There is a widespread fear of a global economic meltdown. Particularly today, it is visible to everyone how critical Supply Chain performance is. A well-run Supply Chain ensures that we all get our daily goods such as toilet paper, hand sanitizers, masks, tests and drugs.

For the Supply Chain Manager and the CEO, experiencing such a major crisis for the first time, it can be challenging to navigate both mentally and operationally in this challenging environment. That’s why we have gathered a crisis checklist. The checklist is of course not covering all aspects, but it can work as a starting guide.

The following crisis checklist is of course not covering all aspects, but it can work as a starting guide.

Crisis checklist step 1: Move the crisis into the boardroom
Like never before, the Supply Chain has the attention of the board. A survey conducted by PwC showed that 9,34% of the CFO’s said Supply Chain issues were among their top 3 concerns in the current climate. That being said, 30% of the companies where thinking about making changes to their existing Supply Chains. The conclusion is though that the duration of the impact is the most important factor. It is expected that the learnings from the outbreak will most likely move the competitive forefront of Supply Chain operations toward more comprehensive, proactive modeling.

Crisis checklist step 2: Establish a war-team and understand your supply exposure
You should start out by asking yourself:

  • What are the challenges, our supply chain is facing?
  • What actions could be taken to tackle unexpected challenges?
  • What is the short-term immediate action plan? Can we short term look at different sourcing strategies?
  • What aspect of supply chain management is most challenging – demand forecasting, logistics, manufacturing?

If you have not already done so – establish your crisis team. Make sure it works cross functional. Some companies are working with daily dashboards in order to handle it operationally. It is not enough to handle the issues on a high-level track driven approach.

For many companies it means looking into production and part-level mitigation. It could also be beneficiary to look into your n-tier exposure, which means reaching out to tier-2 and tier-3 sources and risks. It is about being fact based: which components are affected, at what production burn rate and what is supposedly on-hand and in-transit.

A way to proactively mitigate risk is to build extreme scenarios. It could be: “this is a 100 year event”. If you do not have the digital software yet, short term operational solutions can be established if working agile and focused.

Crisis checklist step 3: Protect your employees and customers
The advice is to implement and overinvest in the best-known guidelines available for both employees and customers. Overcommunicating with full transparency is not possible.

Crisis checklist step 4: Defend against revenue decline
How will this effect business results and how are we minimizing the negative impact on business results?

Start by putting the customer in the centrum. How will you build trust, loyalty and market share through and beyond the crisis. Build specific revenue mitigation actions for core revenue stream declines. Pivot resources to pockets of current and future growth, online and beyond

Crisis checklist step 5: Plan urgent cost take-out to conserve cash
After stabilizing operations to “new normal” it is time to look at whether it is necessary to reduce cost in order to conserve cash. One of the ways to release cash is by looking at what you have in stock, what the demand looks like and how the processes are towards your suppliers. Research conducted by Optilon shows, that in average 22% of what companies have in stock is not necessary.

Crisis checklist step 6: Design your future Supply Chain around risk competitiveness
Already now companies are experiencing product and material shortages. For most of the companies the short-term focus is on getting things working. In the long term though, many companies are looking at rethinking their Supply Chains, making them less risk prone and creating contingency plans. Many companies are now realizing that they designed their operations with cost in mind. And not around risk competitiveness.

You could start out by asking yourself:

  • What is our long-term action plan?
  • How are we planning to reduce the risk posed by any future health crisis?
  • Do we have any business continuity plans and protocols to hep us tackle this?
  • What are the ongoing challenges for our supply chain moving forward?

While it is impossible to predict the outcome of this kind of crisis, maintaining and adapting your operations to these fast-changing events is complicated but possible. It is critical for you as a CEO, Supply Chain Manager or business leader in general to have a clear understanding of the disruption consequences and the actions required to restore your business foundation.

References:
https://www.prnewswire.com/news-releases/pwc-cfo-covid-19-pulse-survey-the-first-in-a-bi-monthly-series-that-shows-how-cfos-and-finance-leaders-plan-to-react-to-covid-19–and-what-impacts-they-expect-to-see-301024904.html

Many Supply Chain Executives are nowadays questioning what AI (Artificial Intelligence) in Supply Chain is. It is still the “stuff of the future” for some organizations and to some history’s biggest paradigm shift. Yet, we are still only at the beginning of the AI (r)evolution. In this blog post, we will look into what is AI in Supply Chain.

What is AI (Artificial Intelligence) in the Supply Chain? To some Supply Chain Executives it is still a mystery. How can this technology provide a competitive advantage to the Supply Chain? To learn more about how you can gain a competitive advantage by using AI in the Supply Chain you can read this blog post. In the following, you can learn more about the basics about AI and through an example learn about the logic behind.

The basics of AI in the Supply Chain

In its simplest form, artificial intelligence is when a computer or computer-controlled device runs functions and performs tasks that would normally need human assistance. Depending on its use, this may require a computer to understand speech, have a visual perception, or be able to make decisions that are independent of human intelligence (aka manual intervention).

Many AI machines can also learn on their own and make decisions based on past events. Or, they can interpret massive amounts of data from a company’s supply chain history to predict future outcomes with incredible accuracy.

Terminologies used within AI:

  • Artificial Intelligence: A program that can sense, reason, act and adapt
  • Machine learning: Algorithms whose performance improve as they are exposed to more data over time
  • Deep learning: Subset of machine learning in which multilayered neural networks learn from vast amounts of data

The following three trends have put AI within everyone’s reach.

  • Costs for data storage and processing has gone down
  • Data availability has increased, not only inside the company but also outside
  • Advanced mathematics has enabled complex data modeling

Though the concept of AI is half a century old, interest in the technology has snowballed over the past decade. This has been driven particularly by increased data availability, a lower cost of data processing, and new advanced mathematics, allowing for a significantly lower cost of predictions and analytical capacity.

In Optilon we are seeing particularly fast growth in three areas of AI:

  • Text and numbers: Today, a wealth of information can be found in text and number formats.
  • Speech: AI can also be used for speech recognition, which translates spoken words into text.
  • Images: One of the most common uses of AI is image recognition. AI can be used to categorize, edit, and parse this image data.

Explaining AI using examples

In order to take out some of the mystery which is surrounding AI let us take an example from outside the Supply Chain.

The Real Estate Agent

Imagine a real estate agent who sells apartments. Every time a new seller signs up, the first task is to suggest how much their apartment can be sold for. The real estate agent is busy, and it is time-consuming to inspect all those apartments, so he decides to automate the task using artificial intelligence. The formula behind the intelligence sounds simple. Price is equal to the number of square meters times 20,000. Therefore, an apartment of 100 square meters is always priced at two million. After a short while, the real estate agent discovers the challenges of using this method.

Obviously, there are other things than just land, which affects the price. As an example, ground floor apartments are typically not nearly as expensive as apartments with views. Therefore, the next generation of intelligence puts a sum for each floor apartment located above ground level.

After looking at data for actual sales prices, the formula is refined a bit, because it is mainly on the lower floors that the distance from street level makes a difference. In other words, there is a greater difference in price between the living room and the first floor than between the sixth and seventh floors. In the real estate agent’s formula, it is fixed by taking the square root of the floor number and multiplying by DKK 100,000. Then an apartment on the first floor will be priced DKK 100,000 higher than the ground floor, while one on the ninth floor will be DKK 300,000 higher.

The following generations of formula incorporate further conditions: Whether there is a lift in the property, how attractive the area the apartment is in, whether the apartment is in good condition, how busy the road is, and whether one can see the sea.

Along the way, the formula has become somewhat longer and somewhat more complicated. It has been necessary to use both square roots and logarithms, but it can still be shown on an A4 sheet of paper if you use small print. One can question whether it is reasonable to call the formulas in the real estate example and software in self-propelled cars “intelligent”. As we have seen, in both cases, these are just formulas. Very long formulas, but still only formulas.

They are not, in principle, different from the functional machine whose intakes consisted of the formula y = 2x + 1.  Artificial intelligence is, therefore, in no way intelligent. Absolutely not. The name probably describes researchers’ wet dreams about what technique one day they will be able to develop themselves. Not what it actually is.

So now, we hope we have taken out all the mystery, and you should be ready to look at how you can incorporate it into your own Supply Chain.

The Covid-19 epidemic has highlighted the vulnerabilities of the traditional physically offices and ways of working together with external partners and suppliers. It introduces many companies to start working remotely in supply chain. How will that influence the way we work together? What are the benefits and how would Supply Chain management have to ensure adoption of a new culture and new technology? Read this text and learn about working remotely in supply chain.

Higher productivity and job satisfaction
Statistics are indicating that nearly twice as many are working from home full time. That is nearly twice as many as ten years ago. Why so? People feel a higher satisfaction, productivity and organizational commitment as well as decreased stress levels and exhaustion. This could also be the case when working remotely in supply chain.

Hire the best people
Some companies have gone all the way and are no longer maintaining an office. They have people working all around the globe and are trying to exploit new technology to the fullest. The “all remote model” allows companies to hire the best people wherever they are. For some companies it would mean reducing cost because they would not have to pay high rent and perhaps also high salaries.

Effective culture
The company named GitLab has over 1000 people located in 60 countries around the world. They have no physical offices. They have not only experienced a financial impact but are also reporting a cultural impact. Normally offices breed politics. Intrigues, backstabbing, toadying and other forms of power brokering behavior thrive behind closed doors. Removing the walls fundamentally changes organizational culture. The assumption is, that a dispersed company committed to open discourse, with no political manoeuvring, will work more cohesively than a standard co-located company.

Harness and grow supplier innovation
Supply Chain innovation is a way to create new competitive advantages. Suppliers and partners play a key role. Best-in-class companies work closely with suppliers and partners long after a deal has been signed.

In most circles today, this is called “supplier relationship management.” But that translates to one-way communication (telling the supplier how to do it). Two-way communication, which requires both buyer and seller to jointly manage the relationship, is more effective. A more appropriate term for this best practice could be “alliance management,” with representatives from both parties collaboratingr to enhance the buyer/supplier relationship.

Doing this in a remote setting could mean building a “collaboration platform”. In this platform the supplier/partner could be onboarded/offboarded, it could be a way of working with problem resolution ensuring that the relationship stays healthy and vibrant. It could be a way of sharing progress on key targets. Not to forget to mention that it is a brilliant way of working towards Supply Chain innovation.

The potential is big. According to a recent survey done by State of Flux, 64% of the questioned companies use portals for handling contracts with suppliers. Only 21% use portals to manage the relationships with the suppliers and only 6% use technology to manage supplier Innovation.

Improve Joint Planning
Besides working remotely in Supply Chain towards innovation, a collaboration platform is also a great way to engage suppliers and partners in the planning, both on a strategic and operational level. Sales and Operations Planning (S&OP) processes and Supply Chain Risk Management have become increasingly important, when developing a shared view of how to run a company. A collaboration platform, that builds on real-time data, can support lowering business risk, improving visibility and communication so the decisions that are made are as effective as possible.

The Supply Chain of yesterday, where stable conditions, standardized products, low cost production and very inventory-based operations will most likely not come back. Instead we will have a Supply Chain of tomorrow, characterized by increased uncertainty, more customized products, a very conscious consumer. By applying technologies that will be part of the future industry you can support your Supply Chain organization in meeting these demands. You can learn more about this at Optilon SCC2020.

Are you wondering why you should implement AI to your Supply Chain? Supply Chain is more and more recognized as a key source of competitive advantage and differentiation. Companies strive to build Supply Chains that support company growth, increase transparency, streamline operations, and increases customer satisfaction. Implementing AI to your Supply Chain could become a source for creating competitive advantages. In this blog post, we will look into why Supply Chain AI creates competitive advantages.

The Supply Chain has a great influence on all cost drivers in a company. Optimizing how Supply Chains are operated opens for possibilities to win new market shares, boost sales and establish new business models. Focusing on the Supply Chain can improve the bottom line with 5-20% within 24 months (1). Supply chain AI, is still the “stuff of the future” for some organizations. Some of the world’s most significant leaders and thinkers are even suggesting that artificial intelligence is history’s biggest paradigm shift. Yet, we are still only at the beginning of the AI (r)evolution. Next we will look into why Supply Chain AI supports the company in gaining competitive advantages.

Why Supply Chain AI can support differentiation and lower cost
The Supply Chain is a network of suppliers, manufacturers, distributors, and retailers that act together to control, manage and improve the overall Supply Chain performance. Evaluating the performance of the entire Supply Chain can be a complex task, due to the complexity inherent in the structure and the operations.

No matter how the performance evaluation is done, the company must be able to differentiate against its competitors. Hence, the company must be able to offer value propositions that create an advantage over its competitors. Secondly, the company must operate at a lower cost than its competitors. This is where AI could become a competitive advantage in the Supply Chain, simply because the use of AI in the Supply Chain can both support differentiation but also lower cost.

Why Supply Chain AI can support the new Supply Chain model
The traditional model of the Supply Chain is fundamentally changing. We are shifting towards consumer-led, data driven, highly complex supply networks. The consumer increasingly drives innovation from the heart of the supply network, rather than being on the receiving end of the supply chain. Companies have to act in a more globalized world and balance the global with the local.

Companies have to be agile and willing to change by involving the whole organization. Companies have to put up a sustainable agenda internally as well as externally. They have to build a flexible and resilient culture that makes the organization robust toward big changes and chocs around the world. They have to provide visibility and transparency. Surrounded by an explosion of data, many Supply Chains are also struggling to leverage or take advantage of their data.

Why Supply Chain AI can solve real Supply Chain problems
These shifts in the Supply Chain demand more accurate supply chain planning and synchronization, and faster multichannel responsiveness that go far beyond the abilities of the typical workforce and infrastructure. It requires instant visibility, quick decision making and increased flexibility across the whole network. Also here Supply Chain AI can become a competitive advantage as it is possible, with the use of the right kind of supply Chain AI technologies to solve some of these real Supply Chain challenges.

Would you like to learn more about how you can create competitive advantages with AI then we encourage you to explore some of our content from Optilon Academy right here. 

Alis Sindbjerg Hemmingsen is a Thought Leader at Optilon. She has more than 25 years of experience within the Supply Chain field. Optilon has a long track record helping companies achieve competitive advantages by improving Supply Chain performance. Learn more about Optilon here. 

References:
(1) Arlbjørn et al;  “Supply Chain Management, sources for competitive advantages, 2018 edition.

Some of the world’s most significant leaders and thinkers are claiming, that Artificial Intelligence is history’s biggest paradigm shift. Yet, we are still only at the beginning of the AI (r)evolution. The question you might be looking for an answer to is perhaps: How will my company get started with AI in Supply Chain?

How to get started with AI in Supply Chain is a typical question that we hear from our clients.  The reason being, that to some Supply Chain Executives implementing AI, can seem as complicated as landing a space shuttle on the moon. But it does not have to be complicated. It is all about thinking big and taking a step by step approach. Even though some of the world’s most significant leaders are suggesting that artificial intelligence is history’s biggest paradigm shift, we are still only at the beginning of the AI (r)evolution.

It may be difficult to imagine a world in which Artificial Intelligence (AI) creates production drawings, controls robotics to perform industrial operations or improves Supply Chain performance. However, it was once unfathomable that a computer could beat a human at chess or drive a car autonomously.

To get started with AI in Supply Chain there are some basic questions you could ask:

  • Which Supply Chain problems are we looking to solve with AI?
  • How transformational are we looking to be, i.e., how big a step are we looking to take?
  • How automated or autonomous are we looking to become?

Make sure to solve real Supply Chain problems and take a step by step approach

Given the broad scope of AI and variations of use cases, it is vital to start by identifying what problems to solve (key objective) and what opportunities to pursue and learn through piloting.

o be honest, what we are also trying to say here is that the most important thing is to start with something rather than starting with the right thing. Embarking on the AI journey is a true learning process.

As Walmart’s CEO says, “AI is less like a project and more like an ongoing effort. As an ongoing effort, you want to figure out how AI can impact every aspect of your business. You want to understand how it affects your businesses’ core decisions, how it changes your overall strategy and business model, how you can get it into the hands of your frontline employees so they can better do their jobs, how it automates processes that don’t need human interaction and how roles in your organization need to change to best complement what AI can do for you”.

5 Steps to get Started with AI in Supply Chain

Hire new skills ahead of the curve – or train existing talent

Success depends very much on the trust and capabilities that the employees are able and willing to put into adopting new technology. When designed with people at the center, AI can extend companies’ capabilities, free up creative and strategic endeavors and help achieve more.

Start by using historical data

A technology partner can guide you through your journey, establishing a solid foundational baseline model on which to layer more and different types of data. A phased approach will help ensure a sustainable solution that meets your business objectives today and as your needs change. Data volume, data granularity, data quality, and data variety play a vital role.

Choose self-adapting models

To achieve the stability and adaptability required for operational use, it’s crucial to use self-adaptive models. These models will require less rework as time passes. Though model evaluation and tuning will always be necessary to a certain degree.

Ensure a digital culture that allows for experimentation

From a leadership perspective, it is essential to foster a culture that allows for experimentation and failure. Not all hypotheses will work or give the desired outcome.

Partner with a company which has practical experience with AI

In this approach, you are working with a partner firm that can help you with your AI journey. This partner can work with you to come up with the right AI strategies and projects, help you build out and test new ideas, and help you grow your internal capabilities. Not all firms can help you with this.

To make this work, you need to find the right partner. You should look for the following characteristics:

  1. A partner that can help you generate AI hypotheses that will work or have a chance to change your Supply Chain. This comes with experience in the area and a mix of business and technical skills. This can be difficult when growing an internal team simply because of its small size.
  2. A partner with a wide range of business and technical experience. As you develop your AI competences, you’re likely to need a diverse range of skills to help you come up with innovative solutions.
  3. A partner with a willingness to be transparent and share. You need to learn how AI works, and you need to own the overall solution moving forward. The AI journey will not be static.

How automated or autonomous are you looking to become?

Your decision on how autonomous the process should be as an impact on how the AI technology should be designed to work. Below you will find a description of the different levels:

Predictive

What if you could predict how your suppliers will perform? You can. The technologies available can interpret massive amounts of data from your Supply Chain and make educated scenarios on future performance based on past deliverables. It is a prediction, so it might not be 100% correct. It is all about using real-time and past data to create likely or ideal scenarios for a given situation. The ability for AI algorithms to learn from historic data sets transforms decision-making. It allows executives to work alongside AI to make more efficient, informed decisions.

Prescriptive

Imagine if you could automate the selection of suppliers or the route optimizations for your vehicles? This can be done with the technologies available. By inferring and producing simple predictive and transparent “if-then logic rules”, you can enable the automation of many of the decisions currently being made.

Autonomous

Imagine if you could predict product demand so that you could order the right amount of materials from your suppliers before you need them? With AI, you can. Low-power, low-cost IoT edge devices cannot process conventional, math-based predictive models. They must send data, often lots of data, over the network to a large prediction server and await a response. Logic-based models can be processed by virtually any computing device and used in real-time to respond to events as they happen. They can make informed decisions based on automated alerts.

We hope we have inspired you to bring AI into your Supply Chain and sincerely hopes it can improve your Supply Chain performance.

It may be difficult to imagine a world in which Artificial Intelligence (AI) improves Supply Chain Performance. But it was also once unfathomable that a machine could beat a human at chess. In this white paper, we will share with you how you can create your own approach to Supply Chain AI and how to implement it.

It may be difficult to imagine a world in which Artificial Intelligence (AI) improves Supply Chain Performance. But it was also once unfathomable that a machine could beat a human at chess. Since the Supply Chain has a great influence on all cost drivers in a company, optimizing the Supply Chain through Supply Chain AI opens for possibilities to win new market shares, boost sales and establish new business models. Supply Chain Executives from various industries are turning their heads towards AI. AI is still the “stuff of the future” and some are even suggesting that AI is history’s biggest paradigm shift. No matter what, the Supply Chain landscape is changing.

Supply Chain AI can solve real Supply Chain problems

The changing landscape of the Supply Chain demand more accurate supply chain planning and synchronization, and faster multichannel responsiveness that go far beyond the abilities of the typical workforce and infrastructure. It requires instant visibility, quick decision making and increased flexibility across the whole network. Also here Supply Chain AI can become a competitive advantage as it is possible, with the use of the right kind of supply Chain AI technologies, to solve some of these real Supply Chain challenges.

This whitepaper will give you the following:

  1. You will learn how and why you should turn Supply Chain into a competitive advantage with AI
  2. You will learn how Optilon helped a Swedish manufacturer save 22% on their logistics cost – by automatically correcting addresses
  3. You will learn how you can create your own approach to AI in the Supply Chain and implement it in your own organization

Download your own copy of the whitepaper right HERE.

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