Correct (accurate) costing, is one of the most crucial processes for manufacturing companies. It enables them to correctly set a product’s selling price, analyze profit margins, determine the optimal product mix for production, and decide whether to manufacture or purchase certain inventory items. Coming up with the right answers to these questions often determines a company’s success or failure, making accurate costing essential for business.
Correct costing is also the basis for control and monitoring. By measuring the actual cost of each product or work order compared to the expected cost you can immediately identify deviations in production and solve them before they have a major effect on profitability.
One of the most common errors that lead to inaccurate costing is difficulty in measurement. Often, product costing relies entirely on standard estimates for the processes involved, without considering the actual machine downtime, the varying yields of each product and the actual energy consumed to produce it.
Why 80% of Manufacturers are Getting Costing Wrong
Product costing depends primarily on the following two components:
- Direct costs
- Indirect costs
Indirect costs (or overheads), such as rent, are relatively fixed, and therefore, they can be estimated rather easily. Essentially, you know a year in advance how much you’re going to be spending on rent. It’s not going to change unexpectedly. Direct costs, however, have the most impact. These are costs that are not as easy to measure.They include manpower costs, material, energy and machine hours used for each product produced. They can vary greatly, and as manufacturers know, they are affected by unexpected events such as machine failure, variation of yield or a change in the costs of raw materials. Direct costs are difficult to measure accurately due to difficulties in accessing data such as hourly power consumption. As a result, all too often, manufacturers must settle for estimates and hope for the best.
Clearly, manufacturers need greater accuracy in measuring direct costs and making the data available to managers and other decision-makers. To give but a few examples; actual machine hours along with the non-labor costs of each machine’s operation (fuel, repair parts, etc.), labor costs per shift, including overtime, material costs, and scrap. This data must be compiled and presented to management, along with relevant previous estimates so that they can see at a glance if costs are being contained or not.
With the advent of technology driving all of Industry 4.0, the cost of detecting this data via sensors and other devices added to legacy equipment has plummeted, making it possible to gather 100% accurate costing and other KPI data, rather than settling for estimates.
Utilizing data for decision making can be implemented gradually, beginning with specific production lines and expanding onwards.
The Benefits of Real-Time Costing Control
By working at a steady pace, companies will see the benefits of providing accurate costing data to their decision-makers. Detailed costing data, analyzed and presented via drill-down dashboards that support implementing decisions immediately, enables manufacturers to see profitability per product, per customer, per job and to also see product cost vs. selling price.
With this data firmly in hand, decision-makers also gain the following advantages:
- Optimizing supplier and vendor quality assessment, using actual data about the quality and cost to produce with their raw materials
- Make or buy decisions – is it worth it for you to produce a certain part or product yourself, or buy it from an outside supplier?
- Ability to make “turn on a dime” decisions based on the data and changing market conditions
Nowadays, when profits are rigorously scrutinized, it is imperative that business managers not only have all relevant information at their fingertips, but that it can be acted upon, using the same platform that gathers and processes it. The result: a better-functioning and more profitable business in which all employees can replace mundane, error-prone data collecting tasks with more rewarding actions that improve your bottom line.
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