Today’s guest post is from Ayush Sharma, a Strategic Sourcing Consultant with Trade Extensions in the Americas. His particular speciality is the application of optimization to Retail Sourcing, Dedicated Transportation, 3PL Logistics Sourcing, and Direct and Indirect Materials Sourcing. Ayush has a Masters degree in Supply Chain Management from the University of Texas at Dallas, certifications in Lean Six Sigma and Supply Chain Management, and has served as a Technical Director for a local branch of the Institute for Supply Management (ISM).

We started the series off by discussing the importance of supply and demand chain integration, with respect to the organizational strategic plan, as the key to an efficient, profitable and fluid business and the importance of a good Strategic Sourcing process, built on combinatorial bidding and optimization, in the execution of supply and demand chain integration. Then we discussed the characteristics of a strong and measurable sourcing process which can be utilized to increase Supply Management throughput and turn the organization’s Strategic Spend into a Strategic Value-Add for the corporation as a whole. In our last post we presented the first of two examples, inspired by real-world events, that demonstrate the impact of including combinatorial bidding and optimization in a sourcing project that follows a process similar to the one outlined in our last post. Today, we present our second example.

Let’s consider the case of Retailer X that wants to source several cases of fresh fruit juice. Three varieties are being sourced in this project — Apple, Blueberry and Cranberry Juice. The retailer has three DCs in Austin, Baton Rouge and Columbus and wants to determine if it’s more cost effective for the supplier to transport items to the DCs versus the retailer’s trucks picking them up. Finally, let’s consider the three suppliers placing bids on these items are Company A, Company B and Company C.

Retailer X has the following forecast for FY 2012:

The team wants to perform some creative analyses. To this end, suppliers are allowed to provide the following information:

• Delivered Duty Paid (DDP) ‘Cost per Case’
  (this includes the cost of transportation from the supplier location to a DC)
• Collect ‘Cost per Case’ excluding transportation
  (in this case, the retailer handles transportation)
• Item and location-specific capacities
  (e.g., the supplier can only provide 30,000 cases of Apple Juice from their Florida location)
• Discounts on dynamic bundles of items
  (e.g., If awarded the entire forecast of Apple Juice and Blueberry Juice, the supplier offers to provide a discount of 5%)
• Information about the locations that suppliers will be shipping from

The retailer has been strictly monitoring data from the last two years and is using the implemented costs from FY 2011 as a baseline for this project. Based on the data collected over the last two years, the retailer was also able to find a direct correlation between the suppliers’ qualitative metrics (let’s call this an Index Score) and their ability to match the expected price without unexpected cost increases over the financial year. Based on this information, the retailer wants to penalize suppliers with a low Index Score to ensure they’re able to maintain supply quality.

It’s possible to get a sense of analysis possibilities just from looking at the supplier data collected. The retailer obtains a ‘Transportation Cost’ (Cost per Case) from their internal transportation team using the suppliers’ location information. This Transportation Cost is used to calculate a ‘Landed Cost per Case’ if the retailer handled transportation. The Landed Cost thus obtained is then compared against the ‘DDP Cost per Case’ and the best cost is chosen. The retailer also takes into account supplier capacities to calculate how much of the demand volume gets fulfilled from each location. Also, each supplier has offered certain discounts if they’re awarded certain volumes. This is weighed against the capacity information to determine the best overall fit.

The optimization and analysis process typically spans several steps:

1. Low Cost Scenario: This scenario simply calculates an award to each Item-DC combination using the lowest cost per case (among the Landed Cost and the DDP Cost) without considering capacities or discounts
2. Low Cost with Capacities: This scenario again uses the lowest cost per case but now considers supplier capacities and discounts while calculating individual awards
3. Limiting Winners: Typically, there are some supplier specific constraints that need to be applied (e.g., only 1 supplier gets the Austin DC); We build upon the solution in #2 by applying these constraints
4. Supplier Mix: This set of constraints ensures product availability while maintaining the desired supplier mix (e.g., award at least 10% of each DC to a new supplier)
5. Applying Penalties: In this case, we build the solution further by incorporating some penalties using the suppliers’ Index Scores
6. Additional Constraints: Each category has its own unique set of requirements which determines the constraints that are applied; An example of this would be penalizing suppliers that are located far away from a DC if the product is time-sensitive

The process for this project spans across multiple rounds. The retailer participates in face-to-face negotiations between the two rounds to discuss the suppliers’ quote with each supplier and to explore any additional ways they could add value. The retailer also decides to share some feedback with suppliers in the second round based on their analyses. In most cases, increased transparency encourages suppliers to provide better quotes.

The example above was very simple with just three items being sourced. But you’re immediately able to get a sense of the possibilities where an increased number of Item-DC combinations can be sourced in the same project. Potentially, the retailer could also look for multiple commodities that could be fulfilled by the same set of suppliers and group these into a single project. Having this level of scalability ensures the advantage of better supplier quotes while maintaining the desired supplier-product mix in the analysis stage.

The retailer identifies relevant KPIs that allow them to effectively monitor the category over time. Examples of such metrics include the ratio of product to shipping costs (per DC and overall), suppliers’ on-time delivery performance (this must be applied to the overall index score), Expected vs. Implemented Costs (costing changes due to supply shortages, natural disasters, etc.), the cost of maintaining the supplier mix (aligned with sourcing strategy), etc.

Over a multi-year supply cycle, this process effectively drives savings while maintaining a strict hold on metrics that are important to the category and aligned with the retailer’s overall strategy.

When you combine this example with the example in the last post, it’s easy to see how optimization, when used in conjunction with combinatorial bidding, can add tremendous value to any strategic sourcing initiative. The advantage of being able to compare different possibilities within a short duration of time while following stringent sourcing methodology means your organization has a repeatable and result-oriented process on the right track to sourcing success.

Thanks, Ayush!

Today’s guest post is from Ayush Sharma, a Strategic Sourcing Consultant with Trade Extensions in the Americas. His particular speciality is the application of optimization to Retail Sourcing, Dedicated Transportation, 3PL Logistics Sourcing, and Direct and Indirect Materials Sourcing. Ayush has a Masters degree in Supply Chain Management from the University of Texas at Dallas, certifications in Lean Six Sigma and Supply Chain Management, and has served as a Technical Director for a local branch of the Institute for Supply Management (ISM).

We started the series off by discussing the importance of supply and demand chain integration, with respect to the organizational strategic plan, as the key to an efficient, profitable and fluid business and the importance of a good Strategic Sourcing process, built on combinatorial bidding and optimization, in the execution of supply and demand chain integration. Then, in our last post, we discussed the characteristics of a strong and measurable sourcing process which can be utilized to increase Supply Management throughput and turn the organization’s Strategic Spend into a Strategic Value-Add for the corporation as a whole. Today, we are going to present our first of two examples, inspired by real-world events, that demonstrate the impact of including combinatorial bidding and optimization in a sourcing project that follows a process similar to the one outlined in our last post.

We start with a logistics sourcing project run by ‘Transport Corp.’, a 3PL (third-party logistics) company that wants to source three routes — Route A, Route B and Route C. Each route has a certain volume (number of truckloads) that needs to be fulfilled. Transport Corp. wants to utilize the combinatorial bidding and optimization process and invites three freight carriers to bid in this project — ‘Carrier A’, ‘Carrier B’ and ‘Carrier C’.

Transport Corp. has the following volume information.

Transport Corp. wants the carriers to provide the following inputs:

1. A ‘Rate per Mile’ for each lane
2. An estimated ‘Transit Period’ (number of days from the origin to the destination)
3. A ‘Capacity Commitment’ (number of loads each carrier can fulfill)
4. Any ‘Lane Bundles’ that would entail a lower rate across the bundle

The freight carriers each quote the following:

Carrier A doesn’t have any additional bundle discounts to provide.

In addition, Carrier B says that if given all the volume in Route A and Route B, they’ll provide an additional discount of 5%.

Carrier C doesn’t have any additional bundle discounts to provide.

Initial Results (Low Cost without Capacities or Discounts)

With the carrier Lane Rates (cost for shipping all the loads on each lane), it’s possible to get a ‘Total Cost’ comparison. Looking at the numbers simplistically (i.e. without considering any capacities or discounts), we can infer the lowest cost carrier easily. In this case, looking at the table below, it’s easy to identify the winner overall would be Carrier A if one was just looking at the carrier prices

Low Cost Considering Discounts

However, we know that Carrier B has offered a 5% discount on Route A and Route B if awarded both these lanes. Let’s consider this possibility in the table below. It’s apparent that after applying the discounts, Carrier B becomes more favourable not only on Route A and Route B but also overall (see the last row showing the total cost for awarding all routes to a single carrier).

Optimal Payment Considering Discounts, Capacities and Business Constraints

In the same problem, we now analyze the possibility of honouring carriers’ ‘Capacity Commitment’ numbers. In addition, Transport Corp wants to mitigate risk and therefore wants to award each route to at least two carriers. We now see that a simple problem with three lanes and three carriers quickly becomes hard to solve. This is where the power of optimization comes into play, allowing us to quickly compute the best solution. Here’s a look at the solution if we want 2 winners per route and also want to honour capacity commitments. Carrier B’s discount doesn’t materialize in this scenario as no carrier gets a full lane award.

Taking this one step further, it’s possible to visualize cases where Transport Corp wants to incorporate some penalties for carriers with higher ‘Transit Periods’ to arrive at another solution that has a better overall lead time. In this manner, several what-if scenarios can be run in a short span of time. These types of creative analyses can be performed while simultaneously allowing carriers to submit all the information they have. However, a process also needs to be instituted where the awarded scenario is closely evaluated against previously implemented rates. It is also useful to do some sensitivity analyses to understand how the award alignment changes if the payment is relaxed by a certain percentage. Monitoring these in addition to carrier performance and quality metrics allows Transport Corp to arrive at an optimal decision that considers all factors and is right for their business.

Thanks, Ayush.

Today’s guest post is from Ayush Sharma, a Strategic Sourcing Consultant with Trade Extensions in the Americas. His particular speciality is the application of optimization to Retail Sourcing, Dedicated Transportation, 3PL Logistics Sourcing, and Direct and Indirect Materials Sourcing. Ayush has a Masters degree in Supply Chain Management from the University of Texas at Dallas, certifications in Lean Six Sigma and Supply Chain Management, and has served as a Technical Director for a local branch of the Institute for Supply Management (ISM).

Yesterday’s post discussed the importance of supply and demand chain integration as the key to an efficient, profitable, and fluid business. These processes, which should be integrated with the strategic plan, should utilize Strategic Sourcing and it’s ability to drive ‘savings’ year after year. And the best Strategic Sourcing processes are those that combine combinatorial bidding and optimization, which allows an analyst to run several what-if scenarios in minutes and generate reports that show exactly how the overall spend distribution changes as newer business processes are taken into account. In today’s post, we will discuss the requirements for a strong and measurable sourcing process.

A strong and measurable sourcing process normally exhibits the following characteristics:

1. Integrated Processes
   Using a rolling window of a few years (usually two to three years), strategic sourcing projects should be strictly monitored to understand expected vs. implemented costs and ensure implemented costs are in line with the strategic plan. The suggested time window works best as it allows room to respond to market dynamics while maintaining a medium to fairly long-term focus.
2. Creative Analyses
   Technologies like combinatorial bidding and optimization can be used creatively. Today’s tools offer extreme flexibility in terms of the types of data that need to be captured and the limitless possibilities for analysis. Businesses must look at ways of incorporating qualitative information and ongoing metrics (e.g., favouring suppliers who have been able to maintain the price for the duration of the contract) in the analysis process.
3. Collaboration
   Supplier collaboration is key to insure the success of any Strategic Sourcing process. In this era of real-time communication, it’s vital to collaborate with suppliers on an ongoing basis while providing them dynamic feedback to improve the overall quality of the sourcing process.
4. Economies of Scale
   Businesses must look to increase the scale of projects. Several bidding tools allow ridiculously large numbers of bids to be captured and analyzed at an extremely granular level. Increasing the size of projects not only means increased productivity and cycle time (and thereby cost) efficiencies for the organization. It also allows you to take advantage of economies of scale in the bidding process while maintaining the appropriate level of detail during analysis.
5. Benchmarking
   Sourcing projects should be used to create financial benchmarks allowing organizations to understand industry trends and the impact of specific changes in methodology. When the market fluctuates, effective benchmarking techniques help understand the immediate and long-term effects and allow organizations to mitigate risk.

The easiest way is to just get started using the guidelines above and then steadily build and refine the process. No one solution will work for all organizations, but taking the lather-rinse-condition-repeat approach with special focus on ‘conditioning’ will ensure maximum optimality. Supplier collaboration should take center-stage, especially when the focus is on long-term profitability. Utilizing the latest technology to capture all of their requirements ensures a wholesome process and a meaningful relationship with suppliers. As the process gets more streamlined, productivity benefits (along with specific measurable savings) will mean increased throughput in the entire sourcing process without losing track of strategic goals. This is how your Supply Management organization turns the organization’s Strategic Spend into a Strategic Value-Add for the corporation as a whole.

In the posts that follow, we will illustrate this with a couple of examples, inspired by real-world events, that demonstrate the impact of including combinatorial bidding and optimization in a sourcing project that follows a process similar to the one outlined above.

Thanks, Ayush.