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.
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
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."
The result of a typical strategic network design study, often yields the opening of new warehouses and new manufacturing plants. IBM's LogicNet Plus XE helps companies determine these locations. For large supply chains, the optimization of the number and locations of a facilities can impact hundreds of millions of dollars of cost. LogicNet Plus XE helps make sure you make these decisions correctly. Click here for a video overview of LogicNet Plus XE.
Implementing the new sites is a critical step in realizing savings. IBM's TRIRIGA software solution helps companies get the new sites up and running (and keeps them running efficiently.). TRIRIGA is a solution that manages the bid process for picking the real estate, helps get the building built, the equipment moved in, and ensures that the site is running efficiently. TRIRIGA is a complete facilities management solution.
This is another good example of how IBM's growing software portfolio can help make firms more successful.
In a blog entry we featured earlier this year, we noted that Navistar selected Menlo Worldwide Logistics as their 3PL partner, in part, because of their optimization capabilities. Also, the 3PL's of Fidelitone in the US and AFL in India (now owned by FedEx) also highlight their optimization capabilities.
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.
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
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.
In yesterday's broadcast of the weekly Supply Chain Video News sponsored by the Supply Chain Television Channel and CSCMP, we were interviewed about the new multi-objective optimization capability. If you click here, it will take you to the video. The interview starts at about the 7:00 minute mark.
This type of technology fits in with IBM's broader strategy of Smarter Commerce. IBM is seeing the trend towards much more complicated supply chains with a much more connected customers at the center. These customers have great access to information through their smart phones and social networks and are buying through many different channels. IBM's Smarter Commerce strategy helps companies thrive in this new environment.
Making sure the supply chain is properly designed is an important component of Smarter Commerce. The multi-objective optimization is the technology that gives full visibility to potentially conflicting objectives of various components of a value chain and analyzes the trade-offs between them. This technology is an attempt to replace the traditional optimization questions such as "what is the least-cost supply chain?" with questions such as "what is the ideal value chain for my customers, partners and my own organization".
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:
Lean techniques started with Toyota's manufacturing system and have moved into many other types of operations over the last two decades.
Often, though, it is difficult to take the concepts of 'Lean' and apply them to operations that do not look much like Toyota. Often, these efforts will just focus on waste reduction. However, a careful study of the fundamentals of lean reveals the importance of creating optimal (and minimal) buffers to protect against variability. This is where optimization can come in. Optimization can often reveal new strategies for minimizing the buffers you have in your supply chain. For example, the article quotes:
"Of course, another great way to reduce inventory at the warehouse is if the product just skips the warehouse entirely. That requires determining which products should touch every warehouse, which should bypass the warehouses, and which should be cross-docked."
IBM just released a nice video introducing the concepts of mathematical optimization to business. This is a great video to help you convince others in your organization of the value of optimization. Click here to view the video.
The new "hours of service" rules were discussed In a recent Wall Street Journal article. The article mentioned that the hours a truck can drive in a day is proposed to be dropped from 11 to 10. The final decision is expected to be made in October.
This represents a potential 9% decrease in the number of miles that can be covered in a day by a truck. This obviously has a large impact for the supply chain. Some orders that could be met within a day will now be two days. You may have to shorten routes or change modes. And, this will drive up your transportation costs.
To mitigate the increase in transportation cost, you should re-evaluate the structure of your supply chain to make sure you have the right number and location of your warehouses, to make sure you are making products in the right locations, and to make sure your routes and modes are correct. By re-optimizing your supply chain, you may be able to offset much of the cost of the new rules.
Although the new rules are not yet in place, it is a good idea to get ahead of the situation so you are ready if they are enacted. Even if the rules are not enacted, the supply chain optimization scenario may yield other savings.
The new supply chain news aggregation site OpRules, reported on on an article about Australia's new carbon tax. According to the article,
"Prime Minister Julia Gillard yesterday announced a $23 dollar per tonne
price on carbon emissions to be paid by about 500 of the country’s
biggest polluters from July 1, 2012."
Supply chain optimization can help firms help minimize the impact of this tax and reduce carbon. For example, with this tax, it may make sense to change the number of warehouse locations, manufacture or procure products from different locations, develop different routes for the trucks, switch transportation modes, and evaluate different inventory policies.
By re-analyzing the supply chain to include this new tax, firms should be able to find strategies that dramatically decrease the total cost of the carbon tax by developing new strategies in other areas of the supply chain.