Five reasons why APICS CPIM is a must for every ERP user and consultant

Business people on a meeting at the office

For the most part of my career, I have been known to be an active member of the APICS community. This means that, quite frequently, I interact with SCM practitioners and ERP consultants from different industries and with different professional backgrounds. During discussions, I am often asked what ways are best to acquire more in-depth-knowledge of the SCM/ERP domains.

Drawing from my 9 years of extensive, hands-on experience in the fields of Supply Chain Management and SAP ECC ERP implementation/support within the Pharmaceutical and FMCG industries, and a unique techno-functional skill set in SCM enabling technologies and Domain Expertise in the SAP PP/PP-PI module, I have compiled some advice for others.

When reflecting on numerous SAP ERP implementation/improvement projects, I keep falling back on the certainty and solidarity of the APICS certification: Certified in Production and Inventory Management (CPIM) which I believe was one of the main factors that led to my implementation success. Here are five reasons why I believe the APICS CPIM is a must for every ERP user and consultant:

  1. It harnesses your talents: It is widely believed that a lack in SCM talent is the reason behind many ERP implementation failures or less than optimal ERP performances – both the user/consultant sides. And while there is no one-size-fits-all kind of advice, the APICS CPIM certification has so many benefits to both users/consultants that I almost always advise people to pursue APICS CPIM because it is more about getting the best ROI of an ERP implementation.
  2. It follows a process-orientated approach: ERP commercial packages are all built to computerise the classical value chain activities of a company. These value chain activities are resembled in the modular structure that all commercial ERP packages follow. For example, business processes relating to Supply Chain Planning including, Sales and Operations Planning, Demand Management, Production Planning/Scheduling would be found under the Production Planning “PP/PP-PI” module in SAP ECC ERP. Likewise, other business process compromising a company’s value chain would be found as “canned” business processes across different modules of an ERP solution. The CPIM follows a process orientated approach to Supply Chain planning in a fashion that’s is almost identical to what is found in a SCM/Manufacturing Modules of and ERP package. This strategic fit between how ERP systems are structured and the process-oriented structure of the CPIM courseware is what makes CPIM the most powerful framework for SCM/ERP professionals in both user/consultant roles.

    cpimls2018-composite-plus-books

    Australasian Supply Chain Institute offers the CPIM Learning System for self study or together with Guided Learning sessions, available right across Australia

  3. It mirrors the same language as your ERP: The concepts and terminology of an SCM/Manufacturing module of an ERP system, such as MPS/MRP, BOM, phantom assemblies, time fences and forecast consumption techniques, just to name a few, that prove tricky for most users/consultants to grasp are explored in-depth in the CPIM courseware in an a clear and easy to follow approach with plenty of real life examples. This helps to better utilise system functionalities/features that are likely to be ignored due to the lack of underrating of such concepts.
  4. It builds confidence to apply a configuration effort: CPIM equips designees with knowledge that proves critical to guide system configuration efforts in the SCM area.
  5. It results in better, more streamlined implementations and a higher ROI for digital transformation efforts: Many companies the likes of BASF, DuPont and Intel have adopted APICS frameworks which helped them achieve organisational goals and increase the efficiency of their systems and people. It’s why over 110,000 other SCM practitioners around the world have attained the CPIM. Now it’s up to you. https://www.apics.org/apics-for-business/customer-stories

By Hatem Abu Nusair, M.Sc. Engineering, CPIM-F, CSCP-F, SAP Certified Application Associate, APICS Master Instructor

Haytem

Hatem is a Global Supply Chain Management & ERP Expert. He is currently the Production Planner at Tip Top, one of GWF’s divisions in Sydney, having moved from Jordan where he worked for a blue-chip international company that grew rapidly. Here, Hatem founded the Regional Middle East & North Africa (MENA) Supply Chain Department with the purpose of optimising Supply Chain performance across 13 subsidiaries through demand management and forecasting, capacity management, inventory control, and special projects, which entails: IT initiatives, ERP implementation, re-engineering of Supply Chain processes and other relevant matters.

Hatem is a qualified Industrial Engineer and a Master of Manufacturing Engineering candidate at UNSW. He is a Certified Fellow in Production and Inventory Management (CPIM-F) by APICS, a Certified Fellow Supply Chain Professional (CSCP-F) by APICS and a Certified Application Associate by SAP SE.

Hatem will be facilitator for Term 4 CPIM Part 2 Guided Learning for Australasian Supply Chain Institute where will be share his passion of streamlining supply chain processes, eliminating redundancies and utilising enabling technology to achieve operational goals with CPIM Part 2 students.

 

 

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Warehouse of the Future: Adopting Automation within Your Supply Chain – Part 1 of 2

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There’s currently a digital supply chain transformation that’s happening faster than the physical supply chain can react, requiring hybrid solutions in semi-automated environments where humans and robots work in tandem. New incentives to modernize operational capabilities should be added that capture efficiencies not previously achieved, while laying the foundation of a digitalized supply chain, continuously re-evaluating plans and evolving for performance.

Automation has been looked at as a solution to operational challenges, but trends in the marketplace signify an unprecedented rate of adoption taking hold in the coming decade. E-commerce is driving service expectations to levels that may not be achieved without the use of highspeed picking alternatives to manual operations. The aging generations in mature economies and challenges securing a loyal millennial workforce for repetitive tasks are creating increased disruption to staffing, forcing employers to look to automation to offset risk of labor shortages. Continued innovation has reduced costs of entry for automated capabilities, delivering improved business case justification for automation of many forms.

With such a strong justification, operations leaders across the globe are seeking ways to capture the potential that automation offers. Large scale transformation of distribution networks is capital intensive, however, and rarely warranted given the pace of change – however rapid – and market uncertainties. Therefore, we’re forced to look within existing environments to identify opportunities to introduce automation into existing facilities, combining automated equipment with manual operations, which requires the added complexity of orchestrating work across semiautomated operations. This scenario introduces the question of how to create an optimal environment allowing warehouse management systems (WMS) to orchestrate work across manual and automated areas to ensure efficient operations and maintain quality and service levels.

Part 1 of this 2-part blog series will take a deeper dive into today’s automation systems landscape and retrofitting today’s supply chain with automation. Part 2 of the series will cover disruptive technologies and digitalization and next generation capabilities.

The Current Landscape of Automation Systems

In automated environments, WMS often work alongside warehouse control systems (WCS) that manage the routing of containers as they traverse the material handling equipment, and warehouse execution systems (WES) which often have basic task management capabilities but not the level of control or optimization of a WMS. Below are a few general groupings of automation that typically leverage these entities in different ways.

  • Conveyors and sortation equipment receive destination / routing information from the WMS and leverage the WCS to divert containers to the appropriate location.
  • Pick execution equipment, including pick-to-light, carousels, or A-frames will receive pick instructions from the WMS and rely on the WCS to control the MHE. At times, these devices will manage task distribution and user interfaces for the performance of picks, though often, the WMS will manage the tasks through prioritization, and provide a common user experience (using consistent equipment where appropriate) for work performed in the pick modules and in bulk storage which feeds it (this work would include putaways, cycle counting, and picks where appropriate). Often, a WES has been sufficient for high volume outbound operations in retail, but with increasing emphasis on service levels, the advanced functionality of a WMS specific to inventory accuracy, pick module replenishment, cross-docking, and exception handling, the WMS brings a strong justification for a two-pronged approach.
  • Automated guided vehicles (AGVs) and automated storage and retrieval systems (ASRS) are well established, though adoption is increasing as more forklift providers offer driverless units. These units can take direction from a WMS (typical when involved in semi-automated environments) or WES (often used in ASRS racking systems where materials are commingled or when the vehicles can follow multiple routes to alleviate congestion). In either scenario, a WMS is often utilized to manage inventory allocation to customer and order.
  • Palletizers use visual determination for pallet building capabilities, but most in use require some level of consistency in product dimensions at the layer level. Advanced pallet building and robotic arm picking capabilities are increasing in use, but require some consistency in dimensions. Improvements in digital sensing will soon be changing the game here.

Retrofitting Today’s Supply Chain with Automation

Automation adoption will continue to accelerate in response to advanced service level expectations and e-commerce, with a focus on scale and speed, whereas a continued migration of margin focused businesses will drive adoption of driverless vehicles and high-density storage modules, especially in cold storage or mega-cities with high volume real estate. The introduction of automation into the existing facilities will bring challenges, such as:

  • Traditional footprints, system capabilities, and business processes will be challenged when faced with the introduction of conveyance, sortation, and pick execution equipment. A natural inclination to delineate businesses, and potentially create channel-specific operations, can result in artificially inflated inventory levels and/or reduced service levels in increasingly sensitive environments to failures in this area. Multi-channel capabilities can be achieved, often driving operational leaders to adopt pick execution capabilities to distribute work without recognizing the backlash to overall service levels of having disparate capabilities with traditional WMS controlled processes. The results, if not thought through, can have repercussions on inventory accuracy, exception management, and operational efficiency.
  • The introduction of driverless vehicles (AGV or ASRS) offer strong advantages in terms of scale and cost, ROI projections in union environments can often deliver break even points less than a year after go-live, even in new projects. However, legacy storage equipment and material flow can introduce limitations. The environments best prepared for the introduction of driverless forklifts are those managing full pallets in bulk locations (where dimensions are predictable and stack requirements are well documented), or those where racking capacity is capable of managing fixed locations that can be tracked in the WMS (if locations can be dedicated to a specific lot), or in the WCS (where multiple pallet locations can be managed by the WCS but the WMS can manage storage/allocation in concert with non-automated areas). In more complex operations, the WCS can take a more active role in determining work and allocation, but this often drives customization and redundancy with WMS functions specific to the needs of the business.
  • More robust, piece level management in advanced pick modules controlled by ASRS such as goods-to-person automation, offer advanced capabilities for high volume distributors and e-tailers. Often, this will require tote storage of product to standardize the storage capabilities, though concessions for non-conveyables must be considered. Integrating pick and pack operations with traditional areas of the same operation also force decisions on how to integrate inventory management with shipping capabilities, adding complexity to projects as WMS and WCS providers offer similar capabilities.

Check back for part-2 of the blog series, where we’ll go into more detail around the technologies driving next generation warehouse automation and digitalization and next generation capabilities.

For more information download the Future Series white paper, “Adopting automation in the digital age.”

About the Author

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Matthew Butler, Industry Strategies Director, JDA Software

More more information contact, 0414 966 232.

Visit www.jda.com

Building the Business Case for Digital Transformation of Supply Chain Planning

It seems like the phrase “digital transformation” is everywhere these days. There are as many definitions for digital transformation and articles on the subject. I like the definition provided in i-scoop’s online guide to digital transformation.

“Digital transformation is the profound transformation of business and organisational activities, processes, competencies and models to fully leverage the changes and opportunities of a mix of digital technologies and their accelerating impact across society in a strategic and prioritised way, with present and future shifts in mind.”

The digitisation of a supply chain involves creating a detailed data model that mirrors the intricacies of an actual end-to-end supply chain network. (Learn more in Technology Evaluation Center’s report, The Impact of Digital Transformation on the Supply Chain.) Done right, a digital twin will have enough detail to model the information, money, and product flow from acquisition of components, through production, distribution and fulfilment to the customer. Model element include forecasts, capacities, inventory positions, lead-times, resource availability, costs, revenues, and profits. Finally, the model needs constant updates of customer, production, purchase, and distribution order status to ensure analysis and resulting actions reflect what is currently happening in the physical supply chain.

The benefits of digital transformation are plentiful. Below are three tangible benefits of digitally transforming your supply chain:

Process Automation:

A very visible benefit of building a digital twin of your supply chain is the ability to use the information to automate routine process steps and free up resources to work on more value-added activities. Advanced supply chain systems have exception-based workflow and active alerts that when used in conjunction with user-defined limits can automatically process purchase, manufacturing, distribution and customer orders. Human intervention only takes place when plans, transactions, orders, etc. fall outside of defined limits.

Continuous Planning & Optimal Response:

Digitization of the supply chain unleashes the full capabilities of today’s powerful supply chain solutions leading to game changing competitive breakthroughs in customer service and value creation. One such capability is the application of algorithmic optimization in the areas of demand, inventory, supply, manufacturing, and transportation planning. The rich supply chain data available through a digital twin provides the foundation and inputs required for effective algorithmic optimization.

Another advanced supply chain capability is continuous planning. A supply chain digital twin contains up-to-date information on capacities and transactions. As new events take place (for example a new customer order, or a delayed replenishment) a planner can quickly determine an optimal response. Continuous planning and optimal response capabilities often lead to reduction in costs (manufacturing, inventory, transportation) and improvements in customer service (fill-rates, cycle-times).

Advanced Analytics:

Often the largest benefits from digitizing the supply chain come from new insights gained from the ability to conduct in-depth end-to-end analysis. The ability to analyze expected demand versus capacitated supply and determine financial impacts of multiple “what-if” scenarios provides the information needed to head off potential risks and fully embrace opportunities. A digital twin of the supply chain provides the information needed to make smart decisions on when to enter new markets, where to introduce new products, when and where to increase production capacity, and how to effectively compete. A digital twin provides a rich environment for running “what-if” scenarios of likely disruptions to determine the appropriate response before they happen. When the disruption does take place, a pre-established plan can be executed beating competitors to market.

How might a digital supply chain transformation change your daily life?

  • You have real-time, accurate information, eliminating the need for data manipulationPicture1blog
  • Collaboration on actual supply chain activities is online and in real-time
  • “What-If” scenarios and simulations are automatic, intelligent and include sufficient data to make informed decisions
  • Supply chain decisions move from calendar driven to continuous optimal response

A digital transformation of your supply chain can help you harness visibility, velocity and value and allow you to compete and win in today’s competitive marketplace.

To learn more about digital transformation, read Technology Evaluation Center’s report, The Impact of Digital Transformation on the Supply Chain.

 

About the author 

Hank Canitz PictureHenry Canitz is The Product Marketing & Business Development Director at Logility. To read more of Henry’s insights visit www.logility.com/blog.

Changing the Status Quo to Stay Ahead of the Amazon Effect

By Henry Canitz

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Planning teams face multiple dilemmas including promoting and supporting top line growth, containing cost, efficiently managing on-going operations and finding new ways to drive innovation. To complicate matters, supply chains are growing more complex as product proliferation and customer service expectations rise driven in part by the “Amazons” of the world.

Increasing complexity due to larger product portfolios drives demand volatility, more distribution channels and wider-spread supply chain networks. Traditionally, complexity required increasing inventory levels to buffer against the unknown, which in turn brought about more scrutiny from senior management as working capital increased. The answer, while simple to state, seems to allude many organisations: hold the right amount of inventory in the right locations to improve cash flow and provide better responsiveness to dynamic customer demand. Industry research and surveys point to Inventory Optimisation (IO) as a key capability to combat these growing supply chain stresses.

A form of prescriptive analytics, IO determines where and how much inventory to hold to meet a designated service level while complying with specific inventory policies. Through sophisticated algorithms, IO makes stocking recommendations to satisfy demand with the least amount of inventory. Inventory Optimisation can have a huge financial impact by minimizing inventory and freeing up working capital while guaranteeing the right stock is on hand, when and where needed.

Change the Status Quo through Multi-echelon Inventory Optimisation

Multi-echelon Inventory Optimisation (MEIO) goes a step further to simultaneously optimize stock locations and amounts across all inventory types in a supply chain network. Through advanced mathematical algorithms, MEIO models inventory flows through every interdependent stage and location of a supply chain to create an optimal configuration of internal and external inventory buffers to handleScreen Shot 2018-02-13 at 12.18.12 pm demand and supply uncertainty. MEIO can model component/raw, work-in-process (WIP) and finished goods inventory to ensure the right amount of each is stocked in the right locations enabling powerful postponement strategies.

MEIO’s rapid “what-if” scenario analysis to modify stock buffers (lowering some, raising others) and revamped policies and targets around the supply chain has shown in the real world to reduce inventory 10% to 30%, freeing millions (and in some cases, billions) in working capital that was trapped in excess stock and carrying costs.

Multi-echelon Inventory Optimisation, at its simplest form, enables the trade-off between service level and inventory cost modelled across the efficient frontier (see Figure 1). The Inventory Efficient Frontier shows that, for any status quo, it will always cost more to achieve higher service levels. However, through MEIO initiatives we can change the status quo and create a series of new curves that deliver a desired service level at less cost than the formerstate allowed.

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Figure 1: The Inventory Efficient Frontier

 

MEIO’s Impact on the Supply Chain

MEIO modelling compares actual demand to forecast, and actual receipt of goods to the plan for each SKU. MEIO models identifies forecast accuracy and safety stock issues while factoring historical forecast accuracy into the equation enabling predictive service level calculations. This fact-based approach to inventory targets allows you to right-size inventory by SKU and location.

MEIO strategic inventory modelling answers more difficult questions, i.e. where to make or stock products or the impact of distribution or manufacturing facility closures and openings. Strategic inventory modelling can provide quick, side-by-side scenario analysis to help make the right decisions. MEIO enables timely answers to complex “what-if” questions including impacts of channel changes and stocking policies across a complex and volatile omni-channel distribution network.

 

A Proven Three Step Approach to MEIO:

A simple three-step approach has been proven effective to achieving a successful MEIO initiative:

  1. Assess your organization’s capabilities from the perspectives listed below to understand your current state and to lay the foundation for a solid business case that delivers real-world results:
  • Inventory performance
  • Business process and inventory management expertise
  • Technology and organizational readiness
  1. Create a future state MEIO capability—process, technology, organization—that provides your supply chain team with a roadmap to success.
  2. Drive fundamental strategic changes that create greater resiliency and agility throughout the supply chain and establish a cycle of continuous improvement.

 

Time for Change

The benefits of Multi-echelon Inventory Optimization (MEIO) are well established by hundreds of companies of all sizes and in many industries. Leading organisations have shown that right-sizing inventory buffers and restructuring where and in what form inventory is held can drive powerful financial benefits. Inventory Optimisation provides a knowledge platform for better decision-making and enables organizations to use inventory as a lever for balancing supply and demand.

Amazon and other large e-retailers appeal to consumers on product offering, price and speed of delivery. They are able to effectively compete in these areas due to economies of scale that lower operating costs. To compete against the “Amazons” of the world, companies must find ways to simultaneously lower costs and improve customer service. MEIO is a modern weapon that does just that by enabling companies to selectively pick where to engage. MEIO allows companies to optimize inventory for the markets they want the battle to be fought in, for select customers, and select products.

 

About the author

Hank Canitz Picture

Henry Canitz is The Product Marketing & Business Development Director at Logility. To read more of Henry’s insights visit www.logility.com/blog.

BAEP’s Beaumont on understanding the economics of innovation

1515326886990by Julian Beaumont

For all the interest in self-driving vehicles, blockchain, 3D printing and the like, very little time is spent by investors in understanding the economics of new innovation and who might actually benefit.

Most investors in these hot industries can’t fathom anything other than a bright future. With the benefit of hindsight, however, investing in the latest hi-tech industry isn’t necessarily the easy path to riches most might presume.

Looking out from the 1920s when air travel was just taking off and the commercial airline industry was attracting much excitement, few would have been disappointed by its subsequent growth or importance to society. Investors in airlines, however, have been losing money ever since. Indeed, many airlines have gone bankrupt, including Ansett and Compass, and most have at some time required bailouts.

Consumers, however, have benefited, especially through lower flight prices over time. And to prove innovation isn’t the key to success, the supersonic Concorde stopped its super-fast flights in 2003.

Similarly, automobiles, plastics, personal computers and dot-coms were all once new-age industries that have caused carnage for investors. Picking the few winners that will emerge from the hype is often difficult.

From the dot-com bubble, Amazon is obviously one. Other big tech winners, such as Facebook, Google and Netflix, weren’t even listed at the time.

To date at least, Amazon has won with profitless prosperity, with arguably little profits to show for its success. Online retailing has been a tough place to invest.

Here, the value of the innovation accrues to customers rather than shareholders, as those in Surfstitch and Temple & Webster can attest.

Improved range, searchability, price transparency and convenience all clearly benefit the customer, but come at a cost to retailers – particularly due to increased price competition and expensive delivery costs.

Interestingly, it has been bricks-and-mortar retailers like Zara and H&M whose fast fashion and express supply chains have been among the most profitable innovations in retail in recent years.

Right now, investors are enthusiastic about lithium stocks, disruptive tech names, pre-profit concept stocks and bitcoin. Of course, that which is new and lacks much historical track record allows this optimism, with little in the way of disproof.

The key for investors is not to focus exclusively on the importance, societal value or seemingly exponential growth of the innovation, but to understand the economics behind it.

For example, if lithium is ultimately plentiful, it won’t be lithium miners that will prosper from the electric vehicle revolution. Nor will it necessarily be Tesla, as incumbent auto manufacturers can just as easily go electric.

Ultimately, whether any one company truly benefits from innovation comes down to whether they have something unique – a competitive advantage – that limits the extent to which the value of the innovation is competed away or otherwise passed on to the customer.

A common example is where the innovation makes for a unique product or service. Often forgotten as innovators are a number of world class Australian-based healthcare companies that include Cochlear, Resmed, Sirtex and CSL.

They spend big on researching and developing new and better medicines and medical devices.

Their products are protected by intellectual property rights such as product registrations and patents, allowing them to reap the profits of their innovation. Interestingly, investors don’t seem to attribute much value to R&D spend, perhaps because it usually represents an expense and subtracts for profits.

For example, CSL’s pre-tax profits would be almost 40 percent higher but for its R&D investment, which is rarely raised by those focused on its apparently lofty earnings multiple.

Other examples on the ASX include Aristocrat, which is spending more than $300 million annually on developing new market-leading slot machines and online social games; Reliance Worldwide with its Sharkbite push-to-connect plumbing fittings that offer ease and time saving in installation, and which are taking share by disrupting the market; and Costa Group, with its intellectual property in blueberries that improves quality and all-year-round availability.

As these cases attest, seemingly boring innovation can produce exciting profits.

Another less risky way to play innovation is by understanding where it can augment a company’s competitive advantage.

For example, the stock exchange ASX Limited is soon to replace its CHESS settlement system with blockchain technology that is expected to reduce costs and provide added functionality.

Another good example is Domino’s Pizza Enterprises, which operates a franchise of pizza stores. The company has very profitably leveraged new innovation to improve the efficiency of its operations and the cost, convenience and appeal of its customer offer.

For example, new ovens cook pizzas in less than four minutes, its GPS tracker helps speed up deliveries and grows the appeal of using its online ordering app, and DRU (Domino’s Robotics Unit) delivery robots save on costs and are fun for customers.

Of course, it is hard to get ahead using innovation that is readily available – all supermarkets now get the labour savings of self-service checkouts, for example – but Domino’s has been ahead of the curve in integrating new technologies into its customer proposition and thereby advancing its competitive advantages.

There are two takeaways. Firstly, to profitably invest in innovation often means looking beyond the latest sexy sector, including to second derivative beneficiaries. And two, looked at this way, the Australian market is full of innovative companies that are worthy of investment. After all, miners like Rio Tinto have already started using driverless trucks and trains, well ahead of Silicon Valley.

Julian Beaumont is the investment director at Bennelong Australian Equity Partners.

Source: Australian Financial Review


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Supply Chain Planning & Optimisation Projections for 2018 – Back to the Future

By Henry Canitz, Director of Product Marketing and Business DevelopmentPicture1

I get a kick reading “prediction” articles both prior to the year start and then again after the year is complete. When it comes to predicting the very dynamic supply chain management industry, those after year reviews can be quite amusing. For even more fun look back 10 or more years to see where we all thought the industry would be. Therefore, it is with a bit of trepidation that I toss my hat in the arena and make my 2018 supply chain planning and optimization predictions.

From all indications, 2018 should be a very interesting year for supply chains and supply chain practitioners. I think there are a few advanced capabilities that will grow in importance but I also believe there is a growing awareness that to benefit from advanced planning and optimization capabilities a company needs to build a firm foundation. Companies need a robust integrated and highly functional supply chain platform that is operated by highly trained supply chain professionals. In a way, we need to go back to fundamentals to move forward to the future.

The Rise of Cloud Deployment and Heightened Security

The large number of major data breaches in 2017 has been the focus of many C-level meetings. In an interesting reversal, SaaS (software-as-a-service) solutions are now viewed by most as the least risky deployment option and this will increase in the year ahead. 2018 will bring a renewed emphasis on security for supply chain facilities due to the growing awareness that data breaches can originate through almost any type of connected system and the fact that more facilities are being opened in unstable geographies.

The Shift to Continuous Planning

The pace of the supply chain is increasingly driven by ever-growing customer expectations (Amazon Effect) making end of the day, week, or month periodic planning processes, while still important, no longer sufficient for today’s operations. The concept of continuous planning where planners address opportunities and disruptions as they happen will continue to gain ground in 2018. These efforts could be part of a Sales and Operations Execution (S&OE) process or tightly tied to building more robust digital planning and optimization capabilities. To facilitate continuous planning process companies will start to move towards cross-functional teams working in a control-room type environment to address global disruptions and opportunities using advanced planning and optimization capabilities.

Digitisation

You can’t open a recent supply chain periodical today without seeing something about artificial intelligence (AI). Advanced analytics, machine learning, algorithmic planning, and AI will all continue to capture a significant slice of attention in 2018. In the year ahead, this will require supply chains to shift how they operate. With digitization of the supply chain, the role of the planner will become one of solving problems using advanced analytics to make business decisions not just supply chain decisions.

The Internet of Things (IoT) will continue to drive supply chain execution innovation as companies find new opportunities in the wealth of data available. For many, the current state includes difficulties interfacing IoT data in a high quality, repeatable fashion. Most companies just aren’t at the point where consuming this firehose of data is feasible.

Supply Chain Data Quality and Ownership

Supply Chain Master Data Management (MDM) is quickly becoming a critical foundational requirement and I expect to see more interest in this area in 2018. Much of the data used for supply chain planning and execution comes from outside of a company’s ERP systems. Ask yourself, where is supply chain data maintained at your company today? The answer might surprise you. Effective supply chain planning and optimization requires high quality and consistent data and the ability to easily and quickly maintain and update that data. Inconsistent and poor quality data will degrade confidence in recommendations. One of my mentors once told me that, “One awe S#?* wipes out 1000 Attaboys (or Girls)”. One piece of bad data that tarnishes a recommendation will be difficult to overcome. To take full advantage of IoT data, supply chain organizations will need to invest in their Supply Chain Master Data Management capabilities and platforms.

Talent GapPicture12

You continually hear from hiring managers that there is a “War for Talent” driving increased salaries, benefits, and turnover rates for supply chain professionals. This will not change anytime soon. Actually, with a shrinking baby-boomer workforce the war for talent is only going to heat up in 2018 (read more here: The Talent Gap and here: Imagine 2030: Supply Chain Talent). Companies will need to find additional ways to attract and retain talent like rotational programs, clear-cut career paths, advanced degree support, and support for professional training. Another way is to provide advanced supply chain platforms that allow team members to work on more value-added activities. Yes, the ability to hire and retain talent could be another way to justify an investment in new supply chain planning and optimization capabilities.

Taking S&OP to the Next Level

I have personally seen the significant benefits of a well-run S&OP process and I know other practitioners have as well. I may be going out on a limb here but I think 2018 will be the year of renewed efforts around putting advanced S&OP capabilities in place including the ability to;

  • Optimize the end-to-end supply chain based on constraints and business objectives (minimize cost, maximize profits, meet customer service levels, etc.)
  • Analyze the impacts of product-lifecycle decisions, especially new product introductions
  • Align and synchronise strategic, tactical and operational planning
  • Collaboratively plan with partners and customers

A year from now I am sure we will all get a good laugh by revisiting this piece, but I am hopeful that a least of few of my predictions will hold true. Here’s to a happy and successful 2018.

About the author 

Hank Canitz PictureHenry Canitz is The Product Marketing & Business Development Director at Logility. To read more of Henry’s insights visit www.logility.com/blog.

Machine Learning in Supply Chain Planning

Machine Learning in Supply Chain Planning - square

Machine Learning in Supply Chain Planning

Are we ready? And if so what’s involved?

The evolution to using artificial intelligence and machines that learn in supply chain planning is inevitable. In fact, there are early examples of the potential of AI to improve both supply chain planner efficiencies and provide better or optimized supply chain decisions. The question is, are we, as a profession, ready to embrace Machine Learning? If so, what does that mean and how do we get there?

Machine learning is a type of artificial intelligence (AI) that gives computers the ability to learn without being explicitly programmed. Machine learning computer programs teach themselves to grow and change when exposed to new data.

The latest Gartner Hype Cycle, published in July 2016, shows Machine Learning approaching the Peak of Inflated Expectations. Gartner predicts that mainstream adoption of Machine Learning is at least five years away, potentially ten. Still typing “Machine Learning AND Supply Chain Planning” into Google delivers more 16,000 results in less than half a second. This is a topic that supply chain planning people are thinking, talking, and writing about. In reality, the supply chain planning mindshare spent on Machine Learning is miniscule compared to that spent on reducing costs, improving customer service, and driving new revenue. Type “Cost Savings AND Supply Chain Planning” into Google and you get 2.5 million results.  One could argue that Machine Learning could contribute to meeting cost, revenue and customer service goals, but clearly there’s more focus today on basic supply chain planning capabilities like Demand Planning, Inventory Optimization, Sales & Operations Planning, and Supply Planning and Optimization.

One way to get started with Machine Learning is to look at your Demand Planning capabilities. For example, a “Best-Fit” forecasting algorithm automatically switches to the most appropriate forecasting method based on the latest demand information, ensuring you create the best forecast for every product at every stage of its life cycle. The algorithm evaluates forecast error each forecasting cycle and recommends or automatically selects the forecasting method that will produce the best forecast. “Best-Fit” forecasting is a basic form of Machine Learning.

Another example of today’s Machine Learning capabilities is found in software solutions that use algorithms to continually analyze the state of your supply chain and recommend or automatically execute plans to meet customer requirements. Optimization driven by algorithmic planning is an early form of machine learning that relies on a set of provided information (supply chain facilities and capacities, transportation lanes and capacities, customer service requirements, profit requirements, etc.) to automatically make optimal decisions.

One powerful example is the use of Multi-Echelon Inventory Optimization (MEIO) to automatically adjust inventory positions. The current inventory-to-sales ratio in the United States sits at 1.41, higher than any time since 2009 (right after the 2008 downturn). One cause of this glut of inventory is the emergence of omni-channel retailing. The “Amazon effect” of free and fast shipping, easy returns, and everyday low prices has changed customer expectations and the way products get into the hands of the consumer. It’s a struggle to keep up with the mind-bending rate of change that prevents companies from having the right inventory positioned at the right location to service customers. Companies that respond by increasing buffer inventory based on outdated information fail to attack the underlying issue of stock-outs, a fundamental shift in fulfillment. MEIO automatically seeks the optimal balance of inventory at the right locations, and provides optimal inventory parameters and positions by stocking location to establish optimal buffer locations and quantities. Embracing MEIO can reduce total inventories by upwards of 30% while maintaining or improving customer fill rates. MEIO is an example of basic Machine Learning that is available today.

Attaining the full benefits of Machine Learning will be an evolutionary process. We must learn to crawl, then walk, then run. The introduction of Machine Learning into most supply chain organizations will take years, but that shouldn’t stop supply chain professionals from planning for the future or taking advantage of some of the Machine Learning solutions available today. Implementing algorithmic planning and optimization technologies today builds the kind of expertise and experience that will ease the adoption of advanced Machine Learning solutions in the future.

Are you considering Machine Learning solutions?  If so, what steps are you taking to get there?

 

About the author 

Hank Canitz PictureHenry Canitz is The Product Marketing & Business Development Director at Logility. To read more of Henry’s insights visit www.logility.com/blog.

Is Your Supply Chain Planning System in the Cloud?

Supply Chain in the Cloud - 310 x 175My job requires a fair bit of air travel so I literally spend a good deal of my time with my head in the clouds. At 6’5” most airline seats are less than comfortable and provide very little leg, arm and shoulder room, so I often find the most practical activity during a flight is critical thinking. Yes, I might look like I am taking a nap but really I am deeply contemplating things like the current state of deploying Supply Chain Planning Technology in the cloud.

With the explosive growth in supply chain complexity and data volumes, a growing number of manufacturers, retailers and distributors of all sizes are all looking for more agile, easily implemented paths to better supply chain performance. Some have found it possible to enact powerful supply chain optimisations almost immediately, while saving substantial amounts of working capital and ensuring timely support for growth and collaboration over the long term.

They have chosen to deploy supply chain planning solutions in the Cloud.

Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources that can be rapidly provisioned and released with minimal management effort.

Today, the range of implementation options for supply chain planning solutions stretches far beyond traditional on-premises hardware and software. Some competitive-minded organizations question the advisability of lengthy and complex infrastructure projects. These supply chain teams harness the full potential of the internet by taking advantage of deployment models with names like Software as a Service (SaaS), Platform as a Service (PaaS), Infrastructure as a Service (IaaS), and managed services.

Cloud-based deployment alternatives remove IT obstacles and accelerate the launching of supply chain initiatives. However, are the advantages of cloud deployments for supply chain solutions real and worthwhile? I think so, and I have provided a few of the biggest benefit areas for having your supply chain planning software in the cloud.

Benefit #1: Affordability and Savings

  • Lower upfront costs – Initial capital equipment expenses are reduced and total cost of ownership shifts to a highly predictable annual expense line item.
  • Optimal licensing, hosting and services options – The wide variety of options provide a solution delivery profile that fits just about any organisation’s software procurement model and budget process.
  • Ability to reallocate valuable IT resources – Cloud-based deployments free up enterprise IT resources to focus on strategic initiatives and meet mission-critical demands rather than installing software updates and performing system administration.
  • Scalability to handle supply chain growth – It’s a significant competitive advantage to be able to activate capabilities as requirements grow and flex over time.

Benefit #2: Tangible Business Benefits

  • Accelerated ROI – Cloud deployments often deliver better cash flow and create a positive bottom-line impact much quicker than traditional models.
  • Greater agility to react to change – Because “the infrastructure is on the internet,” there is no hardware to implement and no software to install. Users can access the system from any location through web-connected laptops, tablets and smart phones.

Benefit #3: Reliability and Security

  • Less risk of unscheduled downtime – Resiliency and high availability are characteristics of a well-designed cloud-based deployment.
  • Robust security – The fear that storing business data on a cloud server could make it vulnerable to unauthorised access has been assuaged by the great security track record of hosting providers in securing and ensuring data privacy.
  • Expert administrative services – No one knows the ins and outs of system administration better than the solution provider organisation itself. The provider’s technical personnel are an essential resource for installing software updates, hot fixes, service packs and version updates in an optimum computer environment.

According to Gartner, cloud computing has reached a sufficient level of maturity to be in its “productive phase.” In fact, cloud-based solutions have proven enormously successful in a broad range of commercial applications, revolutionising the affordability and “adoptability” of solutions for a much wider range of companies. It is time for Supply Chain Planning solutions to join in this success?

As you consider the benefits of a cloud-based supply chain planning solution, conduct a self-evaluation by asking these questions:

  1. Does your current supply chain planning technology infrastructure fall short of the task of providing the supply chain planning capabilities you need?
  2. Is it difficult in your organisation to drive new capital investments for updated equipment and systems?
  3. Is your IT staff overwhelmed with user support issues and other system administration tasks?

If the answer to any of these questions is “yes,” then it’s time to find out how a cloud-based solution can accelerate one of the most rewarding business improvement initiatives your organisation can undertake: Optimising your Supply Chain.

Related Content:

 

About the author

Hank Canitz PictureHenry Canitz is The Product Marketing & Business Development Director at Logility. To read more of Henry’s insights visit www.logility.com/blog.

Removing the Two Barriers to Optimising Inventory

Removing the Two Barriers to Optimizing Inventory

Removing the Two Barriers to Optimising Inventory
Caught Between a Rock and a Hard Place

Henry Canitz – Product Marketing & Business Development Director, Logility

Supply chain leaders often find themselves in a difficult situation when it comes to the conflicting goals of improving customer service and minimising inventory. The omni-channel world we live in has driven customer service to new heights. Companies that don’t prioritise providing what the customer wants when they want it will soon find themselves losing market-share. On the other hand, product lifecycles continue to accelerate and the penalty for carrying too much of the wrong items leads to high levels of obsolescence. This isn’t a new dilemma, the balancing act between inventory and service has been going on since the earliest days of commerce. However, the penalties for bad service and/or high inventory are growing more severe and the space “between a rock and a hard place” is continuing to shrink.

Because of variability in demand and supply, increasing customer service levels can lead to higher levels of safety stock. Improving cash flow by indiscriminately reducing working capital dollars can result in slashing the wrong inventory, resulting in lower customer service levels.

While some supply chain teams have conducted inventory optimisation (IO) initiatives to raise service levels while lowering inventory cost, others worry that they won’t be successful in the effort.

There are two common barriers that can prevent an organisation from reaping the benefits of inventory optimisation efforts:

  • IO success can be undermined by reliance on:
    • Limited tools (such as modules built into, or bolted onto, existing ERP systems)
    • Inadequate solutions (e.g. error-prone, hard-to maintain spreadsheets)
    • Black-box systems (where calculations are difficult or impossible to validate)
  • An internal perception that understanding and implementing proven mathematical tools and business processes in order to streamline the creation of optimal inventory policies and targets is too difficult for the team to take on.

Overcoming these barriers is easier than you think and the benefits are too good to ignore. Companies that embrace Multi-echelon Inventory Optimisation (MEIO) achieve, on average, a 28% increase in inventory turns.

A simple three-step approach can remove barriers to achieving a successful MEIO initiative.

  1. Understand your current state and lay the foundation for a solid business case. Assess your organisation’s capabilities from the perspectives of:
    • Inventory performance
    • Business process and inventory management expertise
    • Technology and organisational readiness.
  2. Create a future state inventory optimisation capability—process, technology, organisation—that provides your supply chain team with a roadmap to success.
  3. Continue to drive fundamental strategic changes that create greater resiliency and agility throughout the supply chain and establish a cycle of continuous improvement.

Can you overcome the two common barriers to implementing inventory optimisation capabilities and get out of being Between a Rock and a Hard Place? Of course. We work with companies around the world who are driving significant value from their MEIO process.

Learn More:

 

About the author

Hank Canitz Picture

Henry Canitz is The Product Marketing & Business Development Director at Logility. To read more of Henry’s insights visit www.logility.com/blog.

Embracing digital disruption

tech image

Digitalization is changing the game for every industry—and every industry knows it. In one report dealing with the financial industry, 100% of business leaders surveyed said that they expect their sectors to be impacted by digital disruption in the future.

While almost 90% of manufacturers said they’d consider implementing digitally disruptive technology, only 28% think it will generate increased revenue, and only 13% see digitization as a path to a new revenue model. Manufacturers—and industries in general—are worried about the risks of digitally disrupting their current processes and technologies, especially if they’re already profitable.

System-wide change would cause trepidation in any organization, but it’s necessary to address those fears to be able to transition into the new age of hyper-connectivity. Right now, industries and companies need to figure out how they will embrace new technology, put aside their doubts, and make digital disruption work for them—before it’s working for one of their competitors.

Hear Infor President Duncan Angove discuss digital disruption and bridging the gap between what an analog company can deliver and what today’s digital customer expects.

 

About our Guest Blogger

Helen Masters
Vice President & Managing Director, Infor South Asia — ANZ & ASEAN

Helen Masters_VP ANZ & ASEAN_2_highres

Helen Masters is Vice President, South Asia – Infor ANZ & ASEAN where she is responsible for the development and promotion of global corporate products and seamless customer experience to augment market presence in the Pacific and ASEAN regions. These comprise Australia & New Zealand, Indonesia, Malaysia, Philippines, Thailand and Singapore.

In her role, Helen maintains new product lines with a focus on customer and partnership management and strategy-setting to grow business in Infor’s key micro-verticals in the South Asia region.

Prior to Infor, Helen was Vice President, Commercial and Emerging Markets, SAP; and Head, Emerging and Transformational Alliances Group, Cisco Systems where she was responsible for the launch of data business solutions.

Helen is a graduate of Macquarie University, Sydney, Australia and is also certified in Computer Programming.