Why So Many Organisations Fail at Improving their Supply Chain Performance Using Benchmarking?
Owing to the fast paced environment of today, industries are facing tougher challenges due to recurrent financial crisis, more complex and global supply chains, and increasing customer demands. These challenges have forced organisations to look at more effective ways to manage their supply chains.
Needless to say, organisations paying little attention towards improving their supply chain may find it hard to survive in the coming days. The benefits to having an efficient supply chain are diverse: some of them include better responsiveness to demand fluctuations, reduced operational costs, higher order fulfillment rate, increased customer satisfaction etc. However, from an organisation’s perspective, it is not easy to achieve such a state and gain competitive advantage in their industry. As the first step towards achieving supply chain efficiency, companies usually try to compare their own performance versus the competition. And use benchmarking techniques as a means to evaluate their supply chain performance.
With supply chains extending beyond the usual boundaries of direct partners (such as suppliers, distributors etc.) and built in collaboration with various stakeholders such as supplier’s suppliers, customer’s customers or distributor’s logistic partners etc; the management of such heterogeneous supply chains has become much more complex, making the comparison of the performance between two organisations even harder. Further to that, it has become highly difficult (in such scenarios) to identify the issues occurring at different levels and the number of parties affected. Henceforth, it would be interesting to have a look into the different strategies followed by the best-in-class companies to measure and improve their supply chain performance.
Unlike best-in-class companies, most of the organisations are found to have a lack of understanding towards which areas to benchmark and generally end up covering all the supply chain processes and metrics companywide. For example, Compaq in 2007 carried out a supply chain benchmarking study and found them stranded in a similar situation. They were unsure of which areas to benchmark and eventually went on to cover all the supply chain processes implemented across the organisation, which was later found to be a complex exercise and the returns were not as good as expected. Although, they were able to identify the benchmark but it was so wide and covered so many processes that they faced difficulties in prioritising their actions. Given the numerous operational and financial constraints, such an attempt that is targeted towards improving too many processes (at the same time) is time consuming and doesn’t lead to desired performance levels. It is therefore important for organisations to identify the specific key metrics relevant to their business strategy and come up with a prioritised action plan accordingly. Once the key indicators are identified, it will help channelise the efforts in a direction aligned to their own corporate strategy.
Most often, organisations involved in benchmarking tend to look at the aggregated high level metrics which may be hiding some underperforming activities. It is important that the partaking organisations understand the context behind and if these metrics represent the true supply chain performance. To do that, companies are required to drill down and look at level 2 and level 3 parameters and the factors affecting these parameters. For example, an organisation that manufactures two different categories of medical products and accessories, one fast moving medical supplies such as: medicine, band-aids, diapers etc. and the other one represents slow moving medical equipments such as: wheel chair, audio meter etc. In such a case looking at the overall supply chain performance of this organisation may not indicate the true individual performance corresponding to each of the product lines. The aggregated performance may be hiding some underperforming supply chains for one of the two categories. It is therefore required to segment the consolidated supply chain to assess the individual performance of each of the specific supply chains and chalk out a performance improvement plan accordingly.
Organisations can sometimes use sophisticated techniques to benchmark their supply chain but in the process, they usually forget to look at important qualitative factors such as: systems and processes in place, tools used, people skills-set, organisation maturity, etc. that affect their performance. For example, comparing company A and company B just based on the quantitative information is not enough to identify all the possible improvement areas and achieve desired performance levels. It is therefore necessary to understand the difference in their business model, focus of their corporate strategy and the key supply chain elements such as people, processes, practices, type of products etc. while formulating the roadmap towards attaining the targeted performance levels.
In order to carry out a benchmarking study, it is required to have a common framework that facilitates a direct comparison between different organisations. Which is not usually the case, as companies are most of the time using their own definition to calculate metrics. For example, most companies use different formula for measuring their service levels. In an attempt to close this gap, the Supply Chain Council introduced a standard framework called Supply Chain Operations Reference (SCOR) that helps organisations to standardise their supply chain operations and to be compared on the same basis.
Traditional benchmarking techniques are still looked as the go-to-option by the companies trying to benchmark their supply chain. However, these techniques are limited by the fact that only a single metric can be examined at a given time and hence lacking a comprehensive overview of the optimum level of performance that the company can possibly achieve. In simple words, traditional benchmarking makes it look possible to achieve “best-in-class” efficiency for all the possible metrics that may exist on the performance dashboard. However, it is practically impossible for a company to be “best-in-class” on all the supply chain metrics at the same time. For example: one cannot have highest service levels and, at the same time, maintain lowest inventory levels as to match the best in class efficiency. Supply chain professionals are therefore required to note this limitation and analyse all its facets before charting out any performance improvement plan. The traditional benchmarking fails to clearly outline the relationship between the different supply chain metrics.
This very limitation makes it inevitable to ask, “What would be the formula that provides the highest possible attainable performance levels, keeping an account of the relationship which exists between the different metrics”. In other words, how would the formula suggest the positioning of an organisation against a particular performance metric? Considering the various constraints these metrics have to satisfy because of the linkage that exists between them. At first, the very thought of having such a framework might seem to be highly improbable. However, a number of algorithms such as analytical hierarchy process (AHP) and data envelopment analysis (DEA) have been developed, that takes into account the various interdependencies which exist between different performance metrics. These algorithms are becoming more and more popular among the decision makers when the choice of alternatives is influenced by both qualitative and quantitative parameters.
Thus, in order to attain the best possible performance levels, organisations need to revisit the way they have been doing benchmarking. They must look beyond the scope of traditional benchmarking practices and explore methodologies that enable concurrent analysis of both qualitative and quantitative parameters. Such a framework will not only enable organisations to have a clear understanding of their supply chain performance, it will also indicate the starting points to discover the real cause of inefficiencies’ sources and to identify realistic improvements.