South African Benchmarking Survey


In a fast-paced competitive business environment, it is essential to be able to gauge performance, not only for companies to track their progress over time, but also their relative performance to others in their own environment. Understanding where you are in terms of performance, can set the stage for improvement and developing competitive capabilities.

A study was conducted to determine firstly which performance measures are considered important by South African businesses and secondly if this is an acceptable way to measure performance for benchmarking purposes.

The objective of this project is to construct and test a tool to benchmark performance in the context of the South African supply chain environment. The benefit of determining these differentiating factors will be that clearer direction can be given to companies in terms of supply chain factors to improve their chances of success. This could be used as a guide to companies on a continuous improvement journey.

We can conclude from the literature that if business follows the basic input-process-output construct, the inputs (lead) and outputs (lag) can be benchmarked through specific metrics and the process can be benchmarked through practices. It is also clear that there is no right or wrong answer and that the level of detail and number of methods and metrics is up to the specific party conducting the research. In other words, it can be made as simple or complicated as is desired. All of the methods and measures have advantages and shortcomings, but the challenge is to keep it simple and have a balanced view that gives an accurate assessment of performance, free of bias and manipulation to serve a specific agenda.

The characteristics and features of the ideal performance management system are described by Gomes et al. (2004, p. 523) as inclusiveness, completeness, timeliness, universality, measurability, consistency, integrity, flexibility and ethical.

It was found that certain measures are important to the supply chain community to measure (Research Question 1). Results were obtained for these measures indicating how many companies use them, and how viable they are in a benchmarking study such as this (Research Question 2). A small sample was used for this purpose, but it provided a great testing ground for the viability of future research in this area and the reception of something like this in the market. Some measures were responded well to, and this indicates that they are accepted and widely used. This could also indicate the level of measurement sophistication that the respondents have reached.

Others were not responded well to, and this can indicate that either the company is not aware of the measurement, not skilled at taking the measurement or does not understand the importance of measuring that aspect of supply chain performance. All three of these scenarios present an opportunity for improvement.

Some measures present better value in a benchmarking exercise than others. Only forecast accuracy needs to be reconsidered in terms of how it is measured as it does not mean the same to everyone, and as such does not present good value to a benchmarking exercise. A process of designing those measures was done by a focus group involving seven industry experts, where after a survey was conducted to determine how well used, supported and accepted those measures are.

The research shows a selection of 16 measures that the industry experts consider important to measure resulting from thorough debate. It also includes some segmentation questions that the experts considered important:

 

Position

Measure

Suggested calculation

Information required

Bucket

1

Input

Forecast accuracy

MAPE (Mean Absolute Percentage Error)

Calculated MAPE (Mean Absolute Percentage Error)

Year

2

Output

Inventory value/ turnover percentage

Average inventory value/ turnover X100

Average inventory value, turnover

Year

3

Output

OTIF (On time in full)

Number of Customer Orders Delivered On Time and in Full / The Total Number of Customer Orders x 100 (first customer commit)

Total number of customer orders received, number of customer orders delivered without any mistakes, shortages or late in relation to promise date.

Month

4

Output

Percentage returns

Number of items returned/ number of items sold X100 (finished goods)

Number of items returned, number of items sold

Year

5

Input

Percentage salary bill spent on training

Training spend/ salary bill X100

Training spend, Salary bill

Year

6

Output

Percentage late or back orders/ total orders

Number of Late or back sales orders/ Number of total sales orders X100

Number of late or back orders, total number of orders

Current

7

 Input

Percentage new products in the portfolio (younger than a year)

Number of products younger than a year/ total number of products (finished goods)

Young products, Total number of products in item master

Year

8

Output

Stock turns

Cost of Goods sold/ average inventory value

CoGS, Average inventory value

Year

9

Output

Logistics costs as a percentage of turnover

Outbound Logistics costs/ turnover X100

Logistics cost, turnover

Year

10

Process

Supplier performance – Percentage orders delivered on time

Orders purchase orders received on time in full/ number of purchase orders X100 (initial commitment)

Number or purchase orders placed, number of purchase orders received on time and in full

Year

11

Process

Percentage active products on product master (movement in the last 12 months) SKU

Number of items moved in the last 12 months/ Total number of item number records (finished goods)

Items with transactions against them in the last 12 months, total number of item records

Year

12

Process

Percentage Inventory accuracy at last stock count

Number of stocked products with accurate records/ total number of stocked products (clarify)

Total number of item number records, Last month number of accurate records

Last count

13

Output

Percentage in stock

Number of positive stock values on active items/ number of active items X100 (finished goods)

Number of positive stock values on active items, number of active items

Last count

14

Process

Debtors days

Days for customers to pay

Average days for customers to pay

Actual

15

Process

Percentage local to total sourcing

Local / total sourcing value X100

Value of material sourced locally, value of all material sourced

Actual

16

Process

Creditors days

Days to pay suppliers

Average days to pay suppliers

Actual

These form the basis of a better scorecard to measure supply chain performance, from the three perspectives of input, output and process. This will enable businesses to gauge their performance in relation to their competitors comparing the same indicators. 

For the tool that uses the agreed calculations, please download the spreadsheet from www.scbenchmarking.com . Also from this site, the national survey can be accessed where the results of the Excel calculations can be entered.

Liezl Smith.PNG

Contributed by: Liezl Smith, Business Six