Strategies for commodity procurement

By Dr. Mustafa Çagri Gürbüz, Professor at ZLC.

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With colleagues from Dalian, Shanghai and Singapore, I have been exploring how companies can create and benefit from more flexible strategies in the procurement of commodity-type goods and materials, and what would characterize optimal procurement policies.

The “procurement costs” of materials constitute a major component of total manufacturing costs. For example, raw materials (steel, iron, aluminum, etc.) represent 47% of the costs of an automobile. Prices of such goods show significant fluctuations, often due to seasonal patterns or supply-demand mismatches. In 2019 the supply of palladium fell short of growing demand, especially from automakers, and the price doubled to $1,800 per ounce in the year to October, making it more expensive than gold. In another example, in this case of ongoing overcapacity, spot prices per gigabyte of DRAM hit a record-low of $2.59 in November 2019.

The prices paid for raw materials, components and finished goods when using different sourcing options (such as spot market, futures/options, or long-term contracts) can vary significantly at one moment and over time. Companies may benefit from diversifying their sourcing portfolio. This can reduce procurement costs, increase profits (by exploiting beneficial price differentials and movements) and mitigate procurement risks (for example, a failure to meet the demand because a single source has insufficient capacity). The procurement response to expected price changes will depend on the direction of the change:  if managers anticipate that the prices will increase in the near future they can buy now and build up inventory, whereas if their requirement is reduced or prices are high but expected to decrease they may take a profit by selling stocks. If price stability is more important than absolute cost, the firm may secure its supply at a predetermined (fixed) price to hedge against uncertainty.

These approaches and benefits are well known in materials commonly traded as ‘commodities’ –  energy (including natural gas, crude oil), basic chemicals, ferrous, non-ferrous, and precious metals (e.g., platinum, gold), and agricultural products like corn, sugar, or coffee. Other inputs, from electronic components to transport services and even fashion items, may also be traded as commodities, either normally or in particular market conditions. In commodity market situations, where the firm is a price taker, procurement policies become even more critical to mitigating the risks resulting from demand and price volatility.

Flexible business models would allow firms to trade commodities in forward and spot markets simultaneously. Forward contracts are bilateral agreements to purchase or sell a certain amount of a commodity on a fixed future date at a predetermined contract price (these may be binding agreements, or ‘options’ that may or may not be exercised). The spot market or cash market is a commodity market in which goods are traded at the current market price. Both forward and spot markets exist for many commodities and commodity-like products (and services). Several fintech companies, such as Kyos and Lacima, offer pricing simulation and analytics software for energy and commodity markets, proving the value of the management of different sourcing options.

Flexible business models that combine different sourcing options allow firms to respond to changing demand, supply and price conditions by adjusting inventory levels based on up-to-date demand and price information while enjoying the security of guaranteed prices and supply offered by forward contracts. One well-cited example of such flexible business models is that employed by Hewlett Packard (HP) with suppliers of memory chips, spending 50%, 35%, and 15% through long-term contracts, flexible nonbinding agreements, and spot markets, respectively.

Another example is that of Platinum Group Metals (PGM) at General Motors (GM), where quantity-flexible forward long-term contracts with a supplier are combined with trading in the spot markets (New York Mercantile Exchange (NYMEX) or London Metal Exchange (LME)) to mitigate supply chain management risks. The quantity-flexible contract allows GM to secure the necessary raw materials (by reserving capacity in advance) and maintain cost predictability (by fixing the per unit price at the time the contract is signed). The supplier also benefits from the same contract by securing guaranteed future cash flow until the contract is terminated. The spot market on the other hand helps GM adjust inventory levels in response to unexpectedly high/low demand or make a profit by selling in case of favorable price differentials.

Embedding such flexibility in procurement policies clearly help firms improve their financial performance while mitigating operational risks. Thus, the portfolio management of sourcing options is a strategic decision-making process that requires a careful analysis of the following:

  • the value of combining different sourcing options instead of using a single source or method of sourcing (e.g., only buying from a contract supplier), given the additional administrative costs,
  • the optimal mix of procurement (and possibly sales) quantities when multiple sourcing options are used and their dependence on the current inventory levels, demand, and prices,
  • the design of the contract with the long-term supplier: defining the parameters (such as minimum/maximum quantities, the purchasing price, restrictions on price adjustments based on the current spot market price) to be included to make the contract sophisticated in its approach without being over-complicated in application; optimising these parameters; and formulating heuristics that can be applied to yield near-optimal solutions,
  • the sensitivity of financial and operational performance to changes in particular parameters thus enabling identification of the most critical ones (such as demand, price, or fixed costs of trading).

Our research (see “ Optimal Spot Trading Integrated with Quantity Flexibility Contracts”, Production & Operations Management, Vol. 29 (6), 2020, by Xu, Gürbüz, Feng, and Chen) suggests that optimal procurement policies (buying/selling decisions) in spot markets can indeed be characterized under rather general conditions given the long term supplier contract. We also show that the application of straightforward, practical  heuristic rules  yield near-optimal results. Furthermore, we observe that:

  • Dual sourcing (maintaining both procurement options: long-term supplier with a contract and the spot market) is quite effective in improving financial performance (cost reduction and increased profit) and both procurement routes can be used simultaneously in most cases,
  • Financial performance is quite sensitive to the following parameters:
    • contract price relative to the spot price,
    • Fixed costs of trading in the spot market,
    • Quantity flexibility offered by the contract (the range between minimum and maximum allowed order quantities),
    • Cost of not being able to meet consumer demand on time.

Evidently it is critical that firms have access to multiple sourcing options, with the condition, however, that management of this portfolio of options is done properly. Management therefore needs to pay special attention to how the critical parameters mentioned above evolve over time and under what conditions it pays to use multiple sourcing options, and to invest in better relationships with long-term suppliers which may offer higher degrees of flexibility (alternatives which are not mutually exclusive).

There are many opportunities for further research in the field of sourcing option portfolio management. Substantial improvements in the financial and operational performance of value chains could materialize when industry experts and academics focus on the analysis of:

  • the balance between financial outcomes and supply chain related risks, keeping in mind the strategic goals of the firm,
  • the value of building sensors that monitor the changes in input parameters (e.g., prices, demand) enabling more frequent updating and faster reaction, leading to better informed and more frequent re-optimization of buying/selling decisions,
  • price/demand fluctuations over time and correlation (or lack of correlation) between spot, futures, and long term contract prices,
  • the need to reserve supplier capacity in advance based on the likely scarcity of specific resources,
  • regulations within the sector (for example to combat market-fixing) in relation to restrictions on the price of the commodity and quantities to be purchased, stored, and sold,
  • the influence of the individual firm’s own decisions on overall market prices (whether it is for instance a monopsony buyer, or a price taker), when it makes buying or selling decisions,
  • the additional administrative burden of designing/managing contracts and/or trading in the spot market,
  • the effect of multiple sourcing on service levels and quality assurance, and therefore on customer relationships (for example a lowered risk of product shortage when dual sourcing rather than single sourcing),
  • contract parameters between the firm and the supplier that tend towards a win-win solution for both parties and both firms maintain cost/price predictability,
  • inventory costs to the buying firm if taking immediate delivery, or a fair price addition for storage of commodities bought now for later delivery (contango in market speak. This can turn negative – a situation known as backwardation).
  • development of structured machine learning models that utilize Data Driven Approaches (DDA) in order to forecast future price/demand moves given historical data, current and predicted environments and trends, and indicators such as the prices of futures contracts in a particular commodity.

For further information, contact Dr. Mustafa Çagri Gürbüz at [email protected]u.es.