How to establish quantitative operational indicators for B-side operations?

Some time ago, I wrote an article about how to build a B operation system. After building the operation system, the next step should be how to establish quantitative operations, otherwise all operations work cannot be carried out, evaluated and optimized. From a systemic perspective, operations include customers, contracts, orders, settlements, products, procurement, after-sales, channels, activities and many other aspects. So how do we build a set of quantitative operational indicators that can match it?

The significance of quantitative operations

Quantitative operation is the basis of refined operation. Through various quantitative indicators, we can clearly see the costs and benefits of business operations and avoid the business operations becoming a confusing account. With quantitative indicators, we can evaluate and improve each operation link in a targeted and measurable manner, and ultimately obtain higher revenue and profits. By quantifying operational indicators, we can:

• Control operating costs;
• Reasonable pricing;
• Promote sales;
• Customer management;
• Shorten settlement cycles;
• Optimize products;
• Reasonable assessment of business opportunities;
• Assessment activities;
• Channel management.

In short, the system is the framework and the indicators are the goals. Only with clear and quantifiable indicators can we continuously optimize operations.

Quantitative Operational Framework

Pricing Quantitative Operational Indicators

"Pricing is management" - Kazuo Inamori's Amoeba management philosophy. One requirement for pricing is to maximize the product of single profit and sales volume based on a correct assessment of the value of the product. Furthermore, the price must be the highest that customers are willing to pay. You must strive to obtain maximum profit within the price set after careful consideration.

Pricing is the starting point of all operations and the core of operations. The indicators that need to be considered include: cost price, market price, actual selling price, variable cost, fixed cost, break-even point, etc.

Price Index:

Cost price: the total cost of each product (unit variable cost + unit allocated fixed cost)

If the product pricing is uniform, the total cost of each product is relatively easy to calculate: the total cost of a single product = total variable cost/producible quantity + total fixed cost/producible quantity.

For example, in IAAS services, the cloud host has only one specification, such as 4vCPU 8G memory. We purchased a batch of host machines for delivering cloud hosts of this specification. Assuming that the annual depreciation cost of the purchased equipment is 90,000 yuan (variable cost), 100 4vCPU8G cloud hosts can be delivered (producible quantity). The annual fixed costs such as labor costs and office space rental are assumed to be a total of 100,000 yuan.

Then the cost price of each 4vCPU8G cloud host is:

Cost price = 90000/100 + 100000/100 = 900+1000 = 1900 yuan/year ≈ 158.33 yuan/month.

It can be seen that when a single product has a single specification, the cost price of the product is relatively easy to calculate. However, in general, the specifications of products are diverse. For example, in addition to the 4-core 8G cloud host, we also have 1vCPU1G, 1vCPU2G, 2vCPU4G, 4vCPU4G, 8vCPU16G and many other products with different specifications. So how do we calculate the cost price and how do we produce the optimal scale ratio (optimal sales ratio of cloud hosts)? If we think about it in depth, it is a complex mathematical programming problem. However, this article proposes another simpler cost price calculation method, namely pricing factor cost accounting.

Without considering the CPU hardware model, the cost of a cloud host is generally determined by pricing factors such as vCPU, memory, and hard disk capacity. We only need to calculate the unit vCPU cost, unit memory cost, and unit disk cost. Then, cost price = unit vCPU cost usage + unit memory cost usage + unit disk cost * usage

In IAAS services, storage nodes are generally independent of computing nodes and network nodes, and their unit costs are relatively easy to calculate. They can be calculated according to the single product planning model: disk unit cost = total variable cost/producible quantity + total fixed cost/producible quantity.

In IAAS cloud computing, in order to enable cluster drift, the CPU models of the servers purchased in the same cluster must be the same. For example, we purchased a batch of Huawei service equipment RH5885V3 as physical nodes. The price can be checked from the merchant quotes on Zhongguancun Online:

Huawei RH5885V3 standard server price:

CPU Intel Xeon E7-4809 v4 Standard Price:

DDR4 memory standard price:

As can be seen from the above figure, the standard configuration of the server is 8 2=16 physical cores and 16 2=32GB of memory. In IAAS services, the CPU is generally over-allocated and virtualized by 6 times, that is, there are a total of 16 2 3 = 96 vCPUs. Therefore, we need to increase the number of memory sticks. We can simply expand it according to vCUP: memory = 1: 2, so we need to expand 10 16GB memory sticks, that is, the server has a total of 16 12 = 192GB of memory. Our final reasonable purchasing configuration should be 16 physical cores and 192GB of memory, so the final cost of purchasing the server is 42500+1559 10=58090 yuan.

Of the 58,090 yuan, we know that the CPU cost is 8,156 × 2 = 16,312 yuan, the memory cost = 1,559 × 12 = 18,708 yuan, and other costs = 23,070. Since vCPU and memory are measured in different ways, they cannot be allocated directly by quantity. Instead, they can be allocated by cost ratio. This allocation method is essentially the same logic as the variable cost method for allocating fixed costs.

In addition, to ensure a certain degree of redundancy in the cluster, both vCPU and memory retain a 30% idle rate, so:

Cost per vCPU = (16321/96+111.94)/0.7 = 402.65 yuan/vCPU

Memory cost per unit = (18708/192+64.19)/0.7 = 228.05 yuan/GB

If depreciation is calculated over three years, without considering interest costs, the unit time cost of vCPU and memory is:

Monthly cost per vCPU = 357.12 ÷ 36 = 11.85 yuan/month

Monthly cost per unit of memory = 253.625 ÷ 36 = 6.33 yuan/month

The above only calculates the variable costs of vCPU and memory. We also need to consider the allocation of fixed costs. Assume that the variable costs and total production of various pricing elements of the cloud host are as follows:

Assume that fixed costs such as labor costs and office space rental are 1,000 yuan/month. The fixed cost of 1,000 yuan per month is allocated based on the variable costs of the CPU, memory, and hard disk. The cost prices of the three core pricing elements of the cloud host are as follows:

Cost price is actually an extreme pricing model that can be used to verify whether our business is sustainable.

If the market selling price is lower than the unit variable cost, the larger the company's sales volume, the greater the loss, and the business will basically be unsustainable.

If the market selling price is higher than the unit variable cost but lower than the unit total cost, then the increase in the company's sales scale can only reduce the scale of losses, but it cannot achieve profitability and the business cannot be continued.

If the market selling price is higher than the total unit cost, there will be a problem of profit balance point, which usually refers to the output when total sales revenue equals total cost (the intersection of the sales revenue line and the total cost line).

Cost price and break-even point are a dynamically changing process in the operation of a business. As operators, we need to calculate costs and break-even points regularly.

Market price: the current price of the product in the market. Operations personnel regularly obtain market prices of relevant competitors through various channels and compare the differences between their own prices and market prices.

Actual selling price: the actual selling price of the products we operate ourselves. In terms of pricing strategy, the best strategy is to adopt a following strategy, directly following the market price, which can be the same, or slightly higher or lower.

Pricing is the key to determining the success or failure of a business. When setting prices, should you choose small profits but quick turnover, or should you rather sell a small amount while ensuring a higher profit margin?

There are many options for pricing. After determining a certain profit margin, it is very difficult to predict how much sales volume can be achieved and how much profit can be generated. Operations must find the point where the product of sales volume and profit margin is maximized based on a correct estimate of the value of their company's products.

Sales quantitative operation indicators

In B-side operations , a common feature is that customers place an order once, lease for a long period of time and pay fees regularly. The platform has a high stickiness to B-side customers, and there is a certain cost for customers to switch platforms. Unless there are major changes in the external environment or organizational structure, the B-side will not switch easily. Therefore, in B-side operations, it is necessary to always pay attention to the status of existing orders.

The quantitative indicators mainly include: the number of existing orders, the amount of existing orders, the number of new orders, the amount of new orders, the number of terminated orders, the amount of terminated orders, the product specification sales ratio, and cash flow (sales collection) .

Analysis and monitoring can be performed according to time dimensions (year, quarter, month, week, day), customer dimensions, product dimensions, cloud environment dimensions, etc.

The number and amount of sales orders directly affect the platform's operating income, and changes in orders need to be monitored in real time. For example: By observing the changes in orders along the time dimension, we can find that products generally have a peak and off-peak season for sales. The sales volume from October to February at the end of the year and the beginning of the year is often much higher than the sales volume from May to August in the middle of the year. Corresponding resource allocation and product promotion efforts must be adjusted accordingly.

Pay attention to the changing trends of existing orders, understand the reasons for the changes, and take different measures based on different reasons, such as whether the increase in inventory is due to purchases by new customers or increased purchases by old customers.

For new customers’ purchases, it is necessary to ensure the customer’s first purchase service experience. The customer’s first experience with the product largely determines whether a long-term cooperative relationship will be established with the platform. For purchases from old customers, we need to consider their deep needs and help them optimize costs and services in order to establish a long-term trusting cooperative relationship.

For Lao Ge, for example, the loss of orders is not due to business changes or other market competitors attracting customers. Different measures need to be taken according to different situations. Changes in existing orders will have a great impact on the platform's long-term revenue. It is necessary to take responsive measures to avoid the loss of existing orders and continuously expand new customers and new orders.

Cost Quantification Operation Indicators

In the process of cost quantification, the first goal is to clarify the cost structure of platform operations. We perform cost accounting according to the following table, mainly to figure out how much money we spent, where it was spent, and how it was allocated.

Only by clarifying the cost structure in platform operations can we better control costs, especially in the current downward economic situation. Cost control is the easiest choice for enterprises. After all, open source requires external input, while cost control can be solved internally. The layoffs in Internet companies are a living example. If you look at the cost structure of Internet companies, you will find that labor costs are the bulk of Internet companies. From the perspective of cost control, layoffs become a necessary means.

Customer quantitative operation indicators

In customer management, the B-side operating platform has a very obvious 80/20 principle, that is, 20% of customers contribute 80% of the revenue. The usage scale of these customers affects the revenue of the entire platform. It is necessary to invest in full-time sales to conduct customer tracking and service management. Necessary guarantees must also be provided for operational support, such as regular analysis of the usage of core customers, detection of customer abnormalities in advance, whether the business is developing rapidly, whether the business is shrinking, whether customers are tending to leave, etc. For the other 80% of customers, we should pay attention to customer growth, churn, customer conversion rate, etc.

Settlement quantitative operation indicators

In settlement management, an important indicator is sales collection . Whether sales can be collected in time will always affect the normal operation of the platform and even the survival of the entire platform. As a platform operator, when building the operation system, you must plan the platform's sales collection cycle, collection methods, etc. to avoid a collection cycle that is too long or even cause bad debts.

In the operation of large B customers, the core large B customers often have strong negotiation capabilities, which makes the sales collection period become very long. At this time, the best way is to ensure that the platform we operate is strongly linked to the user's core business, so that everyone prospers and suffers together. The platform can have greater bargaining chips and require customers to at least give the necessary payment period to avoid the situation where the platform has to advance large amounts of funds.

If the platform is connected to non-core businesses or newly developed businesses, you should be careful. Not all large B customers are easy to get along with. If you are not careful, you may become a risk bearer of others' trial and error.

Operators need to pay attention to common settlement management indicators such as the collection ratio, collection cycle, collection customers, cash flow inflow and outflow difference, collection amount, bad debt ratio, and reasons for bad debts of the entire platform.

Other quantitative operating indicators

Others include:

• Product indicators focus on the sales and usage of each product on the platform, as well as the product status of competitors.
• Channel indicators focus on channel revenue, conversion rate, cost, etc.
• Business opportunity indicators focus on the opportunity cost and conversion rate of business opportunities.
• Activity indicators focus on activity benefits, publicity effects, costs, conversions, etc.
• After-sales indicators focus on customer complaints, service quality, etc.

Working in B-side operations means getting paid like a cabbage seller but having the heart of a drug dealer. B-side operations are complicated, and the key is to form a system, set indicators, and advance the work in a targeted, planned, and quantifiable manner. Let's encourage each other.

Author: Lao Ge

Source: Lao Ge