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.

Route	Origin	Destination	Volume	Mileage
Route A	Atlanta, GA	Akron, OH	1000 loads	600 miles
Route B	Bakersfield, CA	Buffalo, NY	2000 loads	2500 miles
Route C	Chicago, IL	Cincinnati, OH	3000 loads	300 miles

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
Route	Origin	Destination	Rate per Mile	Transit Period	Capacity Commitment
Route A	Atlanta, GA	Akron, OH	$1.00	1.0 days	200 loads
Route B	Bakersfield, CA	Buffalo, NY	$0.75	2.5 days	1000 loads
Route C	Chicago, IL	Cincinnati, OH	$1.00	0.5 days	2000 loads

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

Carrier B
Route	Origin	Destination	Rate per Mile	Transit Period	Capacity Commitment
Route A	Atlanta, GA	Akron, OH	$1.00	1.0 days	800 loads
Route B	Bakersfield, CA	Buffalo, NY	$0.75	2.0 days	1000 loads
Route C	Chicago, IL	Cincinnati, OH	$1.20	0.5 days	1000 loads

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
Route	Origin	Destination	Rate per Mile	Transit Period	Capacity Commitment
Route A	Atlanta, GA	Akron, OH	$1.25	1.0 days	1000 loads
Route B	Bakersfield, CA	Buffalo, NY	$1.00	2.0 days	2000 loads
Route C	Chicago, IL	Cincinnati, OH	$1.50	0.5 days	3000 loads

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

Route	Carrier A (Full Volume)	Carrier B (Full Volume)	Carrier C (Full Volume)	Winner
Route A	$600,000	$600,000	$750,000	Carrier A OR Carrier B
Route B	$3,750,000	$3,750,000	$5,000,000	Carrier A OR Carrier B
Route C	$900,000	$1,080,000	$1,350,000	Carrier A
Full Business Total Cost	$5,250,000	$5,430,000	$7,100,000	Optimal: $5,250,000

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).

Route	Carrier A (Full Volume)	Carrier B (Full Volume)	Carrier C (Full Volume)	Winner
Route A	$600,000	$570,000	$750,000	Carrier B
Route B	$3,750,000	$3,562,500	$5,000,000	Carrier B
Route C	$900,000	$1,080,000	$1,350,000	Carrier A
Full Business Total Cost	$5,250,000	$5,212,500	$7,100,000	Optimal: $5,032,500

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.

Route	Winner 1	Winner 2
Route A Route B Route C	Volume Awarded Payment Winner 200 $120,000 Carrier A 1000 $1,875,000 Carrier A 2000 $600,000 Carrier A	Volume Awarded Payment Winner 800 $480,000 Carrier B 1000 $1,875,000 Carrier B 1000 $360,000 Carrier B
Optimal Total Payment $5,310,000

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.