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
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.
The consumer durables industry is experiencing significant supply chain threats, from product proliferation, demand volatility, intense global competition, evolving regulations and constrained supply brought on by a long period of sustained growth. By using supply chain management software to stay extremely efficient and resilient, companies can deliver the high-quality, differentiated products at the cost and service levels consumers expect.
For example, one threat is the demand for consumer durable goods is highly correlated to economic strength, making the industry largely dependent on disposable income. The global market has witnessed a surge in demand as developing economies provide more disposable income to more potential buyers. Disposable income can ebb and flow abruptly due to natural and man-made disruptions, leaving durable goods manufacturers scrambling to deal with excess inventory. Many durable goods also have a limited shelf-life due to constant advances in technology and ever-changing customer tastes. There is an opportunity for companies to use supply chain management software and anticipate potential market changes across multiple time horizons in order to mitigate risks and embrace opportunities. Risks and opportunities must be evaluated from a volumetric standpoint, as well as from their financial impact on the business.
It is vital that durable goods companies use supply chain management software to make effective planning and optimization decisions in two key ways:
- Capturing, verifying and combining information to enable rich analysis, decision making and rapid response to planned and unplanned events
- Developing robust integrated business planning capabilities supported by a comprehensive supply chain planning and optimization platform to reduce cycle and response times, maximize resource utilization and improve the effectiveness of the extended organization.
In addition to the one above, this eBook explores four additional areas where the greatest threats occur and presents opportunities in each one to help consumer durable goods companies stay competitive.
Manufacturers today face a long list of tough supply chain challenges. Supply
chain teams that rely on a jumble of spreadsheets, enterprise resource planning
(ERP) systems, and antiquated supply chain applications risk failure. Keeping data in
many different places and systems limits visibility and creates misaligned plans.
There is good news. A convergence of advanced solutions makes this a great time
to take your supply chain planning and manufacturing optimization software capabilities to the next level and solve the never-ending supply chain puzzle.
One area of improvement is Product Life Cycle Forecasting. Most companies recognize the importance of a repeatable and accurate forecasting process. Accurate forecasts help minimize inventory, maximize production efficiency, streamline purchasing, optimize distribution and ensure confidence in company projections. However, developing accurate product forecasts at all stages of a product’s life cycle can be very challenging, and requires the right supply chain and manufacturing optimization software.
A best practice is to assign a forecasting method based on a product’s life cycle stage to ensure the best possible forecast accuracy. However, most demand planning teams don’t have the bandwidth to evaluate each SKU/location level forecast for every forecasting period to determine which forecasting method is best. Fortunately, leading demand planning solutions can automate this selection by comparing forecast error by method and selecting the method that provides the best forecast.
This eBook, Solving the Supply Chain Planning Puzzle: Six Capabilities Every Manufacturer Needs, explores key areas where manufacturers should focus to realize supply chain improvements, including the use of supply chain master data management, sales and operations planning (S&OP), and advanced analytics.
Download this addition to the popular eBook, Practical Tips to Improve Demand Planning. You’ll receive eight more tips to help you blend the art and science of demand planning to drive improved customer service levels, reduce costs and support profitable growth.
Wholesale distributors sit in a precarious location when it comes to supply chain risk management. They “fill the gap” between manufacturers and retail/service customers by providing access to a wide assortment of products, industry knowledge and value-added services. In this role, wholesale distributors face many of the same supply chain risk management challenges as manufacturers and retailers, including:
- Product availability and time-definite delivery — having the right products when and where the customer needs them, and at the right price
- Reliably supplying a broad and deep product line of complementary items, alternatives, assortments, variations and lots, nearly always consolidated from multiple, potentially competing suppliers
- Consolidation and one-stop shopping
- Delivery and installation
- Managing substitutions for comparable or better fit, form, function, or lower price
- Managing succession where technology, regulation, competition, or fashion drive rapid product life cycles
Faced with growing costs, shrinking margins, new competitors and demanding customers, wholesale distributors must turn to advanced supply chain risk management capabilities to separate themselves from the pack including:
Advanced modeling capabilities to create a valid, forward-looking demand plan by product, customer, channel and geography, with more accurate forecasts throughout the product life cycle.
Inventory optimization capabilities to examine stock positions in each stocking location and to model interrelationships between stocking locations to reduce overall inventory levels while meeting customer service requirements.
Enhanced long-range planning capabilities to enable more accurate predictions of market changes, identify and mitigate potential risks, and empower a more predictable and repeatable integrated planning process.
This eBook, Building a Profitable Wholesale Distribution Supply Chain, presents several demand-driven supply chain planning techniques to help wholesale distributors get control of costly overstocks, stockouts and expediting charges and compete from a more profitable position.