The growing importance of supply chain risk management

The growing importance of supply chain risk management

The growing importance of supply chain risk management

Against the backdrop of a highly disruptive and volatile market environment, supply chain risk management has risen to the top echelons ofboardroom agendas. Vivianne Courte-Rathwell, a Consultant at Sourcing Champions, explains why the concept is gaining importance – and outlines some of its main benefits.

A review of the historic supply chain disruptions of the past few years would hardly be news to anyone. In an unprecedented ‘risky’ period, with a pandemic, climate change, a Russia-Ukraine war, geopolitical pressures, and much more, it is no surprise that global supply chains have recently been dealing with heightened risks.

However, it is key to keep in mind that such disruptions do not only occur in unfortunate periods of history. Risks are by nature ubiquitous and unpredictable, and that means that leaders need to embrace an approach that helps them mitigate, adapt and learn.

In 2012, there was a disastrous tsunami in Japan which impacted the automotive industry worldwide. In 2015, an immense explosion at one of the largest ports in the world, the Port of Tianjin, caused significant costs and losses. In 2018 the US – China trade war negatively impacted profit margins and created tense times of uncertainty.

It is impossible to conceive to avoid all risks. Instead, the key is to mitigate significant damages through foresight in strategic management.

After the tsunami of 2012, automotive organizations had nowhere to turn as many realized that their single source of materials was Japan. Even OEMs with a multi-sourcing strategy encountered issues because many tier-1 suppliers procured materials from the same tier-2 supplier. As a result, the challenges of tier-2 suppliers became a direct concern as well.

Had there at the time been a multi-layer supply chain risk management (SCRM) program in place, these issues could have been (easily?) avoided and impact to the business would have been minimized. SCRM tools and processes act as guardrails and shields protecting the business from potential perils, hence providing a competitive advantage.

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7 skills logistics leaders will need to manage the digital supply chain

7 skills logistics leaders will need to manage the digital supply chain

7 skills logistics leaders will need to manage the digital supply chain

It took some time for the tech revolution to hit the logistics industry, but now that it’s here, everything is changing rapidly. Suddenly, it’s all about omnichannel commerce, digital transparency, and advanced analytics (among many other trends). And as the world of logistics changes, the leaders of the logistics industry will have to develop new skills with which to navigate it.

What skills will the logistics leaders of tomorrow (and today) need to effectively manage the new realities of the supply chain? These seven areas will define the success of a business’s digital supply chain operations and separate the organizations that can fuel their success with technology from the ones who must struggle to adapt to it.

To manage the digital supply chain, here are 7 skills logistics leaders need

1. Ability to adapt

Twenty-first-century logistics will require its leaders and managers to constantly learn how to use new tools and react to changing market conditions. The new logistics professional has to keep a steady hand at the tiller during times of big change and use solid data analysis to find the right path forward, even when market conditions aren’t perfectly clear.

2. Proactive curiosity

Adaptation is easier when a business pursues the right new tech, rather than waiting for it to come to them. Good logistics management will also increasingly require a commitment to proactively keeping up with technological and industry trends.

3. Strategic thinking

Thinking two steps ahead can be tough when the business environment is changing so rapidly, but that’s what the new millennium logistics professional has to do. They have to take the long view and keep a business’s core principles at heart when creating plans for the future.

4. Enterprise IT use and procurement

Enterprise IT is an increasingly critical skill set for logistics professionals. Almost all logistics companies now use enterprise IT software, such as ERP suites, to manage their supply chains, and digital logistics professionals must often make decisions about procurement and implementation of these sophisticated software products.

5. Project management

Today’s logistics professional often has to assume leadership roles on major projects. In order to be an effective leader, they must be skilled at tasks such as:

  • ● Identifying the strengths and weaknesses of team members and delegating tasks to them effectively
  • ● Working with upper management to structure project calendars and deadlines
  • ● Estimating costs and planning for the budgeting and deployment of resources

6. People skills

Speaking of managing people, logistics professionals must also remember that not everything in the digital supply chain is run by circuits in a plastic enclosure. On the contrary, old-fashioned people skills are as necessary in the logistics industry as they’ve ever been—perhaps even more so.

7. An omnichannel mindset

Business, both B2C and B2B, now flows through a multitude of channels. That means that for the 21st-century logistics professional, an omnichannel mindset is a must-have. Whoever your customers are, they’re now on mobile phones, tablets and even voice command services like Alexa. A business’s platform and its logistics operations must reflect this new reality.

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How To Improve Supply Chains With Machine Learning: 10 Proven Ways

Bottom line: Enterprises are attaining double-digit improvements in forecast error rates, demand planning productivity, cost reductions and on-time shipments using machine learning today, revolutionizing supply chain management in the process.

Machine learning algorithms and the models they’re based on excel at finding anomalies, patterns and predictive insights in large data sets. Many supply chain challenges are time, cost and resource constraint-based, making machine learning an ideal technology to solve them. From Amazon’s Kiva robotics relying on machine learning to improve accuracy, speed and scale to DHL relying on AI and machine learning to power their Predictive Network Management system that analyzes 58 different parameters of internal data to identify the top factors influencing shipment delays, machine learning is defining the next generation of supply chain management. Gartner predicts that by 2020, 95% of Supply Chain Planning (SCP) vendors will be relying on supervised and unsupervised machine learning in their solutions. Gartner is also predicting by 2023 intelligent algorithms, and AI techniques will be an embedded or augmented component across 25% of all supply chain technology solutions.

The ten ways that machine learning is revolutionizing supply chain management include:

  1. Machine learning-based algorithms are the foundation of the next generation of logistics technologies, with the most significant gains being made with advanced resource scheduling systems.
  2. The wide variation in data sets generated from the Internet of Things (IoT) sensors, telematics, intelligent transport systems, and traffic data have the potential to deliver the most value to improving supply chains by using machine learning.
  3. Machine learning shows the potential to reduce logistics costs by finding patterns in track-and-trace data captured using IoT-enabled sensors, contributing to $6M in annual savings.
  4. Reducing forecast errors up to 50% is achievable using machine learning-based techniques.
  5. DHL Research is finding that machine learning enables logistics and supply chain operations to optimize capacity utilization, improve customer experience, reduce risk, and create new business models.
  6. Detecting and acting on inconsistent supplier quality levels and deliveries using machine learning-based applications is an area manufacturers are investing in today.
  7. Reducing risk and the potential for fraud, while improving the product and process quality based on insights gained from machine learning is forcing inspection’s inflection point across supply chains today.
  8. Machine learning is making rapid gains in end-to-end supply chain visibility possible, providing predictive and prescriptive insights that are helping companies react faster than before.
  9. Machine learning is proving to be foundational for thwarting privileged credential abuse which is the leading cause of security breaches across global supply chains.
  10. Capitalizing on machine learning to predict preventative maintenance for freight and logistics machinery based on IoT data is improving asset utilization and reducing operating costs.

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What’s the Difference Between Business Intelligence (BI) and EPM?

Business Intelligence Emerges From Decision Support

Although there were some earlier usages, business intelligence (BI) as it’s understood today evolved from the decision support systems (DSS) used in the 1960s through the mid-1980s. Then in 1989, Howard Dresner (a former Gartner analyst) proposed “business intelligence” as an umbrella term to describe “concepts and methods to improve business decision-making by using fact-based support systems.” In fact, Mr. Dresner is often referred to as the “father of BI.” (I’m still trying to identify and locate the “mother of BI” to get the full story.)

The more modern definition provided by Wikipedia describes BI as “a set of techniques and tools for the acquisition and transformation of raw data into meaningful and useful information for business analysis purposes.” To put it more plainly, BI is mainly a set of tools or a platform focused on information delivery and typically driven by the information technology (IT) department. The term “business intelligence” is still used today, although it’s often paired with the term “business analytics,” which I’ll talk about in a minute.

Along Came Enterprise Performance Management

In the early 1990s, the term “business performance management” started to emerge and was strongly associated with the balanced scorecard methodology. The IT industry more readily embraced the concept around 2003, and this eventually morphed into the term “enterprise performance management” (EPM), which according to Gartner “is the process of monitoring performance across the enterprise with the goal of improving business performance.” The term is often used synonymously with corporate performance management (CPM), business performance management (BPM), and financial performance management (FPM).

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Why Supply Chain Risk Management is Key to Supplier Management

While brand damage can be quite costly to the businesses whose sales rely strongly on the customer loyalty they generate from their brand strength, cost volatility and supply disruption is very costly to all manufacturers. In fact, in the latest 2015 study by the Business Continuity Institute, supply chain disruption is double in priority relative to other enterprise disruptions and over three-fourths of respondents cited that they had at least one recent (significant) disruption. The same percentage didn’t have full visibility of their supply chains.

While category management can address and even reduce supply chain risk by ensuring a chosen strategy has the right level of resiliency, prevention and agility, it cannot prevent risk or do much to eliminate the source of risk once something has happened. That can only be done by each party in the supply chain doing everything they can to eliminate the risk. In particular, a supplier needs to do all they can to minimize the risk on their end.

However, not all suppliers are as advanced in supply chain management, and in particular, risk management as the buying organization. That’s why good supplier management combined with SCRM is key. Good risk management is a combination of risk prevention and risk mitigation when a risk is detected. Risk prevention involves selecting suppliers, products and services that are low risk and risk mitigation involves taking action as soon as an indicator is detected.

A supplier is not always good at mitigating or even detecting risk in its supply chain, or may overlook an obvious sign that an observant buyer would not, which is why proper supplier management is key. This begins even when qualifying suppliers. Including risk criteria related to the supplier and supplier location gives a good indication of a supplier’s the risk level. Besides the supplier qualification criteria, supply location-related risks provide an overview on potential threats like natural disasters, political situation, sanctions or economic risk. This gives buyers the chance to take preventive actions.

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How to Use Big Data to Enhance Employee Performance

Big Data has been one of the most significant and influential aspects of the Information Age as it relates to the enterprise world. Essentially, Big Data is the massive collection, indexing, mining, and implementation of information that emanates from just about any activity that can be monitored and managed electronically. Some of the uses of Big Data include: marketing intelligence, sales automation, strategizing, productivity improvement, and efficient management.

Enhancement of the workforce is one of the exciting and meaningful benefits of Big Data for the business sphere. Recently, human resource managers and analysts have been researching the implementation of Big Data as it relates to employees, and the following trends have emerged:

Employee Intelligence

For many decades, companies and organizations have tried various methods to gain knowledge about what their employees are really like. The productivity that workers can contribute to their employers is based on personal needs as they are balanced against the performance of their duties. With Big Data solutions, both personal needs and performance can be diluted into metrics for efficient analysis.

Modern workplace analytics originates from tracking employee records as well as metrics on their performance, interactions and collaboration. The idea is to focus on the right metrics to create a climate of positive engagement.

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One step ahead: How data science and supply chain management are driving the predictive enterprise

DHL, the world’s leading logistics company, today launched its latest white paper highlighting the untapped power of data-driven insight for the supply chain. The white paper has revealed that most companies are sitting upon a goldmine of untapped supply chain data that has the ability to give organizations a competitive edge. While this wealth of supply chain data already runs the day-to-day flow of goods around the world, the white paper has revealed a small group of trailblazing companies are utilizing this data as a predictive tool for accurate forecasting.

“The predictive enterprise: Where data science meets supply chain” is a white paper by Lisa Harrington, President of the lharrington group LLC that was commissioned by DHL to identify the opportunities available to companies to anticipate and even predict the future. It encourages companies to get ahead of their business and direct their global operations accordingly.

Data mining, pattern recognition, business analytics, business intelligence and other tools are coalescing into an emerging field of supply chain data science. These new intelligent analytic capabilities are changing supply chains – from reactive operations, to proactive and ultimately predictive operating models. The implications extend far beyond just reinventing the supply chain. They will help map the blueprint for the next-generation global company – the insight-driven enterprise.

Jesse Laver, Vice President, Global Sector Development, Technology, DHL Supply Chain, said, “At DHL, we’re helping our customers get ahead of the competition by working with them to harness the wealth of data information from across their businesses, allowing us to develop smarter supply chain solutions that factor in their wider business operations. For our technology customers, we use data analytics to predict what’s going on in the supply chain, such as what products are in high demand, so we can tailor our solutions accordingly.”

While supply chain analytics technologies and tools have come a long way in the last few years, integrating them into the enterprise is still far from easy. Companies typically progress through several stages of maturity as they adopt these technologies. The descriptive supply chain stage uses information and analytics systems to capture and present data in a way that helps managers understand what is happening.

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Globalization Creates New Avenues for Supply Chain Risk: riskmethods Shares its Predictions for 2016

As part of our ongoing series on what procurement technology providers see as the biggest challenge for procurement in 2016, we recently spoke to riskmethods to hear its thoughts on the topic. Heiko Schwarz, riskmethods founder and managing director, pointed to increased external risks, globalization and regulation compliance as the main issues procurement and supply chain managers will have to tackle in the new year.

These three major trends will expose organizations to risks in 2016, Heiko said. External risk will continue to be an issue. For example, extreme weather such as rain or snow storms will expose and disrupt supply chains even more than in the past, he said. Political risks have been a growing trend for years, but will continue in 2016 as well, he added.

Globalization is also pushing enterprises to search for new suppliers in countries or regions they probably have not worked in before. Procurement’s scope in the last year has dramatically changed, going from a “domestic-centric” view to a more global one, Heiko said. Specifically, he believes we will see movement away from China as the cost of operating there continues to rise. China is no longer a low-cost sourcing country, and this is putting pressure on companies to move to new areas, places such as the northern regions of Africa, he said. This globalization push will put increase supply chain complexities in 2016.

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New Solutions for Supply Chain Risk Management: A Case Study

We are entering an era where it is becoming possible to detect supply chain risks much more quickly. A case in point is offered by AGCO. AGCO AGCO +1.96% is a global leader in the design, manufacture and distribution of a wide range of agricultural equipment. In a discussion with AGCO’s Jan Theissen, Director of Strategy and Methods, and Jake Stone, Manager of Supply Chain Risk and Contract Management, I learned about this public, Atlanta headquartered corporation’s journey to improve their sourcing and supply base risk management capabilities.

AGCO’s products are marketed under a number of well-known brands, including Challenger, Fendt, GSI, Massey Ferguson and Valtra. The manufacture and assembly of their products occurs at 34 locations worldwide and historically each of these brands was managed as a separate supply chain. Further, because the company had grown by acquisition, these different supply chains used more than 10 different enterprise resource planning (ERP) solutions for direct sourcing.

Beginning in 2012, Mr. Theissen, a newly appointed procurement leader, led a transformation of the sourcing organization. AGCO moved from a fragmented and decentralized procurement to a centralized commodity management structure in order to better leverage buying synergies and increase the overall maturity level of this organization. Implementation of standardized roles and responsibilities, and global policies and procedures, were supported by an extensive change management program. The company formed a School of Purchasing to further develop the capabilities of the organization.

The risks associated with sourcing became part of each category manager’s job; these managers became responsible for supplier risk management, not just savings. Mr. Stone was brought into establish new, systems, processes and capabilities to manage procurement risk. One thing Mr. Stone put in place was a clear communication and escalation process to deal with risks once detected.

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Beware the ‘black swans’ in your supply chain

Enterprises know that merely having a supply chain involves a certain amount of risk, but few do enough to protect against the one-off, extreme incidents that can disrupt them.

That’s according to Yossi Sheffi, an MIT professor who is director of its Center for Transportation & Logistics.

Such events — sometimes referred to as “black swans” — include unanticipated catastrophes such as Hurricane Katrina, the BP Horizon oil rig explosion, the 9/11 terrorist attack, the tsunami that hit Japan in 2011, and even the Volkswagen emissions scandal.

While most risk-planning processes focus on events that happen relatively often, such as routine weather emergencies, they often ignore the extreme ones that are considered too unlikely to worry about, Sheffi argues.

While such events are unlikely, the probability that they’ll happen isn’t zero — as history has proven again and again.

“Black swans are never expected,” Sheffi said in an interview. “There are many examples of low-probability, high-impact disruptions. People don’t believe they can happen, but they do — and there will be more.”

Vendors such as Resilinc and Elementum along with IBM, SAP and Cisco are increasingly coming out with software to help companies protect themselves, he noted.

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