Whether a global giant or an SME, the effectiveness and agility of your supply chain can have significant effects on business performance. Keeping tabs on your suppliers is the only way to control the impact they have on your business, and analytics are a key player in that. As supply chains evolve to become more slick, so the network analytics tools employed need to grow too. Recent shifts in supply chain management theory suggest the need to challenge accepted analytical approaches.
A Good Supply Chain
Efficient supply chains maintain visible connectivity across multiple supplier tiers. This ensures information flows relevant to changes in demand or supply can be quickly incorporated and managed. Collaboration between OEMs and suppliers ensure a connectivity in the ongoing production life cycle of a product.
The open sharing and discussion of key performance indicators, coupled with the integration of industry benchmarks, combine to offer the best visibility and flexibility across the supply chain. In this way, risk reduction and continual improvement can be sought and achieved.
Traditional Performance Measures
So where do analytics fit into this model of uber-effectiveness? Traditional supplier analytics have tended to concentrate on the operational aspects of supplier performance. Focus on trends in delivery rates, quantifiable quality measures, and often the volume of corrective action requests in a certain period have been considered to be among the best ways to retain control. These measures have their place, but their scope is limited and they can lead suppliers to place too much emphasis on measurable areas to the detriment of others, particularly if contracts are performance related and punitive.
The main problem with this approach is that it is tier-one supplier centric, leaving unmonitored the lower-tier suppliers, who have just a great an impact on the supply chain. A key word that appears to have been overlooked in this traditional approach is “chain”. Each supplier represents only one link in that chain, and analytics that focus on just one aspect are inevitably going to be limited by that constraint.
The Changing Market
Market volatility is rife, with climate anomalies, exchange rate mechanisms and world economic uncertainty playing a major part in how smooth a supply chain process runs. Increased product variations, and the explosion of the consumer markets in the east are also having dramatic effects on the availability and pricing of key resources. Businesses are becoming ever more complex as a result.
Business Network Analytics
Forward-thinking businesses are changing tack, and moving towards a wider network approach in their supply chain analytics. It involves the collaboration and connectivity of all members of the supply chain. Openness in respect of internal performance dashboards, and key performance data up and down the supply chain is essential to the effectiveness, and this involves a new era of trust within the supplier relationships.
Sharing the analytics that result from this collaboration can, if used correctly, reap radical rewards across all areas of the supply chain. It provides the basis for the establishment of many inter-company processes like vendor-managed inventory, customer order management and demand forecasting. Further benefits can be driven through closer collaboration on product design and issue resolution processes.
The more data gathered, the more useful the analytics can be, as the realms of predictive analytics open up quickly once a solid knowledge base has been established. If similar data collection initiatives are at play across industry peers, it can be possible to aggregate information to the benefit of all. Incorporating publicly available data on financial performance, customer bases, credit ratings and industry can also enhance the overall picture of the industry and the supplier.
Analytics derived from this data can be used to benchmark suppliers against industry averages, and other customers, predict supplier performance, or even maximize margins by optimizing order volumes based on production analysis. Informed use of analytics can have a significant and positive impact on supply chain performance, driving down baseline costs.
The concept of business intelligence is a relatively new. BI is effectively current and relevant information relating to the running of your business that can inform decision-making. Keeping data from tendering processes, for example, can provide valuable market insight further down the line.
Incorporating embedded BI collection software into your business systems will keep this data current. Once the databank builds the possibility for analytic intervention and application is unlimited. Encouraging suppliers to buy-in to this approach will act as enabler to the business network analytics discussed above.
If any doubt remains as to the effectiveness and relevance of data analytics, you only have to look at some of the larger retail organizations to see how they employ them. Supply chain is one of the disciplines in which good practice that applies to large organisations can easily be adapted for small ones. The principles of visibility, relevant measurable data, and openness and trust apply whether you are seeking to tighten-up a supply chain that demands 20 units a month, or 20 million units a month. Procurement in many senses is a gamble, a game of chance. Choosing the right supply partner is critical to the success of your operation. Just as a stock broker relies on market information to decide what to trade and with whom, a procurement professional can only make good business choices if the data they are basing those choices on is current and relevant.
The bottom-line is that network analytics are an invaluable interrogation tool in keeping your supply chain well-oiled. The wider your can cast the information net, the more relevant and helpful those analytics will be.
This article was contributed by Evelyn Robinson.
Originally posted on Tue, May 14, 2013 @ 08:09 AM