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Business Insights from Andrea Hill

There is no magically easy way to manage costing - it is a demanding task that requires intelligence and discipline. But if you manage costing effectively, you will find profits increasing within a year as you refine your production, merchandising, pricing, and marketing strategies based on the insights you gain.

Easy Miracle Cure for Production Cost Management! Not.

27 October 2010


Software & Service Links

The links below are for services offered by Andrea Hill's companies (StrategyWerx, Werx.Marketing, MentorWerx, ProsperWerx), or for affiliate offers for which we may receive a commission or goods for referrals. We only offer recommendations for programs and services we truly believe in at the Werx Brands. If we're recommending it, we're using it.

The first time I struck out on my own, in the 1980s, I was completely unprepared for the realities of budgets and financial management.  I earned a fair amount of money for someone so young, but it never failed - I always reached the end of one paycheck before I received the next. I  did not treat myself to expensive things but I had no idea how much things cost, so I was constantly underestimating how much money I needed and running out when I needed it.

It may seem surprising, but small manufacturing business owners often do not know how much it costs to produce their products.  Not knowing how much things cost, they are left with disappointing results at the end of each accounting period and in need of cash to finance upcoming projects. The two biggest costs most companies incur are the costs of production and the costs of labor, so lack of clarity and control in these areas can be devastating.

The key to knowing product costs is to use a sound costing method. There is no magically easy way to manage costing - it is a demanding task that requires intelligence and discipline. But if you manage costing effectively, you will find profits increasing within a year as you refine your production, merchandising, pricing, and marketing strategies based on the insights you gain.

Your goal in costing is to understand both the overall profit of the company and also the individual profitability of items. As a business manager you must do bottom up and top down analysis at all times. In this case, the top down (macro) analysis is the overall corporate profitability, and the bottom up (micro) analysis is the performance of individual items. Imagine for a moment that you are experiencing a 1% decline in your profit margin. How do you begin to understand what is causing it? If you only understand your profit margin at a macro level, you will not have the insight you need to tweak profit margin at the micro level.

The simplest way to set product costs is to average overhead and salaries by adding them together and then dividing to come up with a production-cost-per-minute. You then multiply this cost by the amount of time required to produce a particular item. This is a fairly common approach, particularly for companies new to manufacturing, but it is fraught with risk. This approach will only work if:

  1. All the people in your production environment have the same skills and productivity
  2. All the people in your production environment are paid the same amount of money (now and in the future)
  3. You are not doing any process batching that can be performed by lower-salaried laborers

If all three of the above conditions exist, then presumably each minute of production time for each product is worth the same thing. In that case, a production labor rate that is averaged across all production workers will work for you.

If, on the other hand, you have variability in pay, skill, and type of process, you must approach costing in a more sophisticated manner. The approach I am about to describe is a derivative of Activity Based Costing (ABC). It's important to note that it's a derivative, because if you study ABC you will discover a nearly molecular approach to costing that is time consuming and suffers badly from point-of-diminishing-returns. This derivative approach takes into account variability in skills, pay, and tasks without the expensive granularity.

Let's use a jewelry example to illustrate. Imagine that you are making two rings, both of 18k gold, both requiring setting three stones. But Ring #1 involves very careful finishing to preserve detail in the band, and it requires channel setting. Ring #2 has a simple band and does not require special attention in the finishing step, and the stones are prong-set. Does Ring #1 take longer to make than Ring #2? Obviously. But what isn't so obvious if labor costs are being averaged and divided by the minute is that Ring #1 may require a $70,000/year production worker for 90% of its minutes, and Ring #2 may require a $35,000/year production worker for 100% of its minutes. In this case the averaging of production time over minutes no longer works, because it understates the cost of Ring #1 and overstates the costs of Ring #2.

The way to manage costing in this environment is to benchmark and test. The benchmark is set at the beginning of production for a given item. Not the first time it's made or even the second - those production times will always be longer and are likely set by a much higher paid person proving the production approach for a new design. You will keep careful track of the total (not elapsed) time of production for new items, and up to the point that an item is released for actual production, you can allocate those times to R&D rather than cost of goods. Do you have to do that? Not necessarily. Companies that are doing a lot of new production that is very similar to previous production may opt not to do that just because they have standardized and minimized the amount of time spent proving a new item. But companies that spend a lot of time in the pre-release-for-production phase may want to consider this.

Once the item is released for production, a cost estimate (based on pre-production activities) is set in the system for the first run. You will likely run slow on the first production run, but you need a cost in the system. Then, on the second run of the new item, you carefully benchmark the time spent  - the time spent in production and the cost of labor for the various steps of the process. That becomes the standard cost for the item. After this, you don't measure each time you run the item (this is where the departure from ABC comes in - ABC would require careful measurement every time. But the time spent doing this costs more than its ultimate value in knowledge). Rather, you set each item to be re-benchmarked on a 2X or 1X annual basis. When you run the re-benchmark, you will typically find some improvement in the production time, but sometimes you will discover drift in process, shift upward in salaries, or shifting of labor types, and these changes will either be reflected in the new cost of the item or will give you the opportunity to correct undesirable drifts and shifts. The only time you should have to analyze items off their typical 1X - 2X/year schedule is if something major occurs, such as when an urban manufacturing  company's entire production group fled to a competitor and he had to start from scratch with new employees.

The downside of this approach is that it requires careful management of costs. When you are benchmarking a new item, you need to consider the averaged salaries of the type of potential labor at each step, you must remember to schedule each item for periodic review, and you must remember to do the scheduled reviews. The other downside is that it is not perfect, but neither is averaging all salaries across minutes. The only near-perfect approach is ABC, and like I said, that involves so much extra work that the knowledge gained isn't important enough to justify the cost of gaining it.

The upside of this approach is that it gives you excellent visibility to the actual productivity of your line. When you are trying to solve a problem, you can drill down into items and groups of items and see where your profitability is slipping. You may realize that you want to raise the price on just one category or subcategory of products, or that you can modify the design of an item or small group of items to reduce the cost, or that you can afford to hire a few more $35k/year employees and shift tasks into batches, or (the list goes on). Using this approach, small manufacturers gain insight into very interesting things. Some of the things my clients have been able to see using this approach include:

  1. One client found that customers had a distinct preference for the more complex items in his line. The more complex items weren't always obvious from the price point, but they were obvious in the costing. So he selectively raised prices on the complex items to increase margin, because the lower margin of those items - plus their comparatively higher volume - was having a disproportionate negative effect on profitability.
  2. One client needed to reduce her price points but had to be very careful how she did it because she had just started seeing the profitability she needed and didn't want to reverse it. By analyzing costs, she saw that she had the opportunity to put her lowest price production workers on a whole category of items that enjoyed good sales. She reduced those product costs and selling prices proportionately - thereby maintaining the overall margin (though not the dollars, of course), and was able to promote this new lower-priced line to counter the competitive pressure she was feeling.

These are just two examples, but they illustrate the type of knowledge this approach can bring. I rarely see conditions (no variability) that would make averaging all production salaries the most prudent approach to costing. The benchmark and test approach is the one I prefer, because even though it requires more work to accomplish, it is one of the most important functions of business. The resulting knowledge will help you manage not only the pricing of your line, but also generate better design and development ideas for future products and the evolution of the company.

(c) 2010. Andrea M. Hill