As a process chemical company it is important to optimize and build advanced supply chain planning capabilities. You may have a current process in place, but are you experiencing the results that you need to prosper in this digital world? Is it time to maximize current supply chain planning investments and do more? To fully benefit from your strategic technology investments—and to take the next steps toward advanced supply chain capabilities—you must ensure your process chemical supply chain can embrace artificial intelligence (AI), optimize inventory, manage a complex supply chain and ensure a robust integrated business planning process.
These capabilities make it possible to implement an advanced supply chain process. With many moving parts in these complex supply chains, a scalable and unique process for each individual company is vital. Chemical process companies must possess strong capabilities in the following areas:
- Supply Chain Data Management
- Accurate Demand Forecasts
- Optimal Multi-Plant Scheduling
- Multi-echelon Inventory Optimization
- Integrated Business Planning
This white paper explores complex chemical process supply chains and the many moving parts that must be considered to succeed. With reduced inventory, increased forecast accuracy, decreased time-to-insight and rich, untapped data sources companies will be able to create their specific formula. In this paper we dive into the five key ways advanced supply chain planning capabilities and optimization capabilities that process chemical companies need.
Supply chain transformation involves improving an organization’s abilities to make decisions about which products to keep in stock, where to keep them, when to replenish them, how to improve
service levels for customers, how to liquidate excess stock in the most profitable way and how to quickly respond to changes in customer demand. Supply chain planning transformation can enable real-time tracking and analysis of customer and product data, decision-making based on predictive and prescriptive models, and the use of new capabilities enabled by artificial intelligence, machine learning, social media and the Internet of things. It can also automate daily operational decisions to free up talent to work on higher value activities.
Supply chain planning is complex and a transformation initiative requires getting off to a good start with the support of senior management and a business case that outlines the benefits as well as the impact to the organization. This is a multi-dimensional journey that must ask the four following questions:
- What new process capabilities do you want your future supply chain planning platform to enable?
- What new data sources do you plan to utilize with your future supply chain planning platform?
- What new solution capabilities do you want to adopt to enable your transformed planning process?
- What new people skills will be needed to analyze data, operate new processes and use new solution capabilities?
Agile, data driven, speedy and highly automated supply chain planning operations are becoming increasingly critical in today’s fast-paced, global business world. This e-book provides practical steps and a best practice roadmap to guide you on your transformative journey.
Supply chain disruptions happen – whether it’s the current COVID-19 situation, or future activities including other pandemics, unforeseen events or weather conditions such as hurricanes and tornadoes.
As a supply chain professional, you are in the power position of being able to learn from this experience and take actions now that can help your company be better prepared to face future supply chain disruptions, regardless of what shape they take.
So, will you be ready?
- Do you have a plan for adopting advanced analytics, artificial intelligence and machine learning in your supply chain operations?
- Do you have the ability to run multiple ‘what-if’ scenarios to analyze how your supply chain will be affected by different types of disruptions?
- Can you quickly sense a supply chain disruption, analyze options to mitigate it and execute the best response?
Logility can help. Our Artificial Intelligence (AI)-based digital supply chain platform can help with these things and more. For example, it leverages machine learning forecasts in scenario planning dashboards to let you easily see what’s going on and make the best decisions for your business. When supply chain disruptions happen, you can analyze and compare activities using a digital twin (a virtual mirror of your physical supply chain operations that lets you run multiple, what-if scenarios before you activate any changes) and make any adjustments in real time.
Explore this ebook, A Digital Transformation Guide for Supply Chain Disruptions, for eight tips to consider now to better plan and prepare for the future.
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
A recession is when the economy declines significantly for at least six months, and there’s a drop in five economic indicators:
- real gross domestic product
- retail sales
Since World War II the US economy has had 12 recessions with an average of one every six years, with the longest interval being 11 years. All leading indicators say we are clearly due for a recession. Is your supply chain ready? Is it a digital supply chain? Fine-tuning your demand planning processes NOW can be a big factor in your company’s ability to survive.
Additionally, companies that survive will focus on cutting costs, reducing capacities, consolidating suppliers, and freeing up cash by optimizing inventory – before the recession hits. Winners will:
- plan for the unexpected
- understand cash is king
- get and keep your financial house in order
- proactively investigate paths to navigate tariffs, including finding alternative sourcing, raising prices and buying ahead
Download and read this eBook, Winning with a Recession-Proof Digital Supply Chain, to glean three digital supply chain strategy tips to not only survive, but come out a market winner. We can offer one tip here – not investing in demand planning and other supply chain optimization improvements – is NOT the answer.
The business world is complex, and growing more so every day, but you can rely on sales and operations planning (S&OP) for help.
For example, with S&OP, you can plan across time horizons more clearly. Most companies have fragmented planning capabilities. Chances are your longer term strategic (financial) and tactical planning processes are not integrated with your shorter term demand, inventory, replenishment and manufacturing planning efforts. These planning efforts are often run by different groups, use different assumptions and data, and rely on different systems! Strategic plans are tough to incorporate into an aggregate S&OP plan, and both plans often do not reflect the latest supply chain network and operational data. The disconnects and misalignments can lead to missed opportunities, higher costs and increased operational risks.
ASCM (formerly APICS) defines S&OP as the “function of setting the overall level of manufacturing output (production plan) and other activities to best satisfy the current planned levels of sales (sales plan and/or forecasts), while meeting general business objectives of profitability, productivity, competitive customer lead times, etc., as expressed in the overall business plan.”
It can help face these challenges and more:
- long material lead times
- volatile component price fluctuations
- safety regulations and quality mandates
- complex manufacturing constraints
- increasing customer expectations
- demand uncertainty complicated by seasonality -high promotional activity
- product perishability
- frequent new product introductions (NPIs) and new distribution channels.
Download and read our short eBook, Smooth Sailing with S&OP, to gain some fresh perspectives.
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.
Today’s supply chains move at a ferocious pace fueled by multiple data streams from both internal and external enterprise systems, social networks, syndicated streams, Internet of Things (IoT) and more.
Advances in machine learning help transform this data to better predict customer needs, identify trends and deliver a more synchronized supply chain from product concept to customer availability. Inventory Optimization (IO) can have a huge financial impact by freeing up working capital while boosting service and minimizing inventory. Harnessing the insights of multiple data streams, Inventory Optimization determines where and how much stock to hold to meet a designated service level while complying with specific inventory policies. Through sophisticated machine learning algorithms, IO makes stocking recommendations to satisfy these needs.
Multi-echelon Inventory Optimization (MEIO) goes a step further to optimize stock locations and amounts across all sites and nodes in a supply chain network. The right MEIO approach automates the stocking and replenishment process as well as enables rich scenario analysis to automatically analyze tradeoffs between costs and service levels. It also uses machine learning to identify stocking patterns for seasonal products or new product introductions. Through robust visualizations, MEIO dashboards and event driven notifications help improve usability, user adoption and user efficiency.
This Advanced Inventory Optimization Handbook more deeply explains the importance of IO and MEIO strategies to help minimize costs and reduce risk while meeting customer service requirements, and provides examples of how to build these capabilities at your company, including a handy checklist if your organization already has an inventory optimization initiative underway.
Life sciences supply chain challenges include demand and supply uncertainty. Market complexity and regulatory restrictions. Mergers and acquisitions. Pricing pressures. And the need for new life sciences supply chain capabilities driven by mass customization and faster new product introductions. Having the right products at the right place at the right time can literally mean the difference between life and death.
To ensure high customer care while meeting corporate objectives, life sciences companies must digitally transform their supply chains. Why is a digital supply chain so important? It can help:
- Automate routine tasks and focus on more value-adding activities
- Minimize risk and maximize opportunities
- Optimize multi-plant production, scheduling and labor resources
- Effectively manage complexity through concept to customer supply chain optimization
- Synchronize and align company-wide efforts
In today’s hyper-competitive business environment companies in this industry need their life sciences supply chains to be an engine for growth and a means to drive customer satisfaction. The availability of big data and advanced solutions—infused with optimization, machine learning, and artificial intelligence—makes the timing right to digitally transforming to smart, connected and agile supply chains. An intelligent supply chain that uses advanced analytics to understand and respond to customer needs can speed up a life science company’s ability to develop, commercialize, plan, source, make, deploy and fulfill value-adding services and products. The transformation to a digital supply chain can be challenging, but Logility can help.
Download this eBook, Five Tips to Take your Life Sciences Supply Chain Digital, to get started today.
Many consumer package goods (CPG) companies face the same challenges as fashion businesses including high turnover in styles, colors and assortments and the need to meet regional and sometimes localized customer product requirements. To be successful, CPG supply chain teams must maneuver astutely around seasons, life cycles, assortments, promotions and retail demand signals across multiple planning horizons using the right SCM software. Synchronized planning across the short, medium and long-term horizons is absolutely crucial to profitability and competitiveness.
This eBook, Defining the Right Supply Chain Strategy in the CPG Industry, examines the role a comprehensive planning system in a SCM software platform plays in building the right strategy for every phase, including long, medium and short-term horizons.
Even under the best circumstances, developing production/sourcing plans three, six, or nine months into the future with a high degree of confidence is difficult for many CPG teams. Huge sales and margin impacts hang in the balance. Once orders are placed, the ability to nimbly respond to changes in demand can mean the difference between profit and loss. A comprehensive SCM software platform is essential in mastering long-, medium- and short-term business planning to ensure the right moves are made at the right time to maximize your business strategy.
The question you need to ask is, “Does your planning process unite the functions in our organization, make it easy to cooperate, simplify hand-offs, build trust, provide an accurate vision of the future, facilitate supplier collaboration, and allow you to evaluate likely contingencies to find the best strategy going forward? If the answer is “no,” download this eBook today and start to change your situation.