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Operational benchmarkes can improve production efficiency and boost overall profits.

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In 2007, Georgia had about 950 licensed growing operations that produced annuals and perennials. After the drought (2003-2007) and the current economic downturn that started in late 2007, 43 percent of those companies went out of business, filed for bankruptcy or closed their doors until better times return. Twenty-five percent of those companies had just come off one of their best years ever (2006).

Truthfully, the drought and recession did not help matters, but clearly what caused these businesses to fold was a lack of cash. Profits had been slim for a few years, sales were slumping and investment in equipment, expansion and labor continued to occur because business owners thought things would get better. Steps weren’t taken to conserve cash. When the banks started asking questions as the 2008 spring loan cycle started, the lending game was over for many growers. The owners had few financial records readily available, they couldn’t show trends or metrics, they were over extended in short-term debt and had very little basis for a loan to be continued.

Understanding where your cash is going is critical to cash flow planning, cash conservation and effecting cash use.


Limited metrics
There are few sources for operational metrics in the green industry. With diversity of operations, using competitive or cross-sectional metrics are likely not going to be as useful as a company’s own historical or internal metrics.

But the metrics have to be developed to use them. Successful benchmarking requires that every employee be assigned the responsibility of providing metrics. The job of the owner or manager is to summarize and evaluate the metrics.


Small changes add up
Large structural or technological changes in any business are difficult. However, even a change of 1 percent can have a major impact on a company.

Table 1 shows a 1 percent increase in production yields a 24.63 percent increase in profit. This is because loss is removed from one side of the equation, with more profit on the other.

A 1 percent increase in labor costs yields a 5.25 percent reduction in profit.


Reducing shrink
One of the achievable areas that any company can track and improve is shrink. Whether this loss is caused by pests or diseases, damaged plants or failure to meet contract specifications, if the plants are simply discarded, growers have nothing to base improvement on.

Are you tracking percentage shrink by crop, by week or by unit manager? The effect of shrink is significant and demands your attention.

A simple benchmark metric is to have employees keep track of how many units of each crop they dump. Assign a reason (disease, damage, no sale, etc.) and then use a spreadsheet with graphics to tally the data. Keep the shrink file as part of the quarterly report. The data can easily tell you whether you have a problem or not. Additional metrics will tell you the source of the problem(s) and you’ll know exactly how much lost profit is sitting in your dump pile.


Production labor metrics
Most growers recognize the loss when they see the dump pile growing at the back of their property. More difficult to see is the loss from inefficient or poorly-trained workers. Looking at common ways workers are used, there are two main types of analysis for measuring employee productivity.


Independent tasks
The Independent task method is fairly easy to determine. Each employee has a distinct task. The output unit, say number of trays transplanted, is assigned to each worker. The supervisor, through a test run, can determine an initial “guesstimate” of what hourly or daily output should be. The actual output is then recorded.

Over time, a realistic company-wide metric is developed for that task and the individual capabilities of each worker are documented. The supervisor keeps track of the output of each employee going forward, and can assess if training allows improvement or if some employees are just not keeping up. Keeping these metrics handy and showing graphics to all the employees on a regular basis can also keep workers focused, since they know their work is being monitored.


In-series metrics
In-series metrics are trickier to measure. Consider a company that runs three packing lines with four members on each line. The unit output should be measured, i.e. the number of boxes packed for each line. However, if one line is doing far fewer than the others, the total daily output data process does not tell the business owner, what step, employee or piece of equipment is not meeting expectations.

Factories since Henry Ford have used piece-rate studies to assess productivity. Our industry rarely does this. A line manager uses a stopwatch to see time how many seconds it takes for one employee to perform a task and then hands it off to a second employee. The line manager should track the first employee for as long as it takes to have a good sample. The manager then tracks the activities of the next employee and so on. By rotating through the lines, the manager can determine the average production time for a unit, which can be used for planning the next time that a task occurs. Knowing where past issues or problems have occurred allows the manager to prepare for them in advance. The manager will be able to anticipate when and where things slow down and what’s causing it. If a manager only counts orders completed, the real worth of the manager is lost.


Make the assessment process work

The assessment process must be someone’s job. An owner cannot effectively do this assessment alone and still manage the business. The collected data is the basis for management decisions. The hard part is obtaining consistent data from employees and graphing the data. Equipment problems may result in a 1 percent decline over a three-week period. A graph with this 1 percent trend will be visually conspicuous.

Over a year, there may be seasonal fluctuations that are not apparent when data is simply reviewed weekly. To make benchmark assessment work, one must acquire data consistently, process that data onto visual graphs/tables and hold assessment meetings with management and workers to discuss potential improvements on a regular basis.


Paul Thomas is professor and extension specialist, University of Georgia, Department of Horticulture, pathomas@uga.edu. Charles Hall is professor and Ellison Chair in International Floriculture, Texas A&M University, Department of Horticultural Sciences, charliehall@tamu.edu.