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Benchmark with the best: Selecting the right benchmarking partners

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Benchmarking

One of the keys to success in benchmarking is connected to selecting the right benchmarking partners and learning from the best in class organizations. However, the process required in the selection phase is a very complex one which needs to have the proper time and resources allocated.

Benchmarking represents a very structured process that should follow several steps. The process generally focuses on how an organization can achieve a valuable learning experience and incorporate the best practice within its own processes. According to Watson (1993), before conducting the benchmarking process, one must answer four key questions:
  1. What should we benchmark?
  2. Whom should we benchmark?
  3. How do we upgrade the performance of this process?
  4. How do they upgrade the performance of this process?
Literature has shown that one of the methods of selecting the best benchmarking partners is based on the analytical hierarchy process (AHP principle).

According to Spendolini (1992), benchmarking partners can be divided into four main categories, from the lowest hierarchical level to the highest one. These partner categories are:

  • Equal or lower than current performance;
  • Improvement compared to current performance;
  • Best practices;
  • Best in class.

Regarding the last two partners’ values, best practices refer to the level of excellence for products, services, or processes performance, whereas ‘best in class’, which also has a synonym named “best of breed”, refers to excellent performance in a certain field within a specific industry.

As the selection is a complex stage of the study, and includes also attributes that look at technical issues or even cultural aspects in order to be able to ensure the success of the study, specialists in the field recommend the usage of multi-attribute decision-making tools.

The multi-attribute decision-making follows a simple approach, composed out of three main steps: clarification of the problem, identification of objectives and measurement of effectiveness.

When a company seeks to identify top performant benchmarking partners, or best in class partners, it is very important to establish a list of possible benchmarking partners for an initial co-operative benchmarking.

It is a certainty that some of these possible or potential partners will be eventually eliminated from the list, for various reasons, like: lack of interest and time, or unwillingness to share their organization’s information.

However, In order to obtain the initial list of potential benchmarking partners, an organization can have different approaches and look at different sources, like: award winning organizations, newspaper and magazine articles related to the area of interest, journal articles, conference speakers, industry and professional associations, books on best practice companies, consultants in a specific industry, and others. Moreover, some of the potential partners will be eliminated if there is no sufficient public data available from their company.

For this matter, specialists have developed various approaches based on multi-attribute decision-making, in order to support the selection process:

  • Alternatives to alternatives scorecard. A scorecard represents a matrix where alternatives (candidates for benchmarking, in our case) are displayed in the first row and attributes (or criteria) are shown in the first column. The outcomes of each candidate are described by numbers that vary from 0.00 to 10.0. The best alternative for each attribute is highlighted with symbols or colors. However, the main disadvantage of this technique is that it does not take the attributes’ weight into consideration, hence, it should be better used in the initial phase of narrowing the candidates’ list.
  • Ranking the alternatives. By using this technique, potential partners can be compared in pairs, against each different attribute, and decide after which of them is more advanced. The preferred candidate receives one full score, and if both candidates are equal, they are both given half point. The final results are graphically represented. The main disadvantage of this technique is that it does not include any prioritization of the attributes and it can somehow be subjective.
  • Polar graphs. This is probably the most popular method among benchmarking specialists, and it is based on a graphical representation, with a rating scale ranging from 0.0 to 10.0 for different attributes. Through graphic connections, different polygons are created to present the potential partners. The candidate that provides a web covering the larger domain is considered to be the best benchmarking partner. The main advantages of this technique include visual representation and ease of decision-making, but it is not very effective when dealing with more than four candidates.

As the main purpose for conducting a benchmarking study is to learn best practices from top performing organizations, and further implement them for improving own processes, the identification and selection process of the ideal benchmarking partners is a critical factor for the success of the study.

References

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