis and business analytics?
Improvado offers a complete data pipeline, from data extraction and transformation to normalization and visualization. Its robust business analytic tools enable organizations to unlock the true potential of their data, drive informed decision-making, and stay ahead of the competition. Improvado's platform facilitates both business analysis and business analytics by providing the necessary tools to gather, analyze, and visualize data effectively.
Two Disciplines for Organizational Success
In summary, business analysis and business analytics are distinct yet complementary disciplines that play integral roles in driving organizational success. Business analysis focuses on understanding business needs, facilitating change, and ensuring alignment between stakeholders and technology teams. Business analytics, on the other hand, emphasizes data exploration, pattern recognition, and predictive modeling to enable data-driven decision-making.
By leveraging business analysis and business analytics in tandem, organizations can effectively harness their data assets, optimize processes, and gain a competitive edge. Whether it's identifying improvement opportunities or uncovering actionable insights, both disciplines are essential components of a comprehensive data-driven strategy.
How do business analysis and business analytics contribute to organizational success?
Business analysis helps identify improvement opportunities and ensures that business needs are effectively communicated and implemented. It drives organizational growth and success by streamlining operations and optimizing resources. Business analytics, on the other hand, provides organizations with data-driven insights that inform strategic planning, operational efficiency, and competitive advantage. It empowers decision-makers to make informed choices and respond effectively to market changes and customer preferences.