From fragmentation to closed loop: a practical framework for business analysis, financial analysis, and data analysis

In business operations, business analysis, financial analysis and data analysis are often regarded as independent functions. However, with the intensification of market competition and the increasing demand for refined management, how to organically combine the three to form a closed loop from data to decision-making has become the key to improving the competitiveness of enterprises. This article will explore the relationship between business analysis, financial analysis and data analysis, analyze their respective advantages and limitations, and propose a method to build a unified indicator system and analysis framework to help enterprises achieve seamless connection from business insights to financial performance, and improve overall operational efficiency and decision-making quality.

Many students have doubts in their work:

*Why have companies begun to pay attention to business analysis in recent years?

*Why are finance, data, and business all doing operational analysis?

*Why was the business analysis I did criticized for only having year-on-year and month-on-month comparisons and no conclusion?

Today’s article will explain it clearly to you.

01 Financial Analysis VS Data Analysis

Financial analysis is a type of data analysis, but it was created much earlier than the concept of "data analysis" that has become popular in recent years. Because it is a legal obligation for companies to keep financial accounts, financial statements can be output with financial accounts, and financial analysis can be performed. The core of financial analysis is the three major reports:

1. Balance sheet: The company's assets, liabilities, and owner's equity, measuring whether the company is financially sound.
2. Profit and loss statement: income, costs, expenses, net profit, measure the company's ability to make money
3. Cash flow statement: cash flow generated by operating, investing, and financing activities, measuring whether the company's funds are safe

Financial analysis in a narrow sense is based on financial statements. When you look at the three statements together, you can interpret many meanings. For example, when investing or buying stocks, you must not buy a company that has been losing money for years, is insolvent, or has cash flow that is on the verge of breaking. It is almost dead. Financial statements can be said to be a physical examination form for a company, which can directly measure the performance of the company.

However, financial analysis has certain limitations:

1. Financial data is updated slowly, usually on a monthly basis, and cannot reflect business changes in a timely manner

2. Financial data lacks business details and cannot deeply identify business problems

3. Financial data is compiled according to the financial account table, which is somewhat different from the actual business

Therefore, if you want to conduct a more in-depth analysis, you must combine it with business data. This is the evolution from financial analysis to operational analysis.

02 Business Analysis VS Financial Analysis

Business analysis originates from the need of corporate management to "analyze business conditions rather than just present financial results". Among the three financial statements, the income statement is most closely related to business:

1. Revenue and cost are the most important issues in daily business work

2. Sales expenses and R&D expenses are important levers for business to drive performance

3. Operating profit is a key indicator that directly measures business performance

Therefore, the key to business analysis is to prepare a "management income statement" and add a large number of business process indicators and subdivision dimensions based on financial results, such as:

1. Process indicators of revenue: number of leads/conversion rate/average order value, number of salespeople/average productivity

2. Revenue segmentation dimensions: region/sales channel/customer type/product category/product subcategory

3. Cost process indicators: raw material cost/manufacturing cost/labor

4. Cost segmentation dimensions: key materials/auxiliary materials, fixed/variable costs

5. Cost segmentation dimensions: brand promotion/product promotion/user subsidies/channel subsidies

This will allow the data to better reflect business details, allowing for in-depth analysis.

Obviously, this requires a high quality of data collection. Therefore, the first to establish a complete business analysis system are banks/operators/airlines. Because these three industries can collect data from every user. And the user's use of bank cards, phone calls and text messages, and flying can be monitored by the big companies in these three industries. With rich process data collection, business analysis can be more in-depth.

These rich data have led to a lot of in-depth analysis:

1. User value assessment: Which types of users have greater spending power and require less maintenance costs?

2. Sales funnel analysis: Which is the obstacle point in each link from user registration to sales?

3. Marketing benefit analysis: Which of the different marketing activities is more effective and can bring net growth?

4. Channel capability analysis: Which channels have a high investment-to-production ratio and can achieve sustained volume growth?

5. Product profit and loss analysis: Which products bring more profits with less investment and are truly popular products

The introduction of these analytical methods has enabled operational analysis to play a huge role in banks/airlines/operators, and it was able to direct front-line operations as early as 10 years ago.

The Internet industry also has an inherent advantage in collecting data. A user's behavior in an APP/Mini Program can be fully recorded, so a lot of detailed analysis can be done. For example, Tencent IEG established a business analysis system for game products 10 years ago, examining the business behavior and financial performance of each product in detail (of course, this also led to the game project team over-emphasizing krypton gold and ignoring the quality of creation, which is a later story).

But most Internet companies don’t pay much attention to this, because in the decade of Internet development, the right way is to work hard and fast! No one seriously calculates the cost, and everyone cares more about traffic, user scale, and turnover, rather than profit. It was not until recent years that a large number of companies encountered a capital winter and began to pay attention to business analysis again.

03 The Renaissance of Business Analysis

Starting from 2023, business analysis has ushered in a renaissance. As the pressure on business operations increases, companies have begun to strengthen the assessment of business performance, strengthen cost control, and emphasize input-output ratio rather than scale growth. Some companies give this task to data analysts, some to finance, and some to specialized business management departments. Therefore, the situation mentioned at the beginning has formed, where every department has to do business analysis.

However, it is difficult for different departments to carry out business analysis.

1. Business departments often only care about revenue, and lack the concept of cost, expenses, inventory, accounts receivable, etc., and often make wrong decisions such as "increased revenue without bonus" and "receivables grow faster as revenue increases".

2. The finance department does not understand the business, especially the emerging business concepts in recent years: fission, live streaming, private domain, DTC, etc.... They cannot reasonably aggregate costs and cannot clearly sort out business indicators, so they cannot go deep into the business from financial result indicators.

3. Data analysts lack financial concepts, especially financial cost-volume-profit analysis. They cannot reasonably distinguish between decision-related costs and sunk costs, resulting in insufficient depth in data analysis.

Therefore, if you want to do a good job of business analysis, you have to

• Integrate business and financial indicators and establish a unified indicator system
• Have a global perspective and consider issues such as revenue, cost, expenses, inventory, etc.
• When going deep into the business, you can sort out your thoughts and build an analysis model based on the characteristics of products/customers/channels

This requires that all people involved in business analysis have sufficient knowledge of business and finance.