The supply chain management (SCM) community is coming to terms with a new world economic picture in which the simple procurement and delivery of goods suddenly seems fraught with risk and uncertainty. The response to events such as the COVID pandemic and war in Ukraine for many firms has been to move into a mode of crisis management.
However, this reactive approach to changing events may not yield optimal results in the long term. Effective SCM is about more than simply responding to changes in the supply chain: it’s about anticipating and, where possible, mitigating them. How is this possible? In this piece, BearingPoint will outline a comprehensive approach to this challenge that we take with our customers.
Just when it appeared that the worst of the pandemic was finally over, Shanghai went into lockdown again, throwing a spanner in the works of supply chains serving myriad firms including Apple, Tesla and Amazon. The response has been a renewed enthusiasm for two familiar panaceas. Firstly, a supplier diversification approach to spread risk more evenly, and secondly, nearshoring: looking for possible sources of components and products regionally, rather than globally.
So much for one of the world’s manufacturing powerhouses. But an even more global trend affecting supply chains is inflation. With regions around the world seeing a sharp increase, businesses are struggling to keep abreast of the changes as prices of commodities, components and transportation continue to rise.
BearingPoint have been monitoring these events closely. We predict a higher incidence of troubling events within global supply chains, that include supplier bankruptcy, price and supply volatility, logistics disruption and storage capacity issues. Sectors strongly affected include pharmaceuticals, chemicals and oil and gas.
The pandemic, the Ukraine war and inflation are all impacting supply chains at just the point when a truly long term trend has matured into an unavoidable imperative – sustainability.
Supply chains are under the spotlight now more than ever as businesses seek to demonstrate that the way they procure products and bring them to market takes into account both environmental and human impacts.
Huge reputational risk is attached to sustainability in the supply chain. Good news stories, such as Subaru’s zero-waste factory in Indiana, can significantly improve brand perception, whereas major failings, such as the Rana Plaza factory tragedy affecting Primark, Walmart and others, can have a profoundly opposite effect.
The sustainability imperative creates an added layer of complexity for businesses seeking to make their supply chains more resilient.
Against this backdrop of uncertainty, there is great variability between businesses in their approaches to managing supply chain risk. Many firms adopt a taskforce approach, reacting operationally to events such as conflict or a pandemic. This is often at the expense of developing a long-term, strategic view.
SCM teams need to allocate resources to look ahead, not simply react. They need to pull together a transparent, structured picture of supply chain risk. Anticipating future challenges has never been more important, and doing so requires systematic collection and analysis of high quality data.
At BearingPoint, we recommend five pillars that businesses can adopt to establish and manage a data-driven supply chain. The purpose of these pillars is to structure and systematize the use of data that can provide a much more certain platform for supply chain strategy over the medium to long term:
It’s essential to have access to as much data and information as possible about your suppliers, both current and potential. This includes operational data, such as inventory levels and replenishment lead times, as well as financial data including resilience and ownership. Proprietary supplier data can be sensitive, and challenging to acquire, but the benefits are considerable.
Derive as much data as you possibly can from your existing processes. Understand where set-up times are lengthy, which processes are inflexible, equipment reliability and lifespans, and carefully monitor contract lifecycles to forecast both the need and opportunity for supplier changes.
This is data that may be imported from a third party provider, and includes information and associated impact assessments around natural disasters, conflict, trade wars, and of course, pandemics.
Knowing your suppliers is one thing; connecting with them and integrating them within your business systems and processes is another. Sharing information and data is critical in building trust, though it may be challenging. Forecasting should be done as much as possible in a collaborative way, which reduces bullwhip effects that can adversely affect supplier relationships.
Undertake detailed scenario modelling to understand how demand could be affected by the loss (or acquisition) of major clients, volatility in market demand, and competitor activity. Use this data once again to model supply patterns in collaboration with your suppliers.
In addition to our five-pillar model, we recommend some further guiding principles to ensure effective use of supply chain data.
The first can be expressed simply: businesses get out what they put in. SCM forecasts and models are only as good as the quality of data that informs them. Data from anywhere – internal, supplier and third party – should be scrutinised to understand its accuracy and validity. For any dataset, how reliable is the source?
Next comes the critical importance of product cost breakdown. It’s imperative to understand how cost accumulates at every stage of the supply chain, from origin to point of sale. This transparency helps your business to compare chains – either live or hypothetical, and understand which are the most commercially desirable in simple cost terms. Product cost breakdown should be the bedrock of supply chain planning.
Data from 3rd party providers is an important part of your data mix. It’s useful, and has its place, but comes with a single strong caveat: it’s always ex-post. It describes what has happened in the past, and is inadequate for predicting the future. For truly useful and reliable forecasting, businesses need internally-generated data.
Finally, supplier calculation models should take into account a number of key metrics to be comprehensive and useful assessments of a supplier’s value and risk exposure. BearingPoint typically recommend a model that takes into account operational risk score, supply chain score and financial risk score to produce an overall rating.
For existing businesses, reconfiguring a supply chain cannot be done overnight. Programmes such as supplier diversification and nearshoring can take years to fully implement.
The keys to building a resilient supply chain are thinking strategically, achieving the strongest possible visibility, and using every source of high-quality data at a business’ disposal. The challenges of attaining these three things are considerable and complex, but bring great rewards in terms of long-term certainty. BearingPoint help our clients to transition to a longer view of their supply chains thanks to extensive experience across numerous sectors, and a focus on data-driven strategy.