The document discusses benchmarking, which involves comparing performance metrics to other organizations in order to identify areas for improvement. It outlines the history and definition of benchmarking, as well as different types (e.g. internal vs. external). A typical benchmarking process involves planning, data collection, analysis, implementation, and monitoring. Various tools are used in benchmarking, including balanced scorecards, gap analysis, and data envelopment analysis. While benchmarking provides a way to improve performance, it also faces challenges in securing sponsorship, defining scope and metrics, establishing standards, and deriving meaningful results.

1. Presented by:
A Raj Shravanthi

2. Introduction
• Benchmarking is the process of continuously comparing and
measuring against other organizations - anywhere in the world - to
gain information on philosophies, policies and practices in order to
adapt them to one’s own situation to significantly improve
performance.
• Benchmarking is measuring performance against that of best-in-
class organizations, determining how the best in class achieve those
performance levels and using the information as the basis for goals,
strategies and implementation.
• Benchmarking is the comparative evaluation of technologies,
production processes and products of an organization, compared to
the leading organizations in the same market.
• Improvements of 30%-50% are typical when using the benchmarking
process.

3. Definition
• Benchmarking is the practice of being humble
enough to admit that someone else is better
at something, and being wise enough to learn
how to match them and eve surpass them at it
(APQC, 1992)

4. History
• This technique was originally rooted from Japanese industry
members.
• Benchmarking was made popular by Xerox in 1980s.
• Other significant companies such as Nissan/Infiniti, ICI Fibers,
Texas, American Express, Kodak Rover, AT&T, Chevron and 3M
have also committed to benchmarking and have successfully
used the technique to excel in their respective industries on a
global scale.
• Benchmarking methodology is based on the plan, do, check,
act (PDCA) cycle, also known as Deming cycle, a standard four
phase continuous improvement cycle

5. The core of the current interpretation
of benchmarking is:
• Measurement, of own and the
benchmarking partners’
performance level, both for
comparison and for registering
improvements.
• Comparison, of performance levels,
processes, practices, etc.
• Learning, from the benchmarking
partners to introduce improvements
in your own organization.
• Improvement, which is the ultimate
objective of any benchmarking
study.

6. Benchmarking usually evaluates performance in
the following fields:
– Finance
– Management of Resources and Personnel
– Strategy
– Research and Development
– Production Technology
– Product and Marketing
– Quality and Customer Satisfaction
– Warehouse management
– Supply chain

7. Benchmarking emphasizes attaining so-called breakthrough
improvements, as shown below (Andersen and Pettersen,
1995):

8. Some examples are :
• Long admittance times in hospitals & Hotel
receptions
• Too lengthy setup of machines
• Planning the delivery of fresh concrete or a Hot pizza
delivery
• Unstructured maintenance of power turbines or
Maintenance of aircraft engines
• Difficult to manufacture shell cases with the right
cylindrical shape and smooth surface or
Manufacturing of lipstick tubes

9. Examples of Benchmarking

10. Difference between innovation & benchmarking

11. Benchmarking Types
The major benchmarking types are:
– Performance,
– Financial,
– Functional,
– Strategic, and
– Product benchmarking
Supply chain benchmarks are categorized into two:
– Internal Benchmarking
– External Benchmarking

12. Internal Benchmarking
• Internal benchmarking allows an organization
with more than one facility with the same supply
chain processes to contrast and compare the
ways in which processes are performed in each
facility.
• The benchmarking process can look at a number
of operations that are performed at each facility.
It can then compare how they are performed and
what improvements can be made by evaluating
the benchmarking results.
•

13. six simple steps to start an internal benchmarking process include:
1. Identify the process to benchmark. For example, production,
warehouse management, receiving, shipping, or quality controls.
2. Managers of the process identified in step one agree to a set of
key performance indicators (KPI) such as changeover time ,
receiving time standard deviation, shipping accuracy, average lead
time for quality test, or fill rate. In this step, managers also need to
agree to a standard way to calculate the KPIs to avoid confusion
down the road.
3. Collect the KPIs agreed to in step two and compare the results.
4. Organize a collaborated effort to understand the reason why one
process is better than the other based on the results from step
three. In many cases, a manager from one of the processes will
visit the other process with the goal of discovering a better way to
do things.
5. Prioritize the findings and turn them into improvement projects to
adopting the best practices.
6. Execute the project and realize the results.

14. External Benchmarking
• Unlike internal benchmarking, where benchmarking happens at the tactical
level of the business, external benchmarking is used to compare a company’s
performance at a strategic level.
• In external benchmarking, you can compare the strategic KPIs such as
inventory turnover, revenue, profit, or any other industrial specific KPIs.
• Unlike internal benchmarking, your competitor is unlikely to share their
wisdom on how to improve inventory turnover, reduce total landed cost, or
any other industry specific KPI.
• In this case, the best approach is to employ research and consulting firms to
perform performance studies to know what you are doing wrong (or what the
competitors are doing right). This lets the company identify the areas of
weakness and it can then work at coming up with a plan to improve the
situation.

15. • Another two types of benchmarking include:
– Qualitative
– Quantitative
• In qualitative benchmarking, often called “best
practices” or “leading practices,” managers gather data
on techniques for solving supply chain problems and
improving performance.
• Managers compare their techniques to those of
organizations with similar supply chains.
• The second type is the quantitative benchmarking of
key performance indicators (KPIs), business metrics,
and scorecards.

16. • This activity involves examining a given supply chain
and gathering data on performance, not practices.
• The goal is to identify any performance differences and
note which processes need to be improved and by how
much.
• Companies often conduct this type of quantitative
benchmarking while doing a financial review of
company performance.
• They also frequently use quantitative benchmarking to
tie the company’s supply chain goals to its overall
strategy

17. Procedure
• Data Collection from the corporation
/ organization.
• Entering the data into the Best
Practice database and compiling the
evaluation diagrams.
• Composing the evaluation report
based on results and diagrams from
the database.
• Discussing the evaluation's results
with the corporation / organization
and with experts, in order to explore
new solutions.
• Stating proposals for improvement
and applying innovation methods.

18. (1) Planning:
• For the optimal results of benchmarking to be reaped, the inputs and
outputs need to be re-defined; the activities chosen should be measurable
and thereby easily comparable, and thus the benchmarking metrics needs
to be arrived at.
• Prior to engaging in the benchmarking process, the total process flow
needs to be given due consideration. For instance, improving one core
competency at the detriment to another proves to be of little use.
• Therefore, many choose to document such processes in detail ( process
flow chart), so that omissions and errors are minimized; thus enabling the
company to obtain a clearer idea of its strategic goals, its primary business
processes, customer expectations, and critical success factors.
• An honest appraisal of the company's strengths, weaknesses and problem
areas, would prove to be of immense use when fine-tuning such a process.
• The next step in the planning process would be for the company to choose
an appropriate benchmark against which their performance can be
measured.

19. (2) Collection of Information:
• Primary and secondary data.
• Primary data refers to collection of data directly from the
benchmarked company/companies itself, while secondary data
refers to information garnered from the press, publications or
websites.
• Exploratory research, market research, quantitative research,
informal conversations, interviews and questionnaires, are still,
some of the most popular methods of collecting information.
• When engaging in primary research, the company that is due to
undertake the benchmarking process needs to redefine its data
collection methodology.
• Drafting a questionnaire or a standardized interview format,
carrying out primary research via the telephone, e-mail or in face-
to-face interviews, making on-site observations; and documenting
such data in a systematic manner is vital, if the benchmarking
process is to be a success.

20. (3) Analysis of Data:
• Data analysis, data presentation, results projection,
classifying the performance gaps in processes, and
identifying the root cause that leads to the creation of such
gaps (commonly referred to as enablers), need to be then
carried out.

21. (4) Implementation:
• This is the stage in the benchmarking process, where it
becomes mandatory to walk the talk i.e far-reaching changes
need to be made, so that the performance gap between the
ideal and the actual is narrowed and eliminated wherever
possible.
• A formal action plan that promotes change, should ideally be
formulated keeping the organization's culture in mind, so that
the resistance that usually accompanies change is minimized.
• Ensuring that the management and staff are fully committed to
the process, and that sufficient resources are in place to
facilitate the necessary improvements, would be critical in
making the benchmarking process, a success.

22. (5) Monitoring:
• In order to reap the maximum benefits of the
benchmarking process, a systematic evaluation should be
carried out on a regular basis.
• Assimilating the required information, evaluating the
progress made, re-iterating the impact of the changes and
making any necessary adjustments, are all part of the
monitoring process.

23. Benchmarking wheel Model explained by
Andersen (1995)

24. Tools used in supply chain
benchmarking
• There are two types of measurements – parametric and non-
parametric.
• Parametric analysis = Benchmarking normally used gap
analysis based techniques for performance measurement.
• Some of the popular gap analysis based techniques are the
“spider” or “radar” diagram and the “Z” chart.
• These tools are very graphical in nature.
• Advantages of these tools are the graphical approaches made
them easy to understand and they are capable of showing
multiple dimensions simultaneously.
• However, their disadvantage is it causes inconveniences to the
analysts as analysts have to integrate all the elements into a
complete picture.

25. • Another well-known method used is the ratio.
• It computes the relative efficiencies of the output versus the inputs
and is easily computed.
• However, a problem with comparison via ratios is that different
ratios give a different picture and it is difficult to combine the entire
set of ratios into a single judgement.
• Analytic hierarchy process maturity matrix is another alternative
technique used in benchmarking of performance measurements.
• This technique utilizes a weighted score in the analysis of various
benchmarks and provides a single score using perceptual values set
forth by decision makers.
• This is a multi-attribute utility technique.
• Though, this method helps to quantify measure and provide
managerial input, it is subjugated to high degree of subjectivity.
• Statisticak methods such as regression and descriptive statistics are
also used to analyse data in performance benchmarking.

26. Non- parametric methods:
• one of the commonly used tools in performance measurement is
balanced scorecard (BSC)
• BSC provides a comprehensive framework that translates a
company’s strategic objectives into a coherent set of performance
measures.
• BSC is a management system that can motivate breakthrough
improvements in critical areas such as product, process, customer
and market development.
• The scorecard basically covered four different perspectives from
which to choose measures.
• It complements traditional financial indicators with measures of
performance for customers, internal business/processes and
innovation and learning activities (Kaplan and Norton, 1996).
• In this way, BSC is distinguished by itself by being able to link the
company’s strategic objectives to the long-term trend analysis for
planning and performance evaluation.

27. Balance Scorecards
• Balanced scorecard is a strategic planning and
management system that helps everyone in an
organization to understand the role towards a
shared vision.

28. • Robert Kaplan has proposed the logic of
Balanced Scorecard – Strategic Planning.

29. • Howard Rohm proposed model of balanced
score card for a Federal Government Logistics
Centre

30. • Robert Kaplan also proposed using scorecards in Collaborative Planning,
Forecasting and Replenishment (CPFR) by focusing the Key Performance
Indicators (KPIs)

31. Data envelopment analysis (DEA)
• Another non-parametric tool that is commonly used for
benchmarking is data envelopment analysis (DEA).
• DEA uses the linear programming technique to evaluate the
efficiencies of the analyzed units.
• DEA is able to evaluate the performance measures
quantitatively as well as qualitatively, hence enabling
managers to make reasonable judgement on the efficiency of
the resource usage.
• The concept of efficient frontier analysis suggested by Farrell
(1957) forms the basis of DEA for evaluation of performance
units.
• At such, it takes into consideration the best value that can be
obtained from the set of data and is not based on the average
value.

32. • DEA is a linear-programming-based methodology that can evaluate
multiple inputs and multiple outputs to calculate performance
measure.
• This measure is often in the form of ratio of total weighted output
to total weighted input.
• This weighted generated ratio represents the relative efficiency of
a DMU.
• The objects of DEA are “decision-making units” (DMU).
• A DEA requires the inputs and outputs for each decision-making
units (DMUs) to be specified.
• It will then define efficiency for each DMU as a weighted sum of
outputs divided by a weighted sum of inputs, where all efficiencies
are restricted to lie between 0 and 1.
• In calculating the numerical value for the efficiency of a particular
DMU, the weights are chosen so as to maximize its efficiency,
thereby presenting the DMU in the best possible light.

33. The Challenges of Benchmarking
• Sponsorship—every benchmarking initiative needs a
sponsor, the higher in the organization the better.
• Scope—selecting the supply chains to be benchmarked is
critical; it’s not a simple process.
• Selection of processes and metrics—focusing on strategic
elements helps keep the program targeted and useful (deep
metrics in a few areas rather than many metrics across
numerous areas).
• Standards—standard definitions of supply chain processes
(e.g., what activities are in manufacturing or procurement)
enable “like-for-like” benchmarks across divisions or
companies. Conversely, lack of standards make meaningful
comparisons difficult if not impossible.

34. • Sources—identifying sources of data for metrics and
having clear pointers to which processes generate
transactional data necessary for calculations.
• Cost—benchmarking can be expensive, especially
when outside consultants are used. It’s not uncommon
for the cost of a single benchmark to range between
$300,000 and $500,000.
• Time—the benchmarking process can take from three
to five months; set expectations accordingly.
• Deriving meaning—the benchmarking initiative must
be structured so that the results produced are
meaningful.