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.
Contributed
by: Liezl Smith, Business Six
