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Keith Dunn: Chapter 8.2: Performance Analysis (Continued)
Posted On: 18-05-2009 09:30:11 AM

8.2 BENCHMARKING PERFORMANCE

Most performance metrics need to be benchmarked to determine what is acceptable and what is not in the current trading conditions. The benchmark represents the average aspirational performance as opposed to the average actual performance. Performance improvements are then achieved by either discontinuing or refining anything that performs significantly below the benchmark.

Benchmarks can be set for any metric but are most commonly used for the main performance ratios such as Full Price Sell Through %, Rate of Sale or Stock Cover. They can be set independently for any hierarchy member – you could for instance have a different benchmark Rate of Sale for two sub-departments belonging to the same department. Benchmarks will also change over time in response to performance trends, although they shouldn’t, ideally, become worse.

Benchmarking is not strictly scientific and is only used internally. While you can calculate a benchmark, therefore, as is shown in the example that follows, you don’t have to and can simply set it however you want.


EXAMPLE 1

We want to benchmark Full Price Sell Through % for the Men’s Plain Shirts sub-department.

If we look at overall performance for the area the average Full Price Sell Through is 82.1%. Within this performance are two options (highlighted in bold italics) which we have decided are exceptionally good or bad.


PLAIN SHIRTS LINE PERFORMANCE REPORT FULL PRICE SALES TOTAL BUY FULL PRICE SELL THROUGH %
TOTAL 68,584 83,525 82.1%
Basic B/D Collar S/S 22,550 28,750 78.4%
Basic B/D Collar L/S 21,684 23,900 90.7%
Poly-cotton Flap Pocket 10,550 12,450 84.7%
Dobby Front Plaquet 8,000 10,000 80.0%
Twin Stitch Detail 3,500 4,550 76.9%
Linen Flap Pocket 2,300 3,875 59.4%


To benchmark Full Price Sell Through % all we need to do is remove these two options and recalculate the average, giving us a benchmark of 80%. We will now use this as the basis for comparison of current performance and as a guideline for setting plans.


PLAIN SHIRTS LINE PERFORMANCE REPORT FULL PRICE SALES TOTAL BUY FULL PRICE SELL THROUGH %
Basic B/D Collar S/S 22,550 28,750 78.4%
Poly-cotton Flap Pocket 10,550 12,450 84.7%
Dobby Front Plaquet 8,000 10,000 80.0%
Twin Stitch Detail 3,500 4,550 76.9%
BENCHMARK TOTAL 44,600 55,750 80.0%


EXAMPLE 2
In some cases the average actual performance is an acceptable benchmark. In this example we are looking at the option performance for a specific product.


BASIC B/D COLLAR SHIRT OPTION PERFORMANCE REPORT FULL PRICE SALES UNITS TOTAL BUY FULL PRICE SELL THRU %
TOTAL 17,679 22,550 78.4%
White 3,828 4,400 87.0%
Light Blue 3,655 4,250 86.0%
Peach 1,371 2,100 65.3%
Moss 1,248 2,400 52.0%



Moss and Peach are significantly poorer than the other colours. To establish if this is a colour problem or if it has been caused by other factors we need to look at the colour attribute performance for all Plain Shirts, which shows the average for all products with that attribute.

PLAIN SHIRTS COLOUR PERFORMANCE REPORT FULL PRICE SALES UNITS TOTAL BUY FULL PRICE SELL THRU %
TOTAL 178,525 225,000 79.3%
White 85,000 100,000 85.0%
Light Blue 42,500 50,000 85.0%
Peach 37,200 50,000 74.4%
Moss 13,825 25,000 55.3%



We can see from this report that while the Peach colour is not a problem overall, Moss is. The Peach Button Down Collar shirt, therefore, should be performing better than it is and we would need to look for other reasons, such as quality or shading problems, to explain the poor performance.

 
 
 

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