The main goal of quality improvement is improved profitability. Greater quality reduces manufacturing costs due to lower scrap levels, less rework and reduced raw material costs. It also increases customer satisfaction because of the quality level itself and faster deliveries, thereby increasing demand for the company’s products. For these reasons, high quality can provide a competitive advantage. Look at an approach that allows manufacturers to focus quality initiatives where they may make the biggest impact on profitability.
Maximizing profitability is the number one goal of manufacturers. However, most manufacturers do not succeed in achieving maximized profits. Why? First, they often do not have complete visibility into profitability at a granular level-by product, customer, market, sales region, plant or production line. This is often because of the presence of multiple systems, a gap between enterprise resource planning (ERP) and manufacturing execution systems (MES) and no central repository for aggregated data.
Aggregating the right information is the first step in profit improvement. Aggregating all information including transaction and cost data residing in ERP systems and product run rates from production systems, such as MES, provides three key benefits: creating a single source of record for the company’s operating data, making it possible to view the data at a detailed level and providing a “profit velocity” view of profitability.
The three tables in figure 1 show the ability to view profitability by different dimensions or even by combinations of them. Profitability can be seen by individual product, by market or by machine, for example, production line or plant. This capability is made possible by pulling all data into one central system, but also by doing this at a detailed level. Combinations of dimensions are possible, such as the profitability of product A made for market B in plant C.
Production SpeedProduction speed is a critical component of the profitability equation. The second major benefit of combining all data in a central repository comes from the inclusion of production run-rate information. By incorporating production speeds with margin, a new metric-profit per minute-can be generated. Because overall corporate profitability is measured over the course of a time period, typically a year, it makes sense to look at profitability at a detailed level also by profit per unit of time, for example, profit per minute.
The topographical map of figure 2 shows how high-margin/low units-per-minute products can generate cash more slowly than lower-margin/higher units-per-minute products. The products in the lower right of the chart may be under consideration for elimination when, in actual fact, they are far more profitable than the high-margin products in the upper left. When margin only is used as a metric for profitability, decisions such as where to spend sales and marketing dollars to increase demand may be spent on the wrong products. While these misguided efforts may increase profitability somewhat for the manufacturer, they will not maximize it.
Greater ProfitsModeling possible changes helps tie quality initiatives to greater profits. Even if they have a central repository for data, most manufacturers are unable to view their data from a profit-per-minute perspective. Furthermore, they are unable to do any forward modeling to see what the impact on profitability may be for making various operational changes.
When company-wide data is assembled in one central repository and when the data can be evaluated using a profit-per-minute metric, adding modeling capability supports decision-making for quality improvement efforts. Figure 3 shows four discrete products, the price of each and various costs associated with them, as well as profit, margin and cash contribution per minute. The products are sorted in descending order by cash contribution per minute, analogous to profit per minute. It is important to note that cash per minute does not correlate with margin as discussed earlier. The fourth product has a higher margin but much lower cash per minute than the third product.
After a product has been identified for a quality improvement initiative, it is even more helpful to be able to evaluate the impact of any potential improvement. The figure 4 table shows modeling of a decrease for the scrap rate of the product in question from $206 to $200 per unit.
The $6 per unit decrease in scrap rate for the worst scrap-rate product increased cash contribution almost $200,000. It also increased average cash contribution per minute by $14.35 and return on assets by 1.2%.
Scrap rate was used as an example in this case to demonstrate the power of being able to model potential improvements which impact quality. However, any cost element that is known at a product level can be modeled to determine the impact of a change on profitability. These cost elements could include rework, customer returns or divert quantities-products sold at a low price because they do not meet required quality levels.
Quality improvement initiatives can, therefore, be identified and prioritized by taking an approach that will help maximize overall corporate profitability: get company-wide data into a central repository; make sure that the data includes production speeds as well as margin information; use a system that combines the margin and production speed data to yield a profit-per-minute metric that measures profitability at a granular level; identify opportunities for quality improvements; and model the impact of potential changes in quality-related costs.
Such an approach will focus quality initiatives where they can make the most impact on corporate profitability.Q
Tech TipsAggregating the right information is the first step in profit improvement. It provides three key benefits:
- Creating a single source of record for the company’s operating data.
- Making it possible to view the data at a detailed level.
- Providing a “profit velocity” view of profitability.