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How to Balance Efficiency and Risk in Your Supply Chain

How to Balance Efficiency and Risk in Your Supply Chain
Over the past several years, the drive to a digital supply chain and the use of IOT has been a major emphasis for those improving their processes and removing inefficiencies. In our quest for the next great technology or tool, have we missed some fundamentals? The current COVID-19 crisis has shone spotlights on supply chains and their ability to react and be flexible to changing demands and supply. However, this is not the first-time challenges have occurred where we have had to adapt and respond to some portion of the supply chain being disrupted; hurricanes Katrina and Rita, and the earthquake in Kyoto are a couple of examples. And those are just the natural disasters. If we add geo-political unrest, trade wars and import/export regulation changes, we see more frequent disruptions, and perhaps acceleration. How have supply chains adapted? In many cases, they haven’t.

Frantic discussions are happening now on how to react and what needs to be in place. My hope is that these activities and action teams result in processes that can be institutionalized. In talking with companies across several different industries, trying to understand the strains on the process by hand is a common denominator. The philosophy of “buy-one, make-one” and many other lean principles that cut waste and redundancy out of supply chains, might very well be brought into question now.

We have compiled this how-to guide to help inspire companies to structure, validate or extend what they may have already done or provide a roadmap on how to get started. Our emphasis is in preserving the lessons learned in these types of crises, using this knowledge, enabling the capabilities within your systems and processes. Supply Chain organizations need visibility now, and in the future, to leverage the data for making decisions and taking informed actions, both in times of crisis and in relative stability.
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Source Risk:

Ensure visibility into vendor ship-from/source country of origin for all materials supplied;

Link parts/materials supplied by vendors (ship-from’s) from affected areas – impacts may be from geo-political or natural disasters;

Measure order change (receipt) variability (date/quantity/quality) and trends;

Identify price/shipping cost variations with normal and non-normal channels;

Set up a “risk index” score by vendor/item considering region stability, financial viability, performance degradation during the crisis;

Ideally, having visibility into the vendor’s supply chain and material sourcing strategy, key materials in the process, their capacity constraints and vendor strategy support even further understanding of supply risk and disruption;

Establish a secondary or alternative sourcing option that may be leveraged in short order quickly, when required.

Inventory Impact:

Compare supply risk (either supplier risk index, cost changes or delivery variability) to current inventory levels:
  • Identify highest risk items, by location
  • Rank items by single/sole/commodity source
  • Identify alternative sources of material (for single/commodity) or identify schedule adjustments
  • Measure cost impact(s)
    • At the tier level (primary versus secondary suppliers)
    • Evaluate risk at a granular (by item and supplier) and aggregate (by tier and location) level
Evaluate return(s) impact from either logistics or “pandemic related changes” to delays and the financial changes from the holding of inventory.

Schedule Impact:

Compare inventory and delivery capabilities to production schedules and identify schedule impacts and risk;

Identify scheduled impact for higher risk areas.

Contract Exposure:

Identify exposure risk of contracts with minimum or step-wise volume-related purchases vs. planned purchases;

Determine volume shortfalls and potential penalties with vendors;

Identify rebate or price adjustment value(s) that will be missed.

Sales Impact:

Identify linkage between finished goods and high risk vendors/materials;

Identify sales $ associated with finished goods tied to at risk materials and vendors;

Report SLA’s tied to finished goods/customers based on material shortages;

Identify penalty $ associated with finished goods tied to at risk materials and vendors.
 

Making it Stick

When companies implement such measures during a crisis, they usually stand up a “minimum viable product” or the minimum needed to fill the need. It usually comes at great effort and maximum exertion, only to be discarded when normalcy returns. Instead, the new capabilities should be evaluated, shored up to make them robust, repeatable and sustainable. They should be available for everyday decision making for how sourcing risk affects the rest of the supply chain. As information is collected and integrated to support these decisions, the use of more advanced analytics to help automate these processes becomes an option. The few key areas identified above, attached with sourcing and procurement, may be extended or adapted to risk in manufacturing, logistics, transportation and replenishment. Availability of resources, closures and social distancing impact manual operations up and down the supply chain which leads to extended cycle times and disruptions.

Organizations are reacting swiftly during this crisis to assess how to address critical shortages, bottlenecks, and potential at-risk suppliers. Don’t let this be a one-time search for information and use of analytics under these circumstances. Plan to invest the additional time and effort to operationalize these processes to support your supply chain in good times and bad. By following the roadmap we have provided here, companies may be better able to sort out their priorities for action, plus a framework for organizing their data to be better leveraged for now and future situations that will inevitably arise. 
Portrait of Greg Sloyer

(Author):
Greg Sloyer

Greg is a Sr. Industry Consultant working with customers across a variety of industries on supply chain and related topics. Prior to joining Teradata 13 years ago, he spent nearly 20 years in the chemical industry in functions ranging from IT, Logistics and Supply Chain Operations. Greg has undergraduate degrees in Mathematics and Computer Science, a Masters in Statistics and a Ph.D. in Operations Research from the University of Delaware. View all posts by Greg Sloyer

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