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Robustness
Especially in supply chains where many different partners are working together
or for organisations with several business units, plants or country organisations, it is
important that the performance element is defined and measured in the same way in the
whole organisation and even across organisations. With this “robustness” criterion the
performance element can be applied in different situations, and it is possible to compare
different units or organisations. In this sense, ratio-based criteria are often preferred to
absolute numbers [10].
The fulfilment of this criterion often depends very much on the business. The
lead time for goods reception (or cost per pallet/container in goods reception) is only a
robust indicator if the focal business used the same loading equipment (e.g. grid boxes)
or if at least the mix of loading equipment was equal. Even indicators such as delivery
reliability could hardly be seen as a robust indicator when the company at hand has a
very diverse product portfolio (e.g. power plants and small electronic devices). Another
possible hurdle for the robustness of delivery reliability as an indicator is whether it is
calculated on the basis of the orders or the order lines.
When evaluating the robustness of each performance element, a trade-off has to
be made between only using performance elements that can be used in all units and
using very business-specific elements that can only be used for one specific unit.
Availability of information
An obvious criterion is that the information to calculate the performance element
should be available. This aims not only at making the measuring process as efficient as
possible (see Figure 3.5) but already on the level of each indicator it has to be ensured that
the indicators are based to a high degree on information that is available in information
systems or that could easily be observed and gathered manually or automatically [3].
Automated information gathering is mostly the case for information that is
available from IT-systems such as the delivery reliability of suppliers. If personal interviews
have to be conducted to gather important information – as it might be the case for the
information on employee or customer satisfaction – the information is not easily available.
This criterion must be seen in combination with the economy of the whole PMMS. On
the one hand, important information has to be gathered despite poor availability but
on the other hand not every available piece of information should be recorded. This is
to avoid a “data graveyard”.
Relatively new developments that have a high impact on this criterion are the
developments with regard to the internet of things and big data. This means that by having
sensor technologies widely available and possibilities to track and share information over
the internet, the automated gathering of data has become easier and more information
is available. Based on this, the generation of meta-data and the use of them for decision
making is a more crucial issue. For example, the detection of fraud in purchasing or
possible supply chain risks have become possible with big data analytics [24].
Controllability
This guideline represents the claim that performance elements should measure
factors that can be controlled [52]. This criterion, often stated in literature, focuses on