May 17, 2020

McKinsey: six key areas of resilience to combat COVID-19

Supply Chain
Sean Galea-Pace
4 min
McKinsey: six key areas of resilience amidst COVID-19
Supply Chain Digital breaks down McKinsey’s report ‘Supply chain recovery in coronavirus times - plan for now and the future’.

In McKinsey’s re...

Supply Chain Digital breaks down McKinsey’s report ‘Supply chain recovery in coronavirus times - plan for now and the future’.

In McKinsey’s report, it was discovered that there are six sets of issues that require efficient action across the end-to-end supply chain amidst COVID-19. These are:

  • Create transparency

  • Estimate available inventory

  • Assess realistic final customer demand

  • Optimise production and distribution capacity

  • Identify and secure logistics capacity

  • Manage cash and net working capital

Create transparency 

First, it is important to work out the most important components of operations. Working with operations and production teams to review your bills of materials (BoM) and catalogue components will work out the ones that are sourced from high-risk areas. 

Following the identification of the critical components, organisations can subsequently assess the risk of interruption from tier-two and onward suppliers. This stage of planning should include asking direct questions of tier-one organisations about who and where their suppliers are, as well as creating information-sharing agreements to work out any disruption being faced in tier-two and beyond organisations. Manufacturers should engage with all of their suppliers across all tiers in order to establish a series of joint agreements to monitor lead times and inventory levels as an early-warning system for interruption and work out a recovery plan for critical suppliers by commodity.McKinsey Coronavirus


Estimate available inventory

Lots of businesses would be surprised at how much their inventory sits in their value chains and should work out how much of it is available. Estimating the inventory along the value chain helps capacity planning during a ramp-up period. Specific categories include:

  • Finished goods held in warehouses and blocked inventory held for sales, quality control and testing.

  • Spare parts inventory that could be repurposed for new product production.

  • Parts with lower grade ratings or quality issues, which should be assessed to work out if the rework effort would be justified to solve quality issues.

  • Parts in transit should be considered to see what steps can be taken to speed up their arrival, including those in customs or quarantine.

  • Supply currently with customers or dealers should be considered to see if stock could be brought back or transparency could be created for cross-delivery.

Assess final customer demand

When a crisis happens, it is important to forecast demand. To prepare correctly, organisations should:

Develop a demand-forecast strategy, which includes defining the granularity and time horizon for the forecast to make risk-informed decisions in the S&OP process.

Use advanced statistical forecasting to obtain a realistic insight into base demand.

Integrate market intelligence into product-specific demand forecasting models.

Ensure dynamic monitoring of forecasts in order to react quickly to inaccuracies. 

Optimise production and distribution capacity

With demand forecast, the S&OP process should be able to optimise production and distribution capacity. Scenario analysis can be used to test different capacity and production scenarios to understand their financial and operational implications. Optimising production starts with ensuring employee safety. This will include sourcing and engaging with crisis-communication teams to communicate effectively with employees about infection-risk concerns and options for remote and home working.

Identify and secure logistics capacity

In the midst of a crisis, working out the current and future logistics capacity by mode is even more vital than ever before. As organisations seek to increase productions and make up time in their value chains, they should prebook logistics capacity to reduce exposure to potential cost increases. Working with partners can be considered an effective strategy to gain priority and add capacity on more favourable terms. 

Manage cash and net working capital

As the coronavirus continues to take over, constrained supply chains, decreasing sales and significantly reduced margins will add more pressure on earnings and liquidity. Companies will require all available internal forecasting capabilities to stress test their capital requirements on weekly and monthly bases. It remains imperative that supply chain leaders focus on freeing up cash locked in other parts of the value chain. Decreasing finished-goods inventory through thoughtful, ambitious targets that is backed by robust governance can help towards achieving substantial savings.

To read McKinsey’s full report, click here!

For more information on procurement, supply chain and logistics topics - please take a look at the latest edition of Supply Chain Digital magazine.

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May 13, 2021

5 Minutes With: Jim Bureau, CEO Jaggaer

3 min
Jaggaer CEO Jim Bureau talks data, the power of procurement analytics, and supply chain risk management

What is data analytics, and why is it important for organisations to utilise?

Data analytics is the process of collecting, cleansing, transforming and analysing an organisation’s information to identify trends and extract meaningful insights to solve problems. 

The main benefit for procurement teams that adopt analytics is that they’re equipped to make faster, more proactive and effective decisions. Spend analysis and other advanced statistical analyses eliminate the guesswork and reactivity common with spreadsheets and other manual approaches and drive greater efficiency and value. 

As procurement continues to play a central role in organisational success, adopting analytics is critical for improving operations, meeting and achieving key performance indicators, reducing staff burnout, gaining valuable market intelligence and protecting the bottom line. 

How can organisations use procurement analytics to benefit their operations? 

Teams can leverage data analytics to tangibly improve performance across all procurement activities - identifying new savings opportunities, getting a consolidated view of spend, understanding the right time for contract re-negotiations, and which suppliers to tap when prioritising and segmenting suppliers, assessing and addressing supply chain risk and more. 

Procurement can ultimately create a more comprehensive sourcing process that invites more suppliers to the table and gets even more granular about cost drivers and other criteria. 

"The main benefit for procurement teams that adopt analytics is that they’re equipped to make faster, more proactive and effective decisions"

Procurement analytics can provide critical insight for spend management, category management, supplier contracts and negotiations, strategic sourcing, spend forecasting and more. Unilever, for example, used actionable insight from spend analysis to optimise spending, sourcing, and contract negotiations for an especially unpredictable industry such as transport and logistics. 

Whether a team needs to figure out ways to retain cash, further diversify its supply base, or deliver value on sustainability, innovation or diversity initiatives, analytics can help procurement deliver on organisational needs.

How is data analytics used in supply chain and procurement? 

Data analytics encompasses descriptive, diagnostic, predictive and prescriptive data. 

Descriptive shows what’s happened in the past, while diagnostic analytics surface answers to ‘why’ those previous events happened. 

This clear view into procurement operations and trends lays the groundwork for predictive analytics, which forecasts future events, and prescriptive analytics, which recommends the best actions for teams to take based on those predictions. 

Teams can leverage all four types of analytics to gain visibility across the supply chain and identify optimisation and value generating opportunities.

Take on-time delivery (OTD) as an example. Predictive analytics are identifying the probability of whether an order will be delivered on time even before its placed, based on previous events. Combined with recommendation engines that suggest improvement actions, the analytics enable teams to proactively mitigate risk of late deliveries, such as through spreading an order over a second or third source of supply. 

Advanced analytics is a research and development focus for JAGGAER, and we expect procurement’s ability to leverage AI to become even stronger and more impactful.


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