Branch Management for Businesses with 10,000 total customers per day

Welcome to the Optimal Outlet Curve Series. This set of guides is designed to help businesses identify the additional number of outlets they require to meet their present demand simply by looking up a chart (which is provided for each case study).

For this series (#1), we are considering a business with a total of 10,000 customers per day. Most small and medium scale businesses fall into this category. 

These 10,000 customers per day are spread across all geographic regions in which the business may operate, including states, cities and counties. It is the total estimate of people using the business' outlets per day.

[Related Article: How to Determine Your Optimal Number of Business Outlets]
 
Assumptions

The curve provided below can be used to accurately determine how many additional outlets are needed to contain present demand on the basis of an overcapacity ratio and branch capacity.

The overcapacity ratio is an expression of the maximum overload any particular business branch can endure, and is given as 20% for the sake of this case study. This means that we assume that every branch in the business network can take no more than 20% of its designed capacity e.g. an outlet designed to service 100 people per day having a maximum of 120 customers per day.

Branch capacity is simply the design capacity of each branch in the business network. 

To generate the curve, we plot data for an increasing number of saturated outlets (currently existing outlets that are going over capacity) as well as increasing branch capacity, so businesses can select the one that best fits their current situation.

Chart #1: 5 Saturated Outlets  

If your business services no more than 10,000 customers per day and you currently have 5 outlets that are going over capacity, use the chart below to determine how many additional outlets you need to have to meet your present demand simply by selecting the branch capacity that matches your outlets (on the x-axis) and moving it up to touch the curve. Once you touch the curve, read off the corresponding value on the y-axis for your additional number of outlets required.

Chart #2: 10 Saturated Outlets

If your business services no more than 10,000 customers per day and you currently have 10 outlets that are going over capacity, use the chart below to determine how many additional outlets you need to have to meet your present demand simply by selecting the branch capacity that matches your outlets (on the x-axis) and moving it up to touch the curve. Once you touch the curve, read off the corresponding value on the y-axis for your additional number of outlets required.

 

Chart #3: 15 Saturated Outlets  

If your business services no more than 10,000 customers per day and you currently have 15 outlets that are going over capacity, use the chart below to determine how many additional outlets you need to have to meet your present demand simply by selecting the branch capacity that matches your outlets (on the x-axis) and moving it up to touch the curve. Once you touch the curve, read off the corresponding value on the y-axis for your additional number of outlets required.

Chart #4: 20 Saturated Outlets  

If your business services no more than 10,000 customers per day and you currently have 20 outlets that are going over capacity, use the chart below to determine how many additional outlets you need to have to meet your present demand simply by selecting the branch capacity that matches your outlets (on the x-axis) and moving it up to touch the curve. Once you touch the curve, read off the corresponding value on the y-axis for your additional number of outlets required. 

Solving the Outlet Problem: How to Figure Out Your Optimal Number of Business Outlets

This is a very important question for corporate managers and CEOs:

How many outlets should you REALLY get for your business?

There are many ways of finding a solution, but an engineering concept called “progressive load balancing” or PLB may hold the most reliable answer for your business.

In the original engineering concept, a load (weight) is applied to a slab and uniformly distributed over a number of equally-spaced supports attached to the slab. PLB theory then determines the conditions for progressive failure (saturation) of each support component until they all eventually fail.

Applied to business, PLB can be used to model factors like demand, subscriber base, clientele, sales volumes, investment opportunities, and so on, as loads being applied to your business units (branches, service centers, stores, and so on) under constraining factors like branch capacity and maximum overload.

[Related Article: Product Costing for Small Businesses]

The result? You can pinpoint the exact number of business units (whether branches, service stations, or shops) you need to effectively meet your demand.

Talk about smart business decision making!

Calculating Optimal Number of Business Outlets with PLB

I’m an engineer by training, so I was able to compress all the technical aspects of this very important theory into a simple equation you can use to calculate the optimal number of outlets for your business (n) on the basis of your average branch capacity (B), maximum overcapacity ratio (f), number of currently saturated outlets (k), and total customer base (L).

Find below the simple PLB equation for optimal number of branches:

I will now provide three case studies demonstrating how to apply this theory for your business.

Case Study 1: Event Manager

You are an event manager and you’ve just sold 20,000 tickets for a show in town. What’s the problem? You were initially expecting 7,000 people and originally booked 5 venues with an average capacity of 1,400 people. 

All 5 venues you originally booked are now saturated. Assuming any new venue you book will have the same average capacity of 1,400 people and you can accommodate up to 20% additional overflow capacity at each venue, how many additional venues should you book?

Without PLB, you might be tempted to just find the difference between 20,000 and 7,000 and then divide that by 1,400. That approach will tell you to book an additional 9 venues – but you’d be overbooking and you will lose money.

With PLB, you have the following analysis:

So you really need to book an additional 8 venues to properly handle your excess crowd capacity.

Case Study 2: Fast Food Chain

You are the regional manager of a fast food chain. In your region, 500 customers daily for each of your outlets is normal with a total potential customer base of 10,000 for the region.

Suddenly, you notice that the 8 outlets in your region are saturated, with outlet managers reporting an average of 700 customers daily. This indicates a significant increase in active customers in your region.

How do you handle this?

To reduce work pressure on your staff and maintain the food standards and the quality of service for the saturated outlets, you may need to add new outlets in the region to absorb and equilibrate the excess demand.

But how many? PLB business simulation gives the answer.

If all 8 of your current outlets are saturated and your maximum acceptable overload is 10% (f = 1.1), such that at worst, you can permit no more than 10% additional demand for each of your outlets, and your normal branch capacity (B) and total potential demand are 500 people per day and 10,000 people respectively,

Then the optimal number of outlets is given by PLB as:

To operate efficiently and reduce demand strain, the regional manager needs to open up an additional 11 outlets, bringing the total number of outlets from 8 to 19.

Case Study 3: Telecom Operator

In our final scenario, we are considering a telecom operator with a total subscriber base of 4,000,000 people. Currently, their network consists of 200 service stations nationwide – with each station designed to provide cell coverage for 10,000 people.

Obviously, the network is strained as the total installed capacity cannot meet the target population. The solution: they need more service stations. But how many?

Simply doubling the number of service stations would seem correct to the layman, but there are other factors to be considered: what is the acceptable network quality?

If we agree that 85% network quality is acceptable at any given time, then it means that we can permit the network to be overloaded by 15% at any particular instant.

f = 1.15, k = 200, B = 10,000, L = 4,000,000

Using PLB, we obtain the optimal number of service stations as:

So since the number of optimal service stations is 374, an additional 174 stations are required – far less than the 200 a layman would have estimated.

Benefits of Using PLB Theory

·         As seen earlier, using Progressive Load Balancing (PLB) theory to model your business demand loading can help you pinpoint your expansion options and arrive at logical and mathematically-precise estimates compared to pure guesswork or experience-based suggestions

·         PLB theory can help you plan properly for your growth and reduce losses due to overspending

·         It is simple and anyone can calculate anything with PLB using a simple handheld business calculator, spreadsheet, or mobile calculator app

Thanks for reading! Please provide your questions or comments below!