How did this large company achieve performance growth through business analytics?

How does business analysis empower performance growth? This article will give you the answer through a case study of a large company.

“When doing business analysis, you should not just pile up data, but also have insights and find opportunities for performance growth.” This is the requirement of many companies, but it makes students feel puzzled: How to do it? How to see opportunities from numbers?

Today, through a specific example of a business unit in a large company, I will systematically explain how to enable performance growth through business analysis. Without further ado, let's get straight to the case.

1. Background

A company has 100 stores, each of which contributes an average of 1.2 million yuan in annual revenue, totaling 120 million yuan. Now it wants to increase revenue by 50% to 180 million yuan in the next year. What should it do?

2. Wrong Practices

Some students, seeing the topic, said: This is easy. Earn an extra 180-120 million = 60 million, 1.2 million per store, open 50 new stores, done!

Don't laugh, many students really do the calculations this way. What are the problems here?

1. 1.2 million is the annual average, so the new store must be opened in January, otherwise it will not be enough.

2. 1.2 million is the average for all stores. Is it the same for new stores or old stores? We need to look at it separately.

3. 1.2 million is the average for all stores. Is it the same for large stores or small stores? You have to look at it separately.

4. How much investment is needed to grow by 60 million, and will the income and expenditure be balanced?

5. Are there too many clusters in one city, leading to a decline in efficiency?

6. Is there still room for growth for the old store? How big is the room?

7. In addition to stores, are there any new channels (such as online channels) that can be considered?

These details were not considered at all. Of course, it would be a joke.

Note that the 7 details listed here can be quantified with data and have nothing to do with specific business operations. We don’t need to consider, for example, whether the store entrance should be in red or blue, whether to place online advertisements or invite long-legged ladies to do live broadcasts. These 7 details ensure that the direction of business operations is correct and that resources are sufficient. If you can find the right direction and have sufficient resources, no matter how long or white your legs are, you can find someone to do live broadcasts.

This is the key to business analytics driving performance growth:

1. Clear direction of performance growth

2. Ensure resource investment

3. Eliminate obviously problematic practices

With these three guarantees, it is like going to the battlefield, equipping the front line with enough guns and ammunition, and choosing positions that are easy to attack. This is much more useful for the front line than airdropping an order from a plane: "Move the machine gun forward 100 meters."

It should be noted that there are actually four types of problems here, which need to be solved separately:

3. Business label issues

Questions 1, 2, and 3 are typical business labeling questions, namely: Do we understand business differences well enough and not be confused by averages? Business labels should be combined with specific business scenarios to find the factors that have the greatest impact on business results and make labels.

For example, for a physical store, we need to consider factors such as new store/old store, location, store size, etc., so we can make labels as follows.

If it is an online delivery, factors such as delivery channels and delivery forms should be considered, which can be labeled as shown below. At the same time, if there is process data of user conversion online, it can also be included in the indicator system to assist in judging the business situation.

Getting rid of averages is the basis for making business analysis useful to the business. Opportunities and problems all come from details.

IV. Input-output issues

Question 4 is a typical input-output problem. The key to input-output analysis is to separate resource usage and distinguish:

• Fixed investment (stores, live broadcast rooms, brand advertising, employee salaries, etc.)
• Variable inputs (promotional gifts, coupons, points, single discounts, etc.)

Fixed investment is more like infrastructure, and it is difficult to directly measure how much each investment can increase orders. Therefore, we can only do classified management and control the total amount of infrastructure investment for each channel. Variable investment is directly related to orders, so the benefits must be specifically assessed. If the resources invested do not see additional growth, the investment value must be reviewed.

This classification is necessary for refined input-output analysis. One-pot input analysis is the direct cause of many companies’ failure in history. It often manifests itself in that too much marketing expenses are spent on subsidies, but the core capabilities of the product are not improved (variable input is out of control); or too much money is spent on brand advertising, production capacity is over-expanded, product competitiveness is insufficient, and the capital chain is broken (infrastructure investment is out of control). Infrastructure represents long-term benefits, and direct promotion represents short-term benefits. Both cannot be neglected.

5. Marginal Benefit Issues

Questions 5 and 6 are typical marginal benefit problems. Marginal benefit problems are easy to solve in economics books because everyone always assumes that there is already a curve. But in reality, how to draw this curve is the biggest challenge. For example, the upper limit of the number of stores in a city. It is impossible to open too many stores in a city until they compete for business and go bankrupt. In reality, we can only make limited guesses.

At this time, we should pay attention to finding suitable samples for observation. For example, if there is a problem with the number of stores in a city, we can split the cities and focus on the cities where the marginal benefits of new stores have declined. It is possible to recommend business control before the ROI becomes negative. This split requires business tags as a basis, so we must first do business tags and then see whether there is a problem of diminishing marginal benefits under various tags.

6. Potential Solution Issues

Question 7 is a typical potential solution problem. The biggest problem with potential solutions is that there is no data. Without the accumulation of test data, it is difficult to derive the correct conclusion directly by reasoning out of thin air.

If there is really no data at all, the priority is to reserve enough resources and organize testing (rather than trying to force data). At this time, you can look at the overall investment plan to see what else can be squeezed out and draw resources. In addition, the test time and expected test results should also be given in advance. This can help the business clarify goals and control the progress of testing.

If you have test data, that would be great.

1. Calculate the input-output ratio of test results

2. Evaluate the optimization space of the test process

3. Calculation: If the scope is expanded, the expected input and output

This will output a relatively complete evaluation of potential solutions.

VII. Comprehensive Analysis of the Scheme

With the above analysis basis, we can quickly identify the problems in the solutions proposed by the business.

1. Whether the input-output data of the channel is misestimated

2. Whether the problem of diminishing marginal benefits has not been considered

3. Did you fail to pay attention to the differences between different types of channels/products/customers?

4. Whether the combination of input and output is not considered and the input factor is ignored

5. Have you not considered the optimization details? Is there a lot of room for optimization?

Combined with data, it can quickly identify the funnel of business solutions and remind the business side to improve. For management, being able to identify problems is also driving business growth, which is always better than launching a product without thinking and then rushing to fix the loopholes.

Of course, if the analysis is done thoroughly, we can propose business opportunities ourselves, and the way to propose is the same as the way to discover problems.

1. I found that there are types of stores with good input-output ratios.

2. I found that there are activities with obvious investment effects.

3. I found that there are channels where marginal benefits have not yet diminished.

4. I found that there are details of the conversion path that need to be optimized

5. I found that there are successful experimental cases that can be promoted

The combination of these elements is an opportunity point that can be proposed. After that, you can communicate with the business to see if there is a possibility of expansion and whether resource support is needed. In many cases, even if the business analyst does not eliminate new solutions, it is a great help to do a good job of resource estimation for the opportunity point.

Author: Down-to-earth Teacher Chen; WeChat public account: Down-to-earth Teacher Chen