Procurement Beyond ERPs

Gaurav Sharma
Sep 4, 2018 · 3 min read

Day 1 : Cost savings in Commodity Procurement : #Cent-i-meter

I have seen two types of organizations. One, where the buyer collects 3 best quotes from vendors and release the purchase order on the lowest one. If this is the only value-adding activity in your procurement cycle, I have some bad news for you.

The second type of organization is where collecting 3 quotes is usually the final step or it is not even required. Here, I have seen and built models to select the best vendor and award him the “Right to Quote Last”. Of course, “Right to Quote Last” is a privilege that needs to be earned. This topic is beyond the scope of this article at this moment.

The thing that makes Commodity procurement different from rest of procurement types is its high velocity and high volume. A cent higher than the market price will make a direct impact on your operating margins (quite an obvious one here, I could have avoided writing this!)

A quick way to understand this impact is to classify your spends according to the sensitivity of unit cents. For example, for one of my Commodity, one cent higher impacts the operating margin by $750k annually. Here is what I have done so far :

1.) I have classified my entire Commodity baskets according to unit cent sensitivities.

2.) Through some quick Python and VBA coding, my program monitors the market movement on real-time basis.

3.) I then combine the quantity to be procured with the unit cent sensitivity, to build a simple dashboard (hence the name Cent-i-meter!). I decide upon a threshold value and monitor actively.

4.) The purpose is to deploy different procurement strategies and monitoring levers for my highly sensitive commodities. I use this information to calculate

a.) What is the right time to buy a particular Commodity

b.) Redefine budgets and calculate Value at Risk for my commodity basket

One might argue that the price trend graph (which is a common price monitoring practice) serves this purpose. I disagree. Cent-i-meter will help you prioritize and quantify the favorable or adverse movements cross commodities. Following is one of a way where I use this data :

a.) I calculate cross-commodity price correlations

b.) I also calculate commodity price correlation with its influencing factors (example exchange rate, crude oil, supply-demand numbers, industry events etc).

c.) I combine (a) and (b) to make a model and group the highly correlated commodities into one basket.

d.) I recalculate the Cent-i-meter of © to quantify the new portfolio movement. This has served me far better than monitoring 10 different price trends of individual commodities. However, Cent-i-meter will only give you the quantum of market movement impact on your procurement expenditure, it doesn’t give the magic number of “how much to buy out of the remaining total quantity”. To do that, we have separate procurement techniques and algorithms. I will cover that later in this series!

My motivation :

I love building stuff. I am combining my little procurement and supply chain knowledge with my machine learning skills to go beyond today’s procurement practices. I do not believe that going with best out of the 3 procurement style, need any skill. It can be and should be automated. Also, I have also seen the majority of manufacturing companies using ERP systems as transaction registers.

I am trying to create Procurement managers more Data Savvy where they focus on real value and not just transactions.

Contact me on gsharma.imbox@gmail.com for more details. I will be happy to assist.

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