IBM Decision Optimization
MichaelWatson 270002K5FS Tags:  routing optimization network_design ilog green carbon_modeling inventory_optimization 1 Comment 4,318 Views
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.
MichaelWatson 270002K5FS Tags:  cognos ilog s&op analytics optimization logicnet_plus_xe 4,285 Views
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.
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.
aeortiz 2700024WMF Tags:  products commerce consumer ilog scm inventory chain analytics supply business smarter optimization cp stockouts cpg ibm 4,216 Views
How Smarter Inventory Analytics Solve the "Out-of-Stock" Scenario for CPG Supply Chains
Date: Tuesday, May 17, 2011
Time: 11:30 ET, 10:30 CT, 9:30 MT and 8:30 PT
Place: Your PC
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 Networks.
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.
Closed-Loop Dynamic 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:
The 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 customer experience.
Michael S. Watson, Ph.D., WW Optimization & Supply Chain Lead at IBM,
Remzi Ural, Global Supply Chain Management Solutions Lead, Consumer Products Industry at IBM
SCDigest Editor Dan Gilmore.
MichaelWatson 270002K5FS Tags:  tms inventory wms sterling network_design yms visibility optimization ilog 4,213 Views
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:
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.
SC_Manager 270002HW8N Tags:  logicnet production transportation network xe plus planning modeling costs 4,197 Views
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…
P. Louis Bourassa
Technical Account Manager
David F. Carr of Forbes Magazine recently wrote an article based on an interview with Steve Sashihara, the author of the new book called "The Optimization Edge: Reinventing Decision Making to Optimize all of Your Company's Assets".
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.
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:
And the list could go on. We are finding that firms who push optimization deep into their organizations see significant returns on their investment.
As a complement to the Forbes article, we have just released a short educational video to explain the value of mathematical optimization to business leaders. Click here for a link to that video.
In a press release reporting their third quarter results, MillerCoors reported that they remain "on track to deliver $750 million in total synergies and other cost savings by the end of 2012."
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 efficiencies.
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.
Gartner recently assessed their view of IBM's acquisition of the ILOG supply chain products In the report, "The IBM ILOG Acquisition: A Progress Report Card, August 4, 2010."
Click here for a link to the report. You will need to be a Gartner member to see this article.
The new release of LogicNet Plus XE shipped last week. This was a major release with some new, breakthroughs in network optimization. Click here for a release notice.
In earlier blog entries, we commented on some of the unique capabilities of this release:
One of the powerful new capabilities is the multi-objective optimization. Click here for a SupplyChainDigest videocast on this new capability.
MichaelWatson 270002K5FS Tags:  analytics scm retail supply_chain ilog optimization 4,064 Views
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).
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:
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.
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?
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:
Andrew Reese 270002Q78Q Tags:  – inventory smarter regional optimziation chains and conference atlanta planning supply 3,972 Views
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.