Still asking if there is a business analysis template? Do these steps first

Many companies' business analysis reports often make the mistake of "explaining results with results". So how can we achieve high-quality business analysis? This article provides some ideas and methods, which are recommended for those who are interested in data analysis.

Many companies write long business analysis reports, with dozens of pages of PPT, hundreds of indicators, and dense numbers. However, once they are presented at the business analysis meeting, they will be criticized as: "The analysis is not in-depth!" "The viewpoint is not prominent!" Obviously, there are so many numbers and charts, why is it not in-depth?

1. Problem Analysis

Because these reports make the mistake of "using results to explain results". Many business analysis reports use financial indicators, such as revenue, profit, cost, expenses, etc. Even if they calculate indicators such as "profitability" and "growth ability", they are still secondary processing using financial indicators.

From a business perspective, these indicators are all results. If we only use results to explain results, we will come up with useless and brainless conclusions such as "profits are lower both year-on-year and month-on-month, so we need to increase them" and "low profits are because costs are high, so we need to lower them."

After hearing the result of "low profits", people want to know more about:

• Is it because of the overall environment or because I didn’t do it well?
• Don’t just say that the overall environment is not good, are there any solutions?
• What did I do wrong? Was it the wrong direction or poor execution?

Therefore, when outputting the report, you should make a directional judgment on the cause of the problem. If it is really a macro-environmental problem, find a solution under the new environment. If it is not a macro-environmental problem, block the excuses of those who shirk responsibility.

To achieve this, you need to:

• Don’t just look at the result indicators, add process indicators
• Find the factors that affect the results and identify the key factors
• Establish analysis logic and find the key points of the problem

Let’s take a look at how to do it.

2. Increase process indicators

When it comes to "adding business indicators to the business analysis report", many people will bring out the following: performance = number of customers * conversion rate * average order value. Note! From a business perspective, indicators such as number of customers, conversion rate, and average order value are still result indicators. If you only take these indicators in, you will still come to the brainless conclusion that "the decline in performance is because there are fewer customers, so we need to increase it."

The process indicators to be added should be able to reflect: "How the business is done". For example, on the revenue side, it is necessary to sort out the business process to see what steps are involved from customer leads to transactions and what data records are there. To give a simple example, the common toB business is shown in the figure below. It is a typical funnel-type conversion process, and a funnel-type indicator system can be sorted out:

Some business actions are difficult to measure with indicators, such as marketing strategies, sales pitches, product mix, and promotional methods. These can be quantified by attaching business labels. For example, sales pitches can be summarized into three categories, ABC, and then combined with conversion data, to observe which category is more effective, thereby further deepening the understanding of the business process.

On the cost side, the handling method is slightly different. On the cost side, we must first distinguish the relationship between various costs and revenues. After all, does this money spent directly bring in revenue or is it just a supplement? Does it need to be accumulated to a certain level to be effective? Or is it a matter of one penny for one dollar, and one earns as much as one invests? Only by distinguishing clearly can we combine the revenue data to do performance evaluation and control the investment that does not directly bring in revenue.

The success of this step is directly related to the company's degree of digitalization. If the company's degree of digitalization is low, the revenue side is entirely based on sales in the mind, and only order data can be analyzed; the cost side only has simple financial items, and there is no corresponding business behavior. Then it is difficult to do in-depth analysis.

3. Identify influencing factors

Do all the added process indicators need to be included in the business analysis report? Of course not. Stacking too many process indicators will make the report more lengthy and more difficult to see the results. Therefore, data analysts are needed to identify the key factors that affect business results and include indicators that represent the key factors in the report.

For external influencing factors, focus on:

• Impact of upstream raw materials, labor, and resources on costs
• The impact of downstream customer demand quantity, preferred types, and preferred channels on revenue
• Are competitors launching targeted price cuts/competing for upstream and downstream resources?

Here, you need to collect a lot of upstream and downstream market data, and communicate more with your company's procurement, human resources, and channel departments. It is possible that the overall environment is really getting worse, or it is possible that our company's procurement, human resources, and channel departments are operating poorly. Find the supply/channel with advantages. In order to make accurate judgments, a lot of intelligence collection is very important.

For internal influencing factors, what is the current business strategy? Specifically, it includes:

• People: What kind of customers are the core customers?
• Product: Product main function/price/service
• Field: What is the main channel and what are the quantity/quality requirements?

First understand the business strategy, then further observe whether the front-line departments have implemented it. If the business strategy is set to develop high-end customers, but the front-line departments are still flooding the market with customers without focusing on key areas, then there is a problem with the execution. If everyone is following the business strategy, but there is no effect, then you need to find time to reflect on whether the strategy needs to be adjusted.

The success of this step is directly related to the depth of the data analyst's understanding of the company's internal and external situations. If the data analyst works in isolation every day, lacks communication with the business, and lacks the collection of industry data and customer data other than internal data, it will be difficult to achieve this.

4. Establishing analysis logic

After sorting out the indicators and confirming the key factors, you need to establish the analysis logic. The analysis logic can be established using the MECE method. The basic idea is: confirm the problem from both positive and negative aspects. Use the onion peeling method to analyze layer by layer to find the answer (as shown below)

Note! There is no fixed routine for analysis logic, which is completely guided by "answering the leader's questions". For example, if everyone is complaining about the "bad environment", the leader may instruct: "Find out what else can be done when the environment is bad?" Or the leader may instruct: "All they know is complaining about the environment! Shut them up!" In these two cases, the analysis ideas are obviously different (as shown in the figure below). When doing the analysis logic, you must be clear: what exactly does the leader want...

The success or failure of this step is directly related to the ability of the data analyst. Fixed financial statements can only illustrate the problem, but cannot explain it. If you want to explain the problem, you have to build analytical logic around the current problem. Eliminate wrong answers, summarize correct answers, and test the effectiveness of business practices. If the data analyst lacks analytical logic training and can only take numbers, he will not be able to do this well.

V. Summary

In summary, high-quality business analysis requires efforts in many aspects:

• The business has a certain degree of digitization and can collect process data
• Data analysts have a full understanding of the business and a rich library of tags to describe business behaviors
• Data analysts have good communication with leaders and can grasp the direction of analysis

Of course, not all companies have such good conditions. Many small factories have poor treatment, low wages, and a mess of data infrastructure. With only a pitiful amount of order data, the leaders still expect to analyze and come up with amazing conclusions, which is really difficult. At this time, it is recommended to adopt some affordable alternatives, train yourself to label and build analytical thinking, and then switch to a regular large factory as soon as possible.

Author: Down-to-earth Teacher Chen

Source: WeChat public account "Down-to-earth Teacher Chen"