Supply chains are moving faster and faster and the complexity of data needed to manage them is growing exponentially. To quickly turn tremendous volumes of data into actionable insight, an increasing number of organizations are now turning to innovative digital supply chain planning platforms that are powered by artificial intelligence (AI) and machine learning (ML).
On its own, supply chain planning (SCP) provides the critical set of business processes that companies rely on for optimizing the delivery of goods, services, and information to their customers. Focused on balancing supply with demand, SCP manages real-time demand commitments, “what-if” scenario analysis, inventory optimization, and sales and operations planning (S&OP), among other functions, according to Gartner.
With increased speed in the supply chain, skilled labor is more difficult to find and retain, and customers are harder to please. Add in trade wars, economic uncertainty, and the risk of supply disruption to the equation, and you wind up with a perfect storm of supply chain challenges that—when combined with other hurdles—require the right mix of software and advanced technology to solve.
When companies incorporate artificial intelligence and machine learning into their supply chain planning activities, everyone wins. Layering advanced technologies like AI and ML into supply chain planning creates new capabilities and propels companies that want to stay ahead of the rapidly changing business landscape. Innovative digital supply chain platforms that are powered by AI and ML, combined with SCP can uncover hidden opportunities, identify potential risks and accelerate decision making – from product concept to customer availability, and all points in between.
In this Making the Case guide, we explore the opportunities that these advanced technologies offer and show how you can get the most out of the potential they offer. AI and machine learning are powerful tools that will continue to propel the supply chain, and in partnership with valuable supply chain practitioners.
Supply chain organizations are still at the early stages of making the most of advances in digital supply chain technology, including the use of a digital twin. In many ways, you could argue the industry is mostly using the astonishing capabilities of computing and internet connectivity to do what they did before – just faster and cheaper. With a more connected world, there is an increased amount of supply chain data available. This increase in data is incredible but also can be daunting. That’s why smart companies focus not just on gathering data, and figuring out how to filter and analyze it, but how to use it to make better, faster, more informed decisions with a digital twin. Since data management is not usually the core business of companies engaged in manufacturing and/or selling goods, most need to rely on a trusted technology partner (such as Logility) to help them make the most of this brave new world.
Artificial intelligence and machine learning can handle more parameters than most are aware. Typically, there’s more than one “right” answer, and the software helps get the best answer for the current strategy. With this artificial intelligence, companies can then employ a digital twin that will assist in analyzing different scenarios. With these scenarios available, companies can explore the impact of changes with little effort and no cost.
Accurate, up-to-date data is vital to achieving these advanced insights. This affects how long it takes to identify something that happened in the supply chain that needs to be addressed – or something that is likely to happen. With readily available insights companies can then use AI, machine learning and advanced analytics to solve problems.
With this increase of information and artificial intelligence, a refined plan is no longer a nice-to-have, but a necessity. Companies are no longer limited to monthly, weekly or daily reports, they can refine their strategy through the entire process, up until the product is headed to the customer.
New Digital Supply Chain Video
The supply chain systems of the past are not enough in today’s fast paced world, and your company needs a digital supply chain platform that supports the speed of business – fast, efficient and transparent.
A single, end-to-end digital supply chain platform is vital for businesses today to thrive and survive. It can help manufacturers, suppliers, retailers and distributors make smarter decisions faster.
How do these platforms work? They start by using digitalization to take advantage of your investments in foundational and advanced supply chain planning and optimization capabilities to help you make better decisions faster. With this in place, you can change your business model to generate new revenue, increase efficiencies and offer greater business confidence.
Digital models reflect the physical network allowing you to leverage Artificial Intelligence, Machine Learning, Collaboration and business scenario analysis to boost customer service, accelerate your time to market and replace inventory with information. Through digital supply chain capabilities your business can help increase revenue, lower costs, reduce risk and boost service as you make better decisions, faster. A digital supply chain enables process augmentation and automation freeing up resources to focus on other value added activities. A digital supply chain also improves your ability to seamlessly collaborate with customers and partners. Digitizing your supply chain allows you to build a “Digital Twin” or an electronic representation of your supply chain increasing visibility and enabling the foundation for advanced analytics including simulations and multiple “what-if” scenarios.
The digital supply chain is the next step in the evolution of modern supply chain management and Logility can provide the visibility and rapid data discovery needed for continuous end-to-end supply chain planning. Watch this quick video to learn more.
One of the key challenges facing organizations today is the digital supply chain talent shortage of candidates. Today, the ideal employee has both tactical/operational expertise and professional competencies such as leadership and analytical skills. Current statistics show there is currently one highly qualified supply chain candidate for every six job openings. The demand for talent with these highly sought after skills is high and growing fast. And let’s face it, empty seats on your supply chain team negatively impact your performance.
This eBook, Attracting and Keeping Supply Chain Talent, contains highlights gleaned from industry experts who know a thing or two about finding and hiring good team members.
Karen Smith, Vice President, Global Supply Chain Operations, Kontoor Brands
Sean Willems, PhD, Haslam Chair in Supply Chain Analytics, University of Tennessee
Scott W. Luton, Founder, CEO & Host of Supply Chain Now Radio, former ASCM Atlanta Chapter President
Topics and tidbits covered in the eBook include:
- How to make your company more attractive to the best supply chain talent
- How to approach the career expectations of Millennials and post-Millennials
- The impact of digital transformation on supply chain career paths
It also provides different perspectives on the question: what factors have had the greatest impact on the digital supply chain talent shortage at different organizations, including the requirement for both business and analytical skills, the general lack of availability of qualified resources; the negative perception of supply chain as a profession; and the differing career expectations of the Millennial and non-Millennial generations
One of the key challenges facing organizations today is the supply chain talent shortage of appropriate candidates. Many companies report that finding the right combination of skills for entry level to executive positions is hard to find, yet most companies do not have a talent management strategy to support their future needs.
Entry level roles require a mix of tech-savvy skills with an aptitude to learn, combined with strong decision-making and communications skills. With six job openings for every supply chain candidate, it’s no wonder there is a supply chain talent shortage, and that management and advanced analytics degrees in undergraduate, graduate and master’s degree programs are popular areas of study across many major universities. And it’s more than entry level roles, especially as Baby Boomers retire form mid-management to executive roles. Those candidates must have both strategic/tactical/operational expertise and professional competencies such as analytical and leadership skills.
A brief poll of our webcast registrants revealed:
- 64% of registrants said that they currently find it more difficult to recruit and retain supply chain talent than in the past.
- 36% cited the requirement for both business and analytical skills as a key factor impacting the talent shortage at their organizations.
- 31% rated strategic/critical thinking skills as a the top skill they are seeking for their supply chain staff.
Hear our panel of industry experts discuss the key challenges facing organizations as they compete to attract and retain top talent for supply chain and retail planning roles.
Listen to this webcast now and learn:
- What to do at your company to attract the best candidates despite the supply chain talent shortage
- Why you must consider Millennial and post-Millennial career expectations
- How supply chain career paths are impacted by digital transformation.
Panelists include:
Karen Smith, Vice President, Global Supply Chain Operations, Kontoor Brands
Sean Willems, PhD, Haslam Chair in Supply Chain Analytics, University of Tennessee
Scott Luton, Founder, CEO & Host of Supply Chain Now Radio and Advisor, TalentStream
Every supply chain team must optimize inventory investments with service level performance. Without proper balance, organizations run the risk of excess inventory and trapped working capital, or too little inventory and lost sales. Finding the right balance is critical to boosting service levels while reducing inventory costs. This research examines the current state of inventory optimization adoption, identifies the top pressures driving inventory optimization initiatives, and provides a breakdown of capabilities by industry.
Through advanced “what-if” scenario evaluations based on the use of Digital Twins, Multi-Echelon Inventory Optimization (MEIO) has shown to reduce inventory investment between 10 – 30% while improving customer service levels.
An overwhelming majority of respondents rely on their ERP system (77%) to manage inventory. This highlights a significant opportunity for companies to further reduce working capital through the use of more advanced solutions.
Inventory Optimization Study Overview
Logility partnered with Elastic Solutions, a leading provider of B2B marketing research services, to conduct a study – Leveraging Inventory for Profitable Growth – and now offering you you the results in this free survey! 100% of survey respondents participated voluntarily.
Over 100 survey respondents, representing more than 10 industries, participated in this study. All are located in North America.
One key takeaway: Multi-Echelon Inventory Optimization – the ability to optimize raw material, WIP, and/or finished good simultaneously across all nodes in the network– is how 48% of the respondents currently optimize inventory. Only 3% stated that they don’t perform any kind of inventory management or optimization.
Download the entire 13-page report to learn more.
Evaluating demand forecasting analytics solutions can be a confusing and complex process. However, knowing the right questions to ask can greatly reduce the risk of selecting the wrong solution provider.
Over the last decade, advanced analytics has been at or near the top of the list of priorities for many executives and information technology professionals throughout the world. Organizations have made major investments in database technologies including CRM, ERP and other transactional systems that run the operations of a department, division and subsidiaries. As a result, most organizations have access to valuable data and are looking for ways to leverage demand forecasting analytics for a competitive advantage. Transforming raw data into meaningful and useful information enables more effective strategic, tactical, operational insights and decision-making.
A recent survey revealed that organizations that place greater emphasis on the solution provider evaluation process tend to have a more successful project. Not surprisingly, these organizations also consistently outperform their competitors in the marketplace. The true value of a solution for demand forecasting analytics lies in the insight it provides on business operations and the opportunities it creates for better decision making. Understanding the business requirements for an advanced analytics project is crucial to the selection strategy that aims to align with the overall business objectives while addressing the needs of business users. Failure to integrate business requirements into the selection process can result in substantial cost overruns or, even worse, project failure.
With hundreds of advanced analytics tools available in the market, a sound selection strategy that integrates business requirements accurately is more important than ever. Download this white paper, Five Questions to Ask before Selecting an Advanced Analytics Solution Provider, to help you on your journey.
Clarios, formerly Johnson Controls Power Solutions, is the world leader in smart energy storage technologies for the automotive industry – globally, one in three vehicles is powered by its batteries. Hear how Clarios integrated a complex ERP landscape to improve the quality of its supply chain data for demand and supply planning using Logility.
Clarios, formerly Johnson Controls Power Solutions, is the world leader in smart energy storage technologies for the automotive industry – globally, one in three vehicles is powered by its batteries. Hear how Clarios is using Logility to reduce costs, deliver to customer expectations and continue to improve performance in a complex supply chain network.
Machine learning is a type of supervised or unsupervised artificial intelligence where software has the ability to learn without being explicitly programmed. For more than a decade, companies have used the power of machine learning to improve supply chain planning efficiencies and develop optimized supply chain decisions. Automatic model switching to improve forecast accuracy is just one of many examples of the early use of machine learning to continually tune the digital supply chain and optimally leverage physical supply chain network performance.
Early results are driving the hype of machine learning applications to a fever pitch and there’s no question that machine learning is a topic that supply chain practitioners should be actively investigating. The real question is, “Are we, as a profession, ready to embrace machine learning in an unsupervised fashion”? If so, what does that mean and how do we get there?
Three areas where you can start with machine learning in your supply chain planning efforts are:
- Forecasting: Forecast accuracy is a top challenge for many companies and a quick win application of machine learning could be the automated adoption of “Best-Fit” algorithms across your portfolio.
- Supply Chain Optimization: Another high value opportunity of machine learning is gained by continually analyzing the state of your digital supply chain and automatically tuning planning parameters to meet customer requirements while maximizing company objectives.
- Multi-Echelon Inventory Optimization (MEIO): Using the latest demand and supply information, machine learning can enable a continuous improvement in your company’s ability to meet a desired customer service level at the lowest inventory investment.
This eBook defines machine learning in greater details, explores its use as part of an overall supply chain planning strategy, and further recommends where and how to get started.