If you want an educational demo of our network design solution using our LogicNet Plus XE product, check our video on YouTube.
The video gives you an introduction to the concepts of network design and takes you through a case study. The focus of this video is on traditional network design-- locating the optimal number, location, size, and territories of warehouses.
IBM recently came out with its annual "Next Five in Five" report highlighting five innovation predictions for the next five years. One article that picked up the story pointed out:
IBM, the world's largest provider of computer services, is one of the
few big corporations investing in long-range research projects and
invested $5.8 billion in research and development last year, accounting
for 6.1% of revenue, according to the company's financials.
This investment in research helps benefit our supply chain clients. For example, IBM recently came out with a new study and white paper, "New Rules for a New Decade: A Vision for Smarter Supply Chain Management." SupplyChainDigest picked up the story and provides a nice summary in addition to the IBM material. The study found that supply chain visionaries have significantly better financial returns by more quickly predicting demand and optimizing and analyzing their supply chain to take advantage of this in closer to real-time. The chart below summarizes the key capabilities of different types of supply chain organization. Of course, there are significant advantages to getting your supply chain to the "Planners" level.
It is increasingly important to have the analytics
that enable better decision-making, says Douglass. But an area where
supply chain managers need to improve is scenario planning— assessing
different alternatives based on risks.
“It’s like having different playbooks with different response profiles for different contingencies,” Douglass explains.
Overall, IBM is investing heavily in supply chain thought leadership to help our clients run better supply chains.
More and more, managers recognize that their business needs multiple supply chains.
As an example, Supply Chain Management Review (Nov 2006) reports on a example that highlights a classic trade-off:
Victoria’s Secret has created two different supply chains for the two sorts of products it sells.Its supply chain for high-fashion items like lingerie has been designed to get products into it stores as quickly as possible to maximize sales of short-lived, high-margin goods; its supply chain for basic items like socks has been designed to products on its shelves at the lowest cost.
In this case, you can air freight one set of products and ship the other set by ocean.The high-margin, high fashion items easily absorb the extra transportation costs while the low-margin, low cost items can easily absorb the extra inventory carrying cost.These products might also flow through different distribution points within the network.
Optimization-based supply chain planning tools can help create the best design and plan for each of these supply chains.
What is interesting, though, is that managers no longer have to figure out how many supply chains they have and then come up with the right design for each one.
The advances in the planning tools now allow the managers to use optimization-based tool to help figure out how many supply chains they should have and what they should look like.This process can lead to interesting new insights into the business.
For example, you benefit from unique supply chains based on product, on different seasons, on different brands, on where the product comes from, on different regions, on different customer segments, on different channels, and so on.
Creating different supply chains can lead to significant increase in overall profit margin, increase in customer service, decrease in cost, and an overall improvement of the supply chain’s ability to meet the firm’s strategic goals.
To monitor and manage this additional complexity, more firms are relying on a tighter integration with operational data.This allows you to make adjustments in real-time. Gone are the days of looking at the design of your supply chains once every couple of years.
All of this taken together means that firms gain a competitive advantage by carefully determining their supply chains and staying on top of them.
1. You can find savings with network modeling. The team quoted that they were able to find $10M in savings just in the initial modeling. In fact, the speakers stressed the tremendous value in just building a baseline model. This allows you to uncover savings, but to also challenge preconceived ideas.
2. Sensitivity analysis is valuable. After narrowing down choices, the team did analysis on the impact of higher oil prices and carbon emissions to rank the solutions.
Bob Ferrari noted that this work can be done with remote teams:
The combined project team performed this task over three months on a
virtual basis, without the need to meet face-to-face until just before
final recommendations. This was an important reinforcement that a
virtual team process can work, with selection of both the right
players, and a single point-of-contact for each constituency.
The speakers also mentioned that through the years they were able to build various models that focused on different parts of their supply chain from distribution to manufacturing.
Last week, IBM hosted another Connect to Win event for business partners at it's northern California IBM Innovation Center. The event focused on business analytics and featured IBM Distinguished Engineer Jeff Jonas, a dynamic and highly sought after speaker. Among his many accomplishments, he is known for developing the technology used by the Las Vegas gaming industry featured in the book "Bringing Down the House", the recent movie "21", and numerous documentaries on the Discovery Channel, Learning Channel and the Travel Channel.
Following the keynote by Jeff Jonas, IBM hosted a panel discussion. Some 30+ partners came to learn how to leverage analytics in their offerings, and naturally a wide spectrum of analytics sophistication was represented, generating a vibrant discussion on everything from Smarter Planet to Artificial Intelligence to Decision Management.
The panel was made up of:
Jeff Jonas, IBM Distinguished Engineer, Chief Scientist, IBM Entity Analytics Group
Jeff Kreulen, Senior Manager, Senior Technical Staff Member, Services Oriented Technologies, IBM Almaden Research Center
Thomas Dong, Senior Product Marketing Manager, ILOG Optimization and Analytical Decision Support Solutions
Daniel Mannisto, CEO, Applied Analytix (IBM Business Partner)
During the panel discussion I had the opportunity to first share IBM's vision for business analytics, using an adaptation from Tom Davenport's book "Competing on Analytics", to explain why, how and where IBM has invested $14B since 2005 in business analytics. Several partners thanked me afterwards for presenting this visual, as it provided them with a blueprint for how they might evolve their own analytics capabilities.
In fact, this gave me an opportunity to define a new software category for many - Advanced Analytics, which applies statistical and mathematical techniques to provide forward-looking capabilities, beyond the insight commonly extracted from historical data and information. It can be viewed as a subset of Business Analytics, and provides an interesting convergence opportunity, between the IT-based "analytics" world, and this emerging world previously reserved for specialists in statistics and Operations Research-related disciplines (Management Science, Industrial Engineering, Financial Engineering, Systems Engineering, Applied Mathematics, etc.). As the business world evolves its analytics agenda beyond business intelligence and performance management capabilities, the desire to not only look back in time, but forward in time as well, is driving awareness for Advanced Analytics - and creating many opportunities for SPSS and ILOG Optimization at the point of business impact.
To learn more about Advanced Analytics for a Smarter Planet, start here:
If you’ve paid much
attention lately, the topic of “smart supply chains” is currently in vogue. But what is a smart
supply chain, exactly? And are you trying to build one at your
company?The idea of smart or
intelligent supply chains has been around for some time – more on that in just a
bit. However, part (but by no means all) of the recent reanimated discussion
about smart supply chains has come from the efforts of IBM, which has made
“smarter” supply chains one of its key marketing messages.
report IBM released last year summarizing surveys and interviews with hundreds
of senior supply chain executives (promoted in many venues since then, including
SCDigest), IBM said that “To deal effectively with risk and meet your business
objectives, we believe supply chains must become a lot smarter,” and called on
Chief Supply Chain Officers to start building to that new vision right
now. Read the full story online at SCDigest.com.
Gartner RAS Core Research Note G00172071, Andrew White, 17 November 2009
"This research updates users on IBM’s overall supply chain management (SCM) product strategy, which has matured in terms of positioning and product management/strategy since its most recent Ilog acquisition in 2008. We highlight the finalized IBM SCM product portfolio, and highlight how this rationalized portfolio aligns with the SCM trends IBM exposed in its most recent Executive Survey, which also aligns closely with Gartner’s research."
To read the note visit: http://imagesrv.gartner.com/media-products/pdf/reprints/ibm/external/volume4/article31.pdf
We've recently written an educational book on network design. This book is aimed at both those who do network design projects for a living and for use in the classroom.
For those who do these studies, you will develop better intuition on how these models are solved and new ideas for modeling your supply chain. It can also be a good guide for people who are new to the discipline within your organization.
For those of you who teach, this book will introduce your students to the topic and provide them with a wide ranges of realistically sized models to work on. You can use with the IBM ILOG LogicNet Plus XE software from the academic initiative to allow your students to learn the topic with the use of commercial software.
There's a big difference between impulse buying and purposeful buying. Most of the Retail customers we met with at NRF 2014 were focused around products designed for purposeful buying behaviors and how to create a seamless customer experience in a very fragmented omni channel world.
"Impulse" product lines are very different - they appeal to the emotional side of consumers. So, how will specialty retail brands compete effectively in an increasingly digital, e-commerce world? As automated checkout and online purchasing increase, how can these Retailers continue to exploit the emotional "buy" when products like candy, for example, are no longer in front of us as we shop? From a retailer's point of view, impulse items bring in high margins—50 percent or better on some SKUs—and have a quick turn over rate (homechannelnews.com/article/impulse-item-guide). How can they make up for this loss of revenue? Thoughts on this?
As banks and financial institutions start to emerge from a prolonged financial downturn, they face a host of challenges. Disruptive forces continue to ripple through the finance industry changing the market and impacting the businesses, such as:
• New regulations • New capital requirements
• New technologies
Optimisation technologies have become key tools in making important business decisions that increase competitive advantage. Optimisation, through the use of advanced mathematics and computer science techniques, is used to assist organisations with solving their complex business problems. The models which capture trade-off between optimum resource allocation and risk minimisation are gaining increasing importance in Banking, Portfolio Construction, Asset and Liability Management, Trade Settlement and Clearing and Cash Management. Recent developments and growing applications of quadratic optimisation, stochastic optimisation and robust optimisation in these domains and the role of modelling systems and solvers will be presented and discussed.
BENEFITS OF ATTENDING:
Understand the role of optimisation in financial analytics and gain an understanding of the leading issues of financial analytics Learn about the latest thinking and practices in the domain of Portfolio Optimisation and Asset and Liability Management Learn how companies have been able to use optimisation technology to help determine how to most effectively allocate capital, balance business risks, uncover novel solutions for their customers and gain insights into their toughest challenges for maximum return with limited risk
Correctly positioning and buffering inventory can help you create a more flexible supply chain with lower costs.
In the military, it is common practice to pay suppliers on a "cost plus" basis. Effectively, this makes all the suppliers a "make to order" location. That is, the suppliers can only make product when there is a firm order. There is no mechanism for the supplier to make product in advance, sit on safety stock, and provide faster service.
Keeping helicopters flying is not trivial. They are made up of many parts and operated in tough conditions. Many of the key parts(drive shafts, sycn shafts, blades) require many sub-components and must be made with specialized materials in a high-precision manufacturing environment.
The supply chain for these key parts can be very long (measured in many months), and it is expensive to keep enough of these items around as spare parts.
With the current system, each key part had to either be stored in inventory as safety stock (waiting to be needed) or the the military had to wait for the supply chain to produce another (creating a backlog of demand and a helicopter that was grounded). Neither alternative was great.
A better solution is to optimize the placement of strategic buffers in this supply chain. The chart below on the left shows the existing supply chain. The yellow box on the right represents the customer (the military) and a key part. The gray boxes to the left represent all the steps in the supply chain needed to make this particular part. You can see the complexity of the supply chain. In the baseline, the entire buffer is held by military, represented by the red bar.
In the optimal case, the suppliers hold buffers. These buffers are seen by the red bars. The inventory optimization identifies where and how big these buffers should be. Now, the military can keep the helicopters flying with much less money tied up in working capital (or worse, with many helicopters not being able to fly).
Of course, implementing this solution is not trivial. Contracts with the suppliers have to be re-worked to allow them to create and maintain the safety stock buffers.
At the 2011 annual CSCMP conference, Walmart's Greg Forbis spoke to a full session about Walmart's inbound supply chain. SupplyChainDigest reported on the talk. Here a a paragraph from their article that represents the challenge and opportunity:
"He also said that Walmart's vast transportation network, including some
6500 dedicated trucks and an amazing 56,000 trailers, covering almost
every area of the country, could reduce total transportation costs
because its network density and buying power may result in lower costs,
especially in terms of using vendor freight to reduce empty miles
travelled, or produce better consolidations. He noted, for example, that
Walmart has about 12 consolidation DCs that combine less-than-truckload
shipments from vendors into full truckload shipments to its stores. "
During the talk, Mr. Forbis mentioned the use of optimization to help with this problem.
This is a great example of how optimization can help firms. When you have an almost unlimited number choices, optimization technology helps you sort through the possibilities. This is especially true with transportation optimization. We have previously discussed how deceptively difficult routing problems are (click here and here for more information).
With Inbound logistics, the optimization is even more difficult. For example, you may need to find routes that pick up from multiple vendors and make drop-offs at multiple distribution centers. Most routing optimization focuses on outbound routes from a depot to stores. A nice advantage of IBM's Transportation Analyst is that engine is based on the Constraint Programming engine that gives you the ability to model inbound logistics and find great solutions that you otherwise would not find.
We often find that when we compare the results of an optimization run to the current plans, the optimization can find solutions that meet all the business rules and time constraints (which are not always met in the existing routes) and reduces the cost.
If you’ve ever tried to build an application that business decision
makers can use, you know that having a good model of the system you want to manage
isn’t enough. And while you need the best optimization solving technology, line-of-business
managers and executives demand more. They want to see the data supporting the
decisions, they want to try what-if scenarios to validate the proposed options,
and they want planners and schedulers to collaborate across the corporate
organizational lines. And if you want to deploy your solution, you need to
satisfy a bunch of requirements and standards from your IT department.
The Design Guide addresses these issues with concrete
guidance and practical examples derived from IBM’s long experience developing
and deploying analytical decision support solutions in many organizations.
Going beyond how to formulate good models, the Guide shows you how to design
data integration, business user interfaces, client/server architectures, taking
advantage of IBM’s ODM Enterprise to streamline development. The Guide
illustrates the steps using a concrete example derived from a real-world
logistics application. Plus the Guide explores two detailed case studies, one
in manufacturing and the other from insurance.
Need to convince your management that optimization can work
for your organization? The Design Guide can give you the credibility you
In 2008, after undergoing a grueling third-party logistics provider
(3PL) selection process, Navistar chose San Mateo, Calif.-based Menlo
Worldwide Logistics, the global supply chain management subsidiary of
Con-way Inc., to support it in improving its global logistics network,
including managing global transportation providers and regional
warehouses, planning lead times, and modeling net landed costs.
He reports that one of their goals was a 25% reduction in supply chain costs. He reports that at "the end of the partnership’s second year, we will have achieved
11-percent cost savings, out of the 25-percent goal we set for the next
When discussing the reasons Navistar selected Menlo, he mentioned their "global coverage, cross-network planning, and optimization capabilities."
This is a very interesting article discussing the challenges of building a new global supply chain from the ground up. It is also interesting that modeling net landed cost and optimization capabilities were mentioned as key factors in the transformation of the supply chain. This mirrors some other findings that leading supply chains are relying on optimization-based technology to help drive improvements.
At Smarter Supply Chains – Atlanta Regional Conference, David Simchi-Levi talked about Combating Volatility through Flexibility. I talked about this in greater detail here.
One point that David raised at the outset was the increased level of volatility surrounding the supply chain. His point was that companies need to be careful in thinking about the "best practices" that they apply to managing their supply chains. In such a dynamic environment, the best practices that applied before the recession - or before oil prices spiked, or before they crashed again - are not necessarily applicable today. It's a call to action for all supply chain executives to step back and reassess their processes to see if they are still "best in class," or whether there might be benefit to adjusting to the "New Normal."
Supply Chain authority Andrew Reese is Editor of Supply & Demand Chain Executive. He has been invited by IBM PR to attend this show as a blogger and speaker. Like all other speakers, Andrew will receive all speaker benefits including travel and board.
Manufacturers are offering more and more products by changing the "sizes, brands, colors, fabrics and flavors."
But, "instead of improving profitability, these tactics often lead to
bloated product portfolios that raise a company's costs, reduce
supply-chain efficiency, confuse consumers and lead to shortages of
The article offers tips for reducing the number of SKUs. But, this problem is difficult to tackle-- it involves many different groups and decisions can impact the top line and ability to compete for shelf space. At IBM, our advanced analytics solutions can add to the analysis.
Cognos helps with the Business Intelligence, allowing you to understand the demand and sales price of each SKU in each market. SPSS allows to determine which SKU's actually sell together and estimate what would happen to overall demand if SKU's were reduced. That is, if you eliminate an SKU, what will be the likely uptick in the demand of the remaining products. ILOG can help determine the true landed cost, supply chain efficiencies, and safety stock impact of a reduced SKU count.
Combined, these technologies could help you make the correct decisions on how many SKU's to eliminate and which new varieties to the market.
An article in DCVelocity provides some great insight into how Whirlpool and Maytag combined their supply chains. Whirlpool purchased Maytag in 2006 and promised the investment community $400M in savings over the first 3 years.
According to the article, $40M of savings per year was going to come from logistics-- freight and warehousing costs. This reminds us how important it is to get these decisions right. And, in Whirlpool's case, the article reported that they were able to overachieve and hit a savings of $66M in the current year.
How they got off to a fast start:
One of the first steps was to determine what inventory was on hand in
both operations so that Whirlpool could determine what to do with it.
The company acquired ILOG's LogicNet Plus suite of network design and
planning software so it would have a tool in place that
could import and crunch data once the deal was finalized (regulations
did not permit the managers to have access to Maytag-specific data until
the acquisition closed).
"When the deal was completed on March 31, 2006, we were in the
starting blocks ready to go. We had our tools in place and people in
place, and we had our own data. We were then prepared to bring in the
The network optimization with LogicNet Plus allowed Whirlpool to determine which distribution centers to close, which new sites should be built, and what the local cross dock network should look like.
We have seen this type of result many times over the years. When a firm grows through an acquisition, having a high-quality network optimization tool allows it develop solid plans for the new network. This creates a foundation for additional improvements and helps a company meet the goals of the acquisition.
This releases enhances LogicNet Plus XE's leadership position in the supply chain network design market. It includes many cutting edge and innovate features that will allow you run new types of optimization , and gain deeper analytical insight. Highlights of the new release include:
Ability to run the optimization with multiple user-defined objectives and automatically build detailed trade-off curves. Traditional network design limits you to one objective. This innovative feature allows you to make better supply chain decisions by weighing multiple objectives.
Detailed Landed Cost reporting and analysis
Lane visualization for easy model building, visual understanding of the structure of your supply chain, and detailed analysis of the output
New interface for improved ease-of-use
Center of Gravity modelling
Stochastic inventory planning
This is the third major release of LogicNet Plus XE since 2009 and shows IBM's continued investment in the product.
While doing some research for an upcoming white paper, I came across a nice article from Nov 2009 from Dan Gilmore at the SupplyChainDigest, "The Real Value of (Less) Inventory." A key line from the article is:
reducing your level of inventories relative to sales and sales growth
can have a dramatic impact on a company’s share price."
The article quotes research and cases to back up this claim. This certainly fits with what our customers are telling us-- they are seeing significant inventory savings through inventory optimization.
The word "permanent" is a great choice of words. Inventory optimization technology, by itself, will not lead to a permanent reduction. As we noted in an earlier post, we have developed an inventory planning playbook to help firms make the right inventory decisions with the right cadence and considering important strategic factors.
A new case study is available highlighting how Johnson Controls uses LogicNet Plus to model and improve their closed-loop battery supply chain.
The following is a quote from Johnson Control's Supply Chain Network Strategy Manager, Chad Montgomery:
"I’m using LNP XE every week to perform modeling on a variety of projects from small capacity analysis/capital investment decisions to quarterly financial forecasting and annual budgeting for capacity utilization, plant manufacturing, and shipping territories. LNP XE has allowed us to create clear pictures of our network, starting with a best-case utopia state and then quantifying the impact of each constraint. This clarity can reveal hidden savings opportunities as well as gives complete insight into the main drivers of our supply chain”
The article shows how the techniques are being applied in a non-discrete manufacturing environment.
We are seeing a similar trend.
However, many firms struggle with translating the lean system developed by Toyota for their environments. This can be especially difficult in long supply chains or in a environment where there is inherent batch or tank processes.
The excellent book by Hopp and Spearmen, Factory Physics, helps translate Toyota's system to other environments by defining lean as:
A manufacturing supply chain is lean if it accomplishes its fundamental objective with minimal buffering costs.
They define three types of buffers a firm can have: inventory, time, or capacity. In short, if you can make your product with a minimum of inventory, short cycle times, and excess capacity, you are getting closer to lean.
We are finding that optimization can be a great way to minimize these buffers and evaluate the trade-offs between them.
With inventory optimization, firms realize that the may not be able to eliminate inventory completely or that they have removed it from the wrong location. In these cases, optimizing inventory is important to achieving a lean operation.
In process manufacturing plants, these firms are relying on high-end optimization to better schedule the plants. They realize that they cannot get around batch and tank production, set-ups, cleaning operations, and other realities in the process industry. Optimization-based scheduling allows them to reduce manufacturing costs, improve inventory, and achieve lean operations.
Join our monthly IBM ILOG Supply Chain Management Virtual User Group (VUG) sessions.
These 1-hour meetings are
a quick way to brush up on your IBM ILOG supply chain modeling skills, meet
other people using the products, ask questions to the community, and learn
about what's new. These sessions will be led by our experts and have plenty
of time for discussions and Q&A.
May 4th 2001: Topic: "Applying Supply Chain Analytics: Benefits of
a Central Group" This talk addresses the value firms can achieve by
deploying advanced supply chain analytics and how a group should be structured.
We will use case studies and recent events to highlight the value from
business analytics such as network and inventory optimization. We will discuss
how 3M Corporation is organized to deploy this capability.
Join our LinkedIn Community to receive updates, more detailed information, and Dial-up/Web Meeting access. Schedule-at-a-Glance: May 4th -
Wednesday June 1st -
Wednesday August 2nd -
Tuesday September 1st
- Thursday October 7th -
Friday November 2nd
- Wednesday December 2nd - Friday
The website highlights why the concepts from the book are important. For example, Jim Champy, the coauthor of Reengineering the Corporation says:
"Companies today are faced with an increasing number of choices in
operational and supply chain strategies. This book goes beyond just
showing how to make the right operational decisions. It makes the
critical link between operations and providing more value to customers.
It's a must read for anyone involved in operations and strategy."
Also, a key concept discussed is the fact that many companies offer different value propositions through different channels or brands. These different value propositions imply that the company may have different supply chains. However, the company cannot simply operate their supply chains separately. They need to take advantage of synergies where it makes sense. Click on the S&OP video in this link for more information
In a recent webcast, IBM discussed the latest enhancements to IBM ILOG CPLEX Optimization Studio 12.2, from streamlined packaging and licensing, to major performance improvements.
CPLEX Optimization Studio now completely supports the rapid development and deployment of both mathematical programming and constraint programming models from a powerful IDE, based on the Optimization Programming Language (OPL), programmatic APIs, or other 3rd party modeling interfaces via supported connectors (Matlab, Microsoft Excel, etc.).
At the conclusion of the webcast, attendees were asked to identify the feature that excites them most from the latest release. Here are their Top 3:
IBM has once again re-asserted its leadership in mathematical optimization, with a remarkable 2.7x performance improvement on the most challenging optimization problems, mixed integer programs taking at least 1000 seconds. The latest release strengthens IBM ILOG CPLEX Optimizer as the most trusted and widely-deployed solver. Streamlined packaging, and removal of license key enforcement makes it even easier to choose CPLEX. What are your top 3 new features? To view the recorded webcast, please follow this link:
Customer expectations have grown for not only what they are buying
and how they are buying it, but how it is fulfilled and when they will
receive it. They want to buy online and pick up in the store, or have it
shipped direct to their home or office -- and they don't want to wait.
This shift has supply chain professionals moving beyond transactional
enterprise systems and operational rules of thumb to a more advanced
value chain. The value chain takes advantage of all this new granular
customer data to enable organizations to respond to demand variability
at the point of consumption -- connecting the supply chain directly to
customer demand, orchestrating seamlessly between trading partners and
suppliers. This is an inherently multi-enterprise, cross-functional
collaborative process that requires bringing together a vast amount of
data from disparate sources to make the right strategic, tactical and
In this webinar, we will discuss the strategic requirement to creating a successful value chain:
Real time analytics to balance supply and demand and optimize inventory levels and postponement strategies.
Visibility to address disruptions and detect patterns of supply chain behavior
B2B connectivity to optimize the inbound and outbound flow of materials
Evolution of the trading partner eco-system to reduce errors and speed fulfillment
Adrienne Selko Online Editor IndustryWeek
Adrienne Selko manages the editorial content of IndustryWeek's
award-winning Web site. Before joining the staff in 2004, Selko was
managing editor of corporate publications at a large regional financial
institution. She was also an editor for the U.S. based publication of a
medical manufacturing company. Prior to that she ran a public relations
and marketing company that published a best-selling healthcare book.
Selko received a bachelor's of business administration from the
University of Michigan.
Richard Douglass Worldwide Industry Director, Manufacturing IBM
Richard Douglass is the Worldwide Industry Director, Manufacturing,
Smarter Commerce within the software group of IBM, where he is
responsible for industry marketing and key industry account support. He
has over twenty-five years of experience in supply chain management
consulting and solutions development in a variety of manufacturing
sectors ranging from chemicals to high tech. Prior to joining,
Douglass had similar responsibilities at Sterling Commerce and
webMethods, integration and application software providers, and prior to
that he was an associate partner at Accenture, a global consulting
He received a bachelor's in computer science from Michigan State
University and an MBA from the Kellogg Graduate School of Management at
Northwestern University. He is certified as a Six Sigma Black Belt. He
is a senior fellow at the University of Maryland.
A recent article in The Wall Street
Journal discusses the benefits of a foldable shipping container. This would be a big innovation in shipping.
Inbalances in supply and demand means that shipping companies must pay
to get their empty containers back to where customers want them.
importance of moving empty containers is simple:
a huge expense, a huge headache for the industry," says Neil Davidson
of London-based Drewry Shipping Consultants. The net cost of moving
empties is around $7 billion a year, say analysts.
foldable container would reduce the cost of shipping the empties.
However, these foldable containers cost around $4,000, or twice the cost
of the standard containers. And, the technology
has not yet proven robust enough for the realities of "heat, cold and
salt water of the high seas, and the rough handling of
Right now, the industry is not standing still.
IBM's ILOG Optimization solutions are being used to optimize the return
of the empty containers. The goal of the optimization is to get empty
containers to where they
are needed at the lowest cost. Of course, the containers do not have to
return from where they started and there are options for leasing or
buying new containers.
The problem can be difficult when you
start to consider such things as the different container types, the
capacities of ships, the costs of different modes of transportation, and
the long ocean shipping times.
Besides reducing costs, the
shipping companies using this technology
are seeing benefits in customer service by having the needed empty
containers in the right place at the right time and having the ability
to quickly re-plan when conditions change.
commitment to Analytics and Smarter Planet, provides additional benefits to this problem:
First, since there is variability in demand and supply, it is important
to correctly set the safety stock levels for empty containers at key
locations. Second, it is important to track and trace the containers so
you have better visibility but also to know when a container needs to
be replaced or repaired.
The Dec 2010 issue of Inbound Logistics reported that McKesson Corporation is using "IBM's Supply Chain Sustainability Management Solution to aggregate supply chain, sales, and geographic data to create "what-if" scenarios that enable distribution network modeling, supply planning, inventory positioning, vehicle routing, and sustainability management."
When optimization and analytics are applied to a firm's supply chain, you can often see significant returns on your investment. When you make this capability part of an overall framework, like McKesson did, you create a repeatable process to continually drive improvements in your supply chain.
IBM ILOG CPLEX Optimization Studio 12.5.1 is now available and brings another breakthrough in performance in solving mixed integer programs. Mixed integer programming models are solved on average 15% faster than the industry-leading prior release 12.5, on models requiring 1 second and above, and for the more challenging group of models requiring at least 100 seconds the average speedup is 40%. As a result of this breakthrough performance, two of the previously unsolved MIPLIB 2010 models have been solved: ns111636 and tw-myciel4.
Also included in the release are:
Additional scripting functions for use with the Optimization Programming Language. These extend the the conflict and relaxation iterators and support multiple MIP starts.
New methods in the conflict iterator class of the Java and .NET APIs of the Optimization Programming Language
Extension of the CPLEX Optimizer remote object for construction of parallel distributed algorithms to Concert Technology for Java and C++
Lift and project cuts in the CPLEX Mixed Integer Optimizer
Enhancements to the CPLEX Optimizer presolve algorithm which result in faster solutions for some mixed integer programming models with quadratic terms
Ability to control generation of QCP duals in the CPLEX Optimizer
This live complimentary event will show you how IBM, through its ILOG® Optimization and SPSS portfolio and Business Analytics & Optimization service line, enables organizations to quickly and confidently answer fundamental business questions, from: Who will be our most profitable customers tomorrow? to What price will maximize profit from sales?
Highlights: • Advanced Analytics – Unifying the Worlds of Statistics and Operations Research • Demo – Illustrating the combination of IBM ILOG CPLEX® and the IBM SPSS Modeler • IBM ILOG Optimization Workshop • IBM SPSS Data Mining Workshop
Learn and share best practices in implementing advanced analytics to your most critical business decisions.
This week’s Economist magazine has a special report on the
“the data deluge.”The report points out:
“According to one estimate, mankind
created 150 exabytes (billion gigabytes) of data in 2005.This year, it will create 1,2000
exabytes.Merely keeping up with this
flood, and storing the bits that might be useful, is difficult enough.Analysing it, to spot patterns and extract useful
information, is harder still.Even so,
the data deluge is already starting to transform business…”
The article notes that the retailers are one of the leaders
in amassing this data.For example:
“Wal-Mart, a retail giant, handles
more than 1m customer transactions every hour, feeding databases estimated at
more than 2.5 petabytes.”(A petabyte is
Of course, this article fits nicely within IBM’s Smarter
Planter.Smarter Planet’s big ideas are
that the world’s systems will be instrumented, interconnected, and intelligent.
In IBM, the group behind this blog works on solutions to
help firms make more intelligent decisions with this data.Often, due to the number of possible choices,
optimization-based technology is the only way to get value from the information
For example, for retailers we’ve worked with, they have
taken advantage of the data in a variety of ways:
items should be stocked at a store, how the store should be laid out, and where
the SKU’s should be on the shelf—this helps retailers increase store revenue
the warehouses and stores should best be replenished, how the workforce should
be scheduled, how products should flow through the supply chain, locating the
warehouses, and routing trucks--- this helps retailers take costs of their
In each of these cases, simply analyzing the data was not
going to be good enough to extract value from it to give the retailer a
As data becomes more available, firms are revisiting their S&OP process to add more analytics to the process. In fact, the lack of analytics and optimization is often a reason that firms do not get the full value from their S&OP process. That is, without optimization-based technology, the S&OP process can become just a demand planning exercise with minimal analysis of the operations and supply.
By combining the Cognos S&OP solution with integration to LogicNet Plus XE, firms can now create optimized plans. That is, Cognos provides the descriptive analytics, an S&OP dashboard, the detailed reporting, the platform for demand consensus, the ability to standardize data from multiple sources to create a single S&OP view, and the ability to tie it back to financial systems. Cognos becomes the enterprise level platform for S&OP. LogicNet Plus XE then receives data from Cognos, allows the planner to run multiple scenarios, and feed the operations plan back into Cognos.
The operational plan considers capacity of the facilities, starting inventory positions, the demand plan from the S&OP process, and alternatives for meeting demand. Using this capability, it creates integrity in the process by coming up with operational plans that match the demand plans.
We have a short video available for additional information.
A SupplyChainDigest article from earlier this year noted that "IBM is building a formidable portfolio of supply chain software solutions that has the potential to shake up the existing market."
Now that IBM has completed the Sterling Commerce acquisition, IBM has much more to offer to the ILOG Supply Chain customers.
The IBM ILOG supply chain group provides supply chain planning capability (LogicNet Plus XE), inventory planning (Inventory and Product Flow Analyst), strategic transportation planning (Transportation Analyst), and production planning and scheduling (Plant PowerOps).
Sterling provides a strong set of supply chain execution and visibility products. These products include:
Transportation Management System (TMS), offered as a Software as a Service (Saas)
Warehouse Management System (WMS)
Supply Chain Visibility
Yard Management System (YMS)
The supply chain products from Sterling and ILOG complement each other and allow our customers to make better plans and efficiently execute against those plans.
I attended the CSCMP Chicago Roundtable event at RR Donnelley last week (February 11, 2009) and heard an interesting presentation by my colleague Jay Jayaraman. He discussed a project we are working on where a manufacturer of a commodity has the choice of exchanging product with a competitor. The idea is that a company can source an order from a competitor’s location that is closer to the intended customer than its current manufacturing base. The impetus being a saving on transportation costs. The key is that both companies can benefit from the swap since they both can reduce transportation costs, and each company keeps their relationships with their customers. Of course, this scenario can only work with commodity-type products.
To take full advantage of the situation, our network modeling and production planning tool, LogicNet Plus XE, can be used to determine the best possible swaps as well as understand all the constraints that impact the results. Doing this type of analysis with Excel can lead to omissions and sub-optimization.
It’s fascinating how collaboration, even amongst “enemies”, can lead to benefits for all…
Fulfilling the Three A's: Adaptability, Agility and Alignment
In the recent
years, we have seen a transformation in consumer behavior. The use of social
media allows consumers to exchange thoughts; the migration from controlled
media and monitored media. Easy information access combined with more educated
consumers is making promotion planning more important. Finally, the chase for
"value" is not only changing the timing of purchases but also
location and brand. All these changes on the demand side are forcing consumer
products companies to think about supply side in terms of: Demand Driven Supply
The supply chains are
being transformed into complex supply networks with the introduction of
co-packers, co-manufacturers and service providers. Commodity price increases
and fluctuations are adding to volatility and margin pressures. Overall,
changing consumer behavior, and increases in complexity, globalization and cost
reduction pressures all force consumer products supply chains to fulfill the
three A's: Adaptability, Agility and Alignment.
The crux of these
strategies relies upon the application of Business Analytics to help close the
gap between planning and execution. In this case, Closed-Loop Dynamic Inventory
Optimization is leveraged to set appropriate inventory targets throughout the
global supply chain and ensure that the right products are positioned in front
of the right customers at the right time.
Inventory Optimization is a core process that regularly tunes policies across
the supply chain to keep inventory closely aligned with changing conditions.
But, the organizational value of such an approach goes beyond the more obvious
metrics of improving service levels, order lead times, and inventory
positioning. For example:
Higher performing supply
chains can incur lower selling costs
Better replenishment enables
faster collection of receivables
Utilization of optimal
inventory targets results in less cash tied up in inventory
Optimal use of existing
distribution assets (warehouses, fleet) reduces need for capital
cash flow from lowered supply chain costs and unnecessary assets drive
higher credit rating and lower borrowing costs
application of Business Analytics on top of traditional supply chain planning
and execution solutions gives CP Manufacturers the unprecedented ability to
continuously improve operational efficiency, reduce costs, and enhance the
Michael S. Watson, Ph.D., WW Optimization & Supply Chain Lead at IBM,
Ural, Global Supply Chain Management Solutions Lead, Consumer Products
Industry at IBM
Ability to run the optimization with multiple user-defined
objectives and automatically build detailed trade-off curves.
Traditional network design limits you to one objective. This innovative
feature allows you to make better supply chain decisions by weighing
Detailed Landed Cost reporting and analysis
visualization for easy model building, visual understanding of the
structure of your supply chain, and detailed analysis of the output
The article does a great job of explaining how firms need to embed mathematical optimization deep into their organizations to really take advantage of their investment in IT and data.
"One of his [Steve Shashihara] most interesting arguments is that a great deal of the effort
spent on information gathering and analysis is wasted — or, at least,
used sub-optimally — when it’s used to feed business intelligence
systems that produce reports that ultimately wind up with being fed into
spreadsheets and PowerPoint slides. Managers then sit around in a
conference room listening to presentations and debating what the data
means and what decisions should be made about it — when, in many cases,
good software could make the decision itself."
The article mentions that IBM and IBM's ILOG CPLEX have the ability to address the need for more automated optimization. This article confirms the value we've seen in Optimization:
It is often difficult to explain how difficult it is to come up with an optimal solution to a vehicle routing problem.
I am convinced that part of the problem is that it is so trivial to come up with feasible solutions to a vehicle routing problem: just send out a truck to make every stop or group stops and send a truck to make multiple stops. And, an experienced dispatcher can often quickly improve upon a given schedule by looking at the routes. And, what we've found in practice, the constraints that would make the problem harder (like deliver time windows) are often simply ignored.
However, being about to find a solution to the problem (and maybe even an infeasible one), is not good enough. We've found that using advanced optimization can lead to routes that shave 5-15% of costs (on routes that are already deemed pretty good) and meet all the constraints.
What makes this interesting, is that the optimization is actually very difficult. Mike Trick's recent blog post highlights some of the difficulty with routing by writing about a Traveling Salesman Problem (TSP) a politician might face in Iowa trying to visit all 99 county seats in the shortest amount of drive time. Mike Trick quotes Bill Cook:
Leaving Des Moines, we have 98 choices for our second stop, then, for
each of these, 97 choices for the third stop, then 96 choices for the
fourth stop, and so on until we hit our last county and drive back to
Des Moines. Multiplying all of these choices gives the number of
possible routes through Iowa. And it is a big number, roughly 9 followed
by 153 zeros. No computer in the world could look through such an
enormous collection of tours one by one.
For vehicle routing (with multiple vehicles, capacities, time windows, and so on), the story gets more complicated. In a 2009 paper by Gilbert Laporte titled "Fifty Years of Vehicle Routing" discusses the progress that has been made in this field. He mentions that the vehicle routing problem "is considerably more difficult to solve than the TSP." Over fifty years of research has led to significant advances in different approaches and algorithms. But, he mentions that the field still has a long way to go to solve larger (and more realistically sized) problems found in industry.
This mirrors our experience with the ILOG optimization for vehicle routing-- these problems can be mathematically challenging. To solve these problems in practice requires an optimization-based approach. We have been working on this since the mid-90's. Some readers may remember the ILOG routing engine called Dispatcher or
the tool Transport PowerOps. This routing engine has found its way into
to the product called Transportation Analyst. And, the underlying
optimization engines are now part of the CPLEX toolkit.
We had the privilege of speaking with MillerCoors at the annual CSCMP conference in San Diego earlier this year. In that talk, they discussed how a significant amount of the $750 million in synergies came from the combining of the Miller and Coors supply chain.
The press release reports on the progress of the supply chain transformation as well as the on-going efforts to improve the supply chain:
In the third quarter, MillerCoors successfully completed initial product
transitions within its national brewery network. The company will
continue to focus on further network optimization through peak/non-peak
season sourcing changes, as well as opportunities for increased
We see many firms relying on advanced analytical solutions, like LogicNet Plus XE, to help drive savings in the supply chain. The savings can come from combining distribution networks, optimizing production decisions across the supply chain, and reacting to the changes in demand patterns throughout the year.
Yesterday, IBM published its 2009 annual report. In the Letter From the Chairman, IBM lays out its growth opportunities for 2010. It lists fours strategic areas for investment. Analytics and Smarter Planet are two of those four areas.
For Analytics, there is great amount of data available and organizations who take advantage of this information will unlock tremendous value. The letter notes:
IBM is moving quickly to capitalize on this promise. We have built the industry’s premier analytics practice, with 4,000 consultants, mathematicians and researchers, as well as leading-edge software capabilities
Of course, this fits with the opportunity IBM sees with its Smarter Planet initiative. In fact, the letter points out some benefits retailers have seen.
Four leading retailers have reduced supply chain costs by up to 30 percent, reduced inventory levels by up to 25 percent, and increased sales up to 10 percent. They’ve done so by analyzing customer buying behaviors, aligning merchandising assortments with demand and building end-to-end visibility across their entire supply chain.
A good example of how this IBM strategy comes together is through our shelf space optimization solution. In this solution, we help retailers place their products in the right place in the store-- from how the store should be laid out, how much space should be given to each products, and where the products should be on the shelf (for example, determining which products are at eye-level). This solution leverages our advanced optimization capability (to determine the placement), our advanced statistical capability (to predict and analyze detailed sales data), and our rules technology (to maintain the system since different regions and stores may be unique in their requirements).
The May 22, 2012 edition of the Wall Street Journal featured an article about manufacturing moving back to the US. (Click here for the article-- it may be restricted to subscribers). The article cited statistics from David Simchi-Levi of MIT stating that 39% of companies surveyed were considering moving production back to the US.
Of course, several factors were mentioned for this trend including changes in the relative cost of labor, the price of oil, and the ability to respond faster. Although not touched on in this article, making product closer to the demand can reduce the required inventory.
What is also interesting is that over the last 5 years, China has become a market where companies sell product. It used to be that companies just received product from China. Soon, firms found that their China plants were well-suited to cover the demand in China.
From a network design perspective, this brings up some interesting questions: should you make product for each region of the world in that region? Which products should you make in China and which ones in the US? And, what is the break-point for the price of labor and oil where it makes sense to move product from China to the US?
Next Session: December 11, 2013 at 07:30 Pacific, 10:30 Eastern, 16:30 CET
Speakers: Mary Fenelon, Development Manager, CPLEX Optimization Studio, IBM
Session Topic: What's New in CPLEX Optimization Studio 12.6
A new release of CPLEX Optimization Studio will be generally available on December 6. In this presentation, you will learn about the new features and performance enhancements, including:
Improved solution times on difficult mixed-integer problems
Improved solution times on scheduling problems
A new algorithm to provide a global optimum for problems with non-convex quadratic objectives
A new distributed parallel algorithm that harnesses compute clusters to solve mixed-integer problems
Constraints to better model ordering relationships between operations and to easily specify highly combinatorial relationships
Reorganization of CPLEX Optimizer parameters into a functional hierarchy
New code assist functionalities in the IDE that help in correctly writing constraints and related structures
An LP-format viewer in the IDE to aid in model debugging
IBM Decision Optimization Virtual User Group Meetings provide you with updated and useful information about our products and how you can get the best value for your organization from our optimization technology and solutions.
These meetings are being held electronically with presentations by our product management and development subject matter experts. The sessions will run for approximately one hour, with about 45 minutes of presentation material and 15 minutes for open questions and answers. Our goal is to provide a forum for you to:
make smarter decisions
get your questions answered
elicit your feedback on various topics.
We look forward to your participation.Please contact Kitte Knight email@example.com an invitation to this Webinar.
At this point in the holiday season, most supply chain professionals in the retail space are probably doing a lot more reacting than planning. Keeping the shelves stocked is likely priority #1,2, and 3, while things like cost and efficiency are farther down the list (if even on the list). With that said, I apologize for not writing this post 6 months ago when you may have been able to act, but perhaps this can be helpful for next year.
The holiday season provides many interesting optimization problems for those working in the retail supply chain. For many retailers, SKUs have short lifecycles and high variability. With these characteristics, it makes sense to try to centrally manage inventory in a small number of distribution centers. This allows them to risk pool the demand variability, keeping inventory and working capital as low as possible. During the non-peak season with lower sales volumes, regular (say weekly) replenishment can be planned in order to achieve transportation efficiency. Unfortunately, when the peak holiday season arrives, this strategy may not be ideal. Stores have limited ability to store product and sales velocity is high. With the goal of keeping the shelves full, they need frequent replenishment during the holiday season. If the retailer manages only a few DCs, there will be stores who are quite far away from the DCs, making it impossible (or very expensive through use of air freight) to replenish the store as frequently as necessary to prevent stockouts. Therefore, its quite possible a different distribution strategy may be called for during the holiday season. It may make sense to add seasonal distribution facilities to the network to get more product nearer to the stores. This type of strategy involves many decisions which all can be helped by using optimization:
How many seasonal distribution points do I need?
Where should they be located?
Which stores are assigned to which DC?
Which SKUs do I deploy to the seasonal DCs and which do I carry only at my regular DCs?
How often to I replenish my seasonal DCs and what type of transportation mode do I use?
How do I deliver to stores from the seasonal DCs (mode, route, etc)?
A good strategy ahead of the holiday season is likely to result in less headaches and less costs when the season actually arrives.
At Smarter Supply Chains – Atlanta Regional Conference, Ronan O'Donovan, product manager with IBM ILOG Supply Chain Applications, spoke about "smarter" inventory and product flow optimization.
Key findings: The challenges around inventory management and product flow are not getting any less. Retail and distribution clients, for example, are requiring a product that optimizes both safety stocks and the flow of products to minimize total supply chain costs.
To juggle all the factors impacting inventory and product flow, companies must make inventory and product flow optimization a formal business process within organizations, front and center and part of the regular monthly planning process, e.g., Sales & Operations Planning (S&OP) or Sales, Inventory and Operations Planning (SI&OP). "Making up the numbers" is no longer acceptable as a planning method.
In addition, processes are moving from "strategic" to "tactical," meaning that planning is becoming an increasingly frequent exercise as companies look to be more responsive to the evolving environment. Companies need to understand, at any given moment, what's the best plan for me right now, given the current set of constraints we're facing.
Ronan discussed typical user workflows and roles for Inventory Optimization, breaking down the separate approaches used by typical Super Users (collecting/managing data), Business Analysts (running what-if scenarios, setting new inventory targets) and Manager Reviewers (reviewing exceptions/alerts, approving/overriding recommendations, tracking planned vs. actual and other KPIs, and reporting). The key to a successful process is not necessarily how each of these classes of users performs their job, but how these users interact through a consistent, closely aligned process.
Where organizations put optimization at the heart of the process, the technology tends to follow to enable that process. Note that this process will evolve and mature over time within a company, as the company learns which factors to incorporate and how best to incorporate them. Ultimately, optimization will never be an "easy button" that will make everything work automagically, but it's a necessary and critical process.
Supply Chain authority Andrew Reese is Editor of Supply & Demand Chain Executive. He has been invited by IBM PR to attend this show as a blogger and speaker. Like all other speakers, Andrew will receive all speaker benefits including travel and board.
A new case study is available showing how Südzucker, Europe's leading supplier of sugar products with an annual revenue of approximately €7 billion, uses IBM ILOG LogicNet Plus to help meet their goals of a cost-effective and flexible supply chain:
Here is a quick summary of the case:
"When the European Union adopted a new market regulation for the sugar industry in 2006, Südzucker was forced to re-evaluate their entire supply chain network. On the one hand the company’s ability to export sugar to world markets became very limited, on the other hand major sugar deficit areas within the European Union were created. This led to a much greater focus on sales and distribution. Südzucker also knew this ruling would give them the ability to enter new sugar markets like Greece, Italy, Spain and the United Kingdom. Their challenge was to merge their national supply chain networks to create one integrated and powerful European supply chain network. The company had to determine how to modify their supply chain network by adding new facilities to ensure excellent service but also minimize transportation costs."
Next Session: June 25, 2014 at 07:30 Pacific, 10:30 Eastern, 16:30 CET
Speaker: Filippo Focacci, CEO, IBM Business Partner DecisionBrain
Session Topic: Use Optimization Techniques for Complex Decision Support: A DecisionBrain Case Study in Container Terminal Logistics
One of the challenges of large Container Terminals is to smoothly coordinate Quay-side and Yard-side operations during the container load/discharge process. Taking advantage of the IBM Optimization platform and technology, DecisionBrain (www.decisionbrain.com) successfully implemented an innovative decision support solution to help one of the largest Container Terminals worldwide to closely coordinate operations and reduce Yard Clashes. In this presentation we share the key ingredients of this successful implementation: project approach, solution architecture, technical approach and best practices.
We look forward to your participation.Please contact Kitte Knight firstname.lastname@example.org an invitation to this Webinar.
Previously, Indeval, like most CSDs around the world, operated a
settlement system that required banks to hold liquidity of billions of
dollars while securities were being settled. Linking the delivery of
securities to their corresponding payment requires depositors to have
adequate financial resources available to settle their trades. Financial
institutions may have to borrow if they do not have sufficient funds to
settle stock and debt trades.
At the heart of
Indeval's Dali securities settlement system, the IBM ILOG CPLEX
Optimizers match thousands of transactions simultaneously, so that only
net amounts of securities and cash need to be transferred among the
participating financial institutions. This tremendously reduces the
amount of cash and securities the institutions need to have on hand to
settle the transactions.
Indeval won the 2010 Edelman Award from INFORMS (Institute for Operations Research and the Management Sciences) for this work.
Memories of having to take unexpected markdowns of up to 70 percent on
leftover holiday merchandise during the recession prompted retailers to
keep inventories low during the critical months of November and
December. The strategy has helped retailers better manage their
businesses, but it also means clearance racks are expected to be thin.
Good inventory optimization are critical to a firm's success. Only by optimizing inventory across the supply chain can you truly optimize inventory within the stores. This often can involve both the retailer and the suppliers jointly optimizing inventory. Proper inventory optimization can give your supply chain the flexibility to meet unexpected high demand with a minimal amount of inventory invested in the system.
As retailers try to continue the momentum of this holiday season, inventory optimization will play a critical role--- too much inventory creates a financial risk if sales do not materialize and too little inventory creates a risk of losing revenue or market share.