Demonstrating Value with Benchmarking
How can the service offering that creates the highest value to the customer be identified? How can industry-wide experience-based data and knowledge be exploited to provide, and continuously improve asset management services.
Manufacturing, mining and process industry companies around the world are looking for comprehensive solutions to raise and keep the overall equipment efficiency (OEE) at a high level. From the service provider’s point of view, this demand requires a deep understanding of the customer´s operation and maintenance processes, and of the various aspects affecting the business. In a global operation, service sites are seldom comparable: the installed base (fleet), environmental conditions, maintenance practices and processed raw materials can vary significantly - among other issues. Service companies focus on providing the customers with highest value services to improve their asset performance. Customer value is, however, case-specific. The solutions provided to one customer might not be as valuable to the next one due to e.g. customer-specific competences or external constraints.
Benchmarking is a widely-used method that allows a company to compare its own practices and processes to the practices applied in the best firms of the industrial branch. A typical objective is to find justified development targets - and to benefit from existing good practices in the industry. Service providers could exploit benchmarking approaches together with their customers when looking for development needs in the asset management practices. Among many problems concerning benchmarking, one challenge is to make companies, plants or production lines and service site comparable.
Benchmarking is not a single method
The commonly applied benchmarking procedure has been the comparison of the average values of the particular industrial sector with the company’s own values (Komonen et. al 2011). In practice, benchmarking approaches make use of a variety of qualitative or quantitative methods. Qualitative methods are able to provide detailed and insightful benchmarking information if the number of involved companies is modest. Quantitative methods, in turn, provide a more efficient way to collect and analyze large data sets producing benchmarking information from a large number of companies. The benchmarking method and tool presented in this article is quantitative and requires data from several companies.
Service provider can utilize benchmarking to develop customer service
The benchmarking tool helps to identify and visualize potential sources of value. The benchmarking method promotes service providers’ ability to recognize improvement potential in customer’s asset management practices and the ability to find improvement actions for the current situation. The method for demonstrating value with benchmarking (Valkokari et. al. 2016) was developed in co-operation with Outotec that provides asset management services to the mining industry. The developed benchmarking approach is generic and applicable to other industries.
The quality and plausibility of the data analysis results depends always on the quality of used data. Benchmarking methods make no exception. Benchmarking is typically used by an organisation that wants to compare own level of productivity or OEE, or some other key performance indicators with other companies in the same industry. If a service provider carries out the benchmarking, the potential customer may question the result due to possible commercial interests. Thus, transparency of the data collection and the data analysis is crucial for the credibility of the results. To make benchmarking transparent, the service provider and the customer should carry out the data collection and analysis in close cooperation. The common effort also provides a well-structured opportunity to discuss aspects related to e.g. the maintenance function and its successfulness.
Benchmark among similar companies
In quantitative benchmarking methods, the basic assumption is that the companies are similar enough to be compared if they operate in the same industrial branch. In real life, the diversity of the companies can be extensive and poses a major drawback. If the benchmarked companies differ too much from each other, the benchmarked company is barely able to find the right development targets or even recognize the companies that should be a valid reference group. With the proposed approach based on categorizing sites to comparable units and benchmarking them against each other, the best practices will depend on the business environment. Thus, the first step is to recognize similar kinds of companies that can best learn from each other.
In this context, similarity means that companies are comparable according to the aspects affecting asset performance and asset management practices. As the focus is in the development of maintenance service offerings, the benchmarking method categorizes sites or plants according to their maintenance environment. ”A maintenance environment” collects together the data arising from those sites that are similar enough with respect to external aspects affecting maintenance activities as illustrated in Figure 3. Maintenance environments describe features that affect the requirements for the maintenance function and include maintenance policy and maintenance activities. Features describing a maintenance environment include for example: availability of competent employees, climate effect on maintenance conduction, life cycle phase of equipment, maintainability of equipment, etc. From a service provider’s point of view these aspects are external and cannot be controlled by a service provider.
The benchmarking method requires a quantitative data set that contains variables about the maintenance environment, applied maintenance practices and level of success. CMMS or other databases seldom contain such statistical data that is relevant from the benchmarking point of view. Thus, part of the method development was to establish a questionnaire for the data collection.
The questionnaire includes 34 questions that help to categorize the sites to different maintenance environments, recognize maintenance practices and calculate a key performance indicator to assess the successfulness of a site (see Figure 1). The service provider carries out the data collection in normal business negotiation situations. For this reason, the length of the questionnaire has to be reasonable and the questions should be easy to answer. The number of the questions is as small as possible and whenever possible the questionnaire offers ready alternatives. Pre-defined answer alternatives also support automated data analysis that allow discussion about results immediately after entering the data items.
Developing targets based on benchmarking
Benchmarking is a tool to find out potentially weak points in the operation and offers an input for detailed discussion, and planning and prioritizing for development actions. In the developed benchmarking method a site under study is, based on the questionnaire entries, categorized to one of the pre-defined maintenance environments according to its similarity index value. The similarity index indicates the closeness of the site’s answers to the profile of a pre-defined environment. As illustrated in Figure 2, all sites belonging to the same maintenance environment are extracted from the benchmarking database for further analysis. The best sites of a particular maintenance environment are defined according to the values of key performance indicators, like availability or maintenance cost divided by equipment replacement value. Comparing maintenance practices between the benchmarked site and the best sites points out the differences in maintenance practices applied in operation and management. Investigating reasons and effects of these differences can reveal targets for development actions of the benchmarked site.
Benefits from a service provider point of view
Outotec Service Business Development is a function that has been actively looking for new ways of providing value to the customer. By developing the benchmarking concept in cooperation with different departments within the company as well as with certain customer sites, the development team has been able to structure the data gathering process. Moreover, it is able to better utilize installed base knowledge as well as understanding about the potential value sources for the customer, on a very concrete level. The benchmarking tool presented in Figure 3 can be used as a sales tool for the services business for an entire site or for sub-processes or process islands. It allows a value-based sales process, and more specifically, the matching of Outotec’s service offering against the customer’s actual needs, as defined on a detailed site assessment. It allows a transparent sales process, which can be defined in close cooperation with the customer. Outotec will be able to use the tool and its results also in internal product development, since it will become more aware of the customers’ key challenges. Addressing the service product portfolio accordingly will give Outotec insight to what type of services the customers value the most.
There is a need for a systematic assessment framework for concretizing value, benchmarking it and ultimately optimizing the offered service solutions. The benchmarking method and tool helps to compare different sites according to their operational and maintenance environments. The benchmarking tool helps to identify and visualize the potential sources of value.With this approach based on categorizing sites to comparable units and benchmarking them against each other, the service provider is able to improve its capability in:
- Showing improvement potential in asset management and make recommendations of applicable asset management policies,
- Facilitating sales by optimizing the customer-specific product and service offering, and
- Concretising customer value of the service provision.
Komonen, Kari; Kunttu, Susanna; Ahonen, Toni (2011). In search of the Best Practices in Maintenance - New Methods and Research Results. Handbook 1st International Maintworld Congress. Helsinki, 22-23.3.2011. KP-media Oy. Helsinki 2011, pp. 166-177.
Valkokari, Pasi; Ahonen, Toni; Kunttu, Susanna; Horn, Susanna (2016). Fleet service solutions for optimal impact (in Finnish). Promaint – kunnossapidon erikoislehti. Kunnossapitoyhdistys Promaint ry, 30(1), pp. 36-39.
A growing number of companies want to use big data analytics in their predictive maintenance and are also investing in the resources needed for this. Of the companies already using this technology, no less than 95 percent say that they have already achieved concrete results. This is the conclusion of a follow-up study conducted by PwC and Mainnovation among 268 companies in the Netherlands, Germany and Belgium.
In today’s operating and production environments, systems and equipment must routinely perform at levels that were not possible a decade ago and which were unthinkable thirty years ago. Requirements for increased availability, throughput, product quality, agility, and operating effectiveness within a rapidly-changing demand environment continue to elevate the tempo and intensity of operations.