Published 28. Nov. 2016
Five Supply Chain Myths, Busted
Supply chain performance gaps in manufacturing companies are not so much driven by supply chain execution, but by leadership thinking about process performance. There are a lot of supply chain myths that prevent companies from moving forward with a better supply chain strategy and more effective execution, but here are five of the most prevalent.
Myth #1: Our Supply Chain Strategy is Part of Our Overall Business Strategy
In 2013, less than half of respondents believed that their companies value the supply chain as a strategic asset and a part of the overall strategy. Here are the key reasons why supply chain strategies are either not integrated or not available:
- Boardroom executives’ insufficient recognition of the importance of the supply chain.
- No strategy, no sense of urgency. Two-thirds of all companies still focus on the basics of running a supply chain because it still works.
- Seemingly insurmountable collaboration challenges within the supply chain and across all functions.
- Supply chain executives’ non-involvement in managing the end-to-end supply chain.
Myth #2: Our Supply Chain is Truly Customer-Focused
In over 70% of R&G’s client base, the delivery date requested by the customer was not available in their systems or had been overwritten by a promised delivery date. Delivery date is one of supply chain’s basics, and if a company fails to take into account this very important customer service tenet, then they can’t possibly claim to be customer-focused. Companyies whose overall strategy is all about supply chain productivity must take to heart the value that understanding the needs of customers can create.
Myth #3: We Fully Understand Our Own Supply Chain
If a company fails to take basic customer request like the delivery date into account, then it also can’t claim full understanding of their supply chain. It may not be possible to have detailed knowledge of all operational issues on a daily basis, however, a 4% awareness of key issues combined with an on-time delivery KPI that suggest everything is fine, may well lead companies to falsely assume that their supply chain basics are in order. So, why are supply chains failing? Here are three reasons:
- Promised delivery dates are typically based on lead-time thinking.
- Most companies measure their on-time delivery performance as a percentage (of orders delivered on-time versus all orders delivered).
- The metric used has no true diagnostic quality.
Myth #4: We Cannot Make the Next Performance Step Without Technology
Sooner or later companies will have to consider investing in new technology. The question is do they need to make the decision now? If their processes are neither stable nor predictable, getting a quick return on investment in new technologies is a considerable challenge. Unsolved process issues are likely to prevent the new technology from performing as expected. To be able to generate the expected ROI, new technologies need stable processes. If a company has not evaluated its current processes and has never met its process targets, then it shouldn’t assume that it will do so with the new technology. Understanding the root causes of supply chain instability will help in identifying the next steps and investments.
Myth #5: We Have All the Skills We Need to Manage the Required Supply Chain Changes
Assuming a team has the right set of basic skills, the following capabilities can be acquired through training. Alternatively, the composition of the leadership team can be altered to acquire the right set of capabilities:
- Cross-Functional Decision-Making Capabilities. Studies reveal that 70% of management teams are ineffective. And since supply chains engage all company functions, the probability that a company will achieve alignment in supply chain strategy is low.
- Process Capabilities. Overseeing all activities isn’t a one man job. To understand what is going on, access to transactional data is imperative. Process capability is the ability to tap into information processes and generate relevant data.
- Data analysis capabilities. Big data analysis will help provide insights into the underlying structures that explain the current performance level. This refers to the full spectrum of validating data, creating cross-functional datasets, statistical data capabilities, the interpretation of insights and the presentation of relevant information and conclusions.