Tuesday, 4 February 2014

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:

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.

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.

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