Throughput Economics Chapter 1: The need for replacing cost accounting with a much better decision support methodology

A decision to make

Bake-T is a large producer of bread and other bakery products. The company sells to supermarkets, bakery shops and hotels. Bake-T just got an interesting business offer. Big-Event offers to use Bake-T products in all their events. Big-Event runs three different events every day. These include conferences, luxurious weddings and special-organizational-events. The problem is that Big-Event is willing to pay only 60% of the list price!  The average margin of Bake-T products, based on their recent calculated cost of products, is 27.8%.  Considering the quantities Big-Event quoted in its offer and the cost-per-unit means a loss of $26K every month. The CFO says that this calculation does not reflect the full picture and the actual loss would be smaller, and it is even possible that the move would lead to minor profit. Still, the concern is significant.  The problem is compounded by the warning of the production manager that those quantities might, from time to time, overload the ovens and the packaging line.

However, being served at all the events managed by Big-Event could have a considerable impact in the market, boosting the reputation of Bake-T products in the high socio-economy market segment. Big-Event would let Bake-T put their labels on the products served during the events.  So, Marketing and Sales are pushing to go ahead with the deal.

Is the decision clear-cut? What additional information is required for the decision?

The basic idea behind cost accounting is that effective cost allocation methods produce a reliable estimation of the cost-per-unit.  Harsh criticism of the too simplistic cost allocation opened the way for the emergence of Activity-Based-Costing, which requires extra efforts to identify all the cost-drivers, their related activities leading to detailed cost calculations, per unit, per client and per deal.

Does the improved information support better decisions?

Let us first check the impact of the following basic assumption behind Activity-Based-Costing:

Every use of capacity costs money!

After all Activity-Based-Costing tries hard to identify every activity and captures its cost. The assumption itself is common in economics and is equivalent to “there are no free lunches”.

Is it always true that every use of capacity generates cost? Let’s examine the following examples:

  1. Using very expensive production-line at night. Assuming overtime of operators is required it definitely generates additional cost, but consuming the capacity of the production-line at night does not add any cost. It may be argued that any usage of the production-line shortens the life of the machines and equipment along the production-line. However, the vast majority of equipment are replaced long before their true end-of-life.
  2. A waiter in a restaurant at off-peak time. A couple comes in and asks for the menu. There are no extra costs due to this request.
  3. The headquarters of a company uses the whole floor in a building. One room is left empty because no one has found a use for it and the company does not want to rent it to others. When someone suggests using it – no additional costs would occur.

What makes it possible to use capacity for free is that in most cases purchasing capacity is done only for a significant minimum amount of capacity!  For instance, employing an operator for 180 hours every month means that if that operator is given work for only 134 hours in a given month, he still gets full salary payment.

Machines, equipment and space in buildings, are purchased in certain capacities. It does not matter whether the buyer uses all the capacity in a specific period or only a very small portion – the cost remains the same. The capacities of very few resources are truly sold per use:  electricity, water and some IT resources.

Some economists and accountants adopt a convenient belief that it is possible to match capacity to demand. In other words, the organization is able to draw work from every employee for the full 180 hours per month, minus the standard time for short breaks. Thus, it is a reasonable managerial target to use every bit of available capacity of every resource. Many employees truly seem to work throughout the 180 hours.  But, if you examine their outcomes it would show very significant fluctuations, meaning in some months their output is considerably lower than in other months.  There is no way to load a resource, human being or a machine, to its limits without creating huge delays in delivery.  However, people know to look busy when they are expected to be busy. It does not mean they could not do more when necessary.

Machines cannot fake being busy and they are able to work 24/7 when you include setup and maintenance.

The need to maintain significant excess capacities on most resources is partially due to having to purchase capacity only in given quantities. There are two additional reasons for the true excess capacity the organization has to maintain.

One is the need to deliver the value to clients in a reliable way.  Delivering value to clients requires synchronization between several resources, which creates dependencies between them.  Every resource is impacted by internal fluctuations, and the combination of dependencies and fluctuations creates bigger negative impact of the fluctuations.  This is a basic theory-of-constraints (TOC) insight.

The other cause for the need to maintain excess capacity comes from the demand behavior. Fluctuations in demand are very frequent, so there is no practical way to match the available capacity to the demand in such fast pace.  Thus, the available capacity has to be big enough to respond to peak demand.  This necessity forces maintaining considerable excess capacity also at off-peaks.

What happens when ONE resource runs out of capacity?

It does not matter how much excess capacity is still available from all the other resources, as long as ONE resource is a bottleneck the market cannot get its full demand and expectations. Such a situation leaves management with three options:

  1. Let the market be grossly dissatisfied. When the organization is a true monopoly and government regulations support such a behavior – this might work.
  2. Reduce the sales of some product/services according to the capacity limitation of that single resource. The difficulty is making sure the intended reduced sales do not cause more damage.
  3. Find ways to increase capacity quickly, using overtime or outsourcing. There are two problems with this option:
  4. It is not always possible.
  5. The cost of the additional capacity is not the same as the relative cost of the available resource. Furthermore, the option to buy more capacity could be also impacted by having to buy a minimum extra amount.

The above analysis reveals the flawed assumption behind all cost accounting methods. The new realization is:

The cost of capacity is not linear!

This means that the cost of producing 100 widgets is not always equal to the cost of producing one unit multiplied by 100.

Note, buying widgets is usually linear. Most of the time buying 100 widgets costs 100 times the price of one.  The exception is getting price reduction for large quantities, but this is relatively a small twist.

However, when it comes to producing widgets, the cost is significantly non-linear.  The cost of capacity of every single resource behaves as a step function and has a limit where increasing the capacity in the short term is impossible.  Some resources come only with huge amount of capacity to start with.  Any increase in their capacity is a significant increase, like purchasing a new production-line.  As long as the existing production-line has enough capacity to cover all the demand, changes in the actual production have limited impact on the cost of capacity.  Going beyond the capacity limit doubles the cost even when the market additional demand is only 25%.  Other resources, like manpower, have many smaller steps.  The total cost of capacity is a step function with many steps that are variable in size.

How should management decide whether to invest in purchasing an additional production line when, at best, the sales would go up by 25%?

Can the decision be based on the margin calculated by the expected selling price minus the cost-per-unit? The cost-per-unit calculation considers not just the cost of the production-line plus materials, but also the capacity cost of every other resource required for producing and selling 25% more sales, whether these resources have excess capacity or not.

Let’s evaluate a simpler and more frequent decision: A potential client looks for 100 widgets every week.  The client is ready to pay $1,000 for the weekly supply, unrelated to the list price that moves between $11.5 and $13.  The practical questions are:

  1. If management accepts the order would the organization make higher net profit?
  2. Are there other positive or negative long-term ramifications?
  3. What is the compound risk of the decision?

The first question is usually the key. It includes checking the possibility of running out of capacity even on one resource.  So, whether the additional 1,000 widgets, on top of the existing demand, would turn even one resource into a bottleneck is a necessary check. The second is required for checking possible long-term ramifications, especially regarding the impact on the future market demand.  The third figures out the impact of uncertainty on both previous questions.

The above three key questions are relevant to all the examples used, including the leading example for Bake-T company.

The most important insight is to have a view of the organization as a system with a set of various resources with a fixed level of available capacity of each resource that is paid for: building space, management resources, equipment and employees.  Maintaining this set of resources and their respective capacity comprise most of the expenses of the organization. Options for fast increase of capacity when needed should be evaluated as well, taking into consideration their actual cost.

Can the current methods and tools of management accounting give a satisfactory answer to the key questions? If the answer is negative then we have to look for another tool to support decisions.

 

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