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A Fortune 100 pharmaceutical company improves its commodity procurement strategy and reduces volatility

Key highlights
  • The business was facing overdrawn budgets and increased spending due to ineffective purchasing and negotiations
  • Working with the procurement CoE we examined key commodities to understand future trends and price drivers and then applied this intelligence with our category knowledge to produce over 250 individual commodity inflation forecasts
  • Our work has delivered typical yearly savings of $20 million through dedicated forecasting and $6 million through better negotiation discussions as a result of the intelligence we were able to provide
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Business challenge

A Fortune 100 Pharmaceutical company was experiencing overdrawn budgets and increased spending due to ineffective purchase planning and poor outcomes from negotiation discussions. The client wanted to ensure cost containment, effective budgeting and optimum supplier negotiations, by staying abreast of market movements of key categories and commodities. The procurement CoE team engaged us to access the specialist intelligence, resources and expertise needed to address this challenge.

The Smart Cube solution

Using our Commodity Intelligence solution we were able to provide inflation analyses for key commodities across multiple business units. This required leveraging a blend of capabilities including specialist commodity expertise, secondary research, statistical modelling techniques and advanced analytics. The scope covered over 250 commodities including:

To build a rigorous solution we looked at:

  • Cost drivers for various spend categories were identified and analysed. Existing contracts were reviewed to identify formulae and indices being used
  • Factors and variables that could be correlated with price movements of key commodities (agricultural, metals, fuels, resins, petrochemicals, minerals) were identified
  • Statistical relationships between various shortlisted variables (feedstock supply, exchange rates, supply-demand, Forex rates, GDP, etc.) were determined, and the forecast model was tested by calculating historical prices and measuring deviations from actual prices
  • The cost structure, spend, commodity forecast and current contract data was collated, to develop inflation forecasts at category, regional and global levels Using this intelligence our commodity experts worked closely with the procurement team in driving negotiations and contracting decisions based on the expected market movements.
  • Commodity inflation forecasts were presented through an online dashboard and mobile app for ease of use by the finance team and category managers.

Results

We provided the client with ongoing analysis and insights into inflation across spend categories and commodities, to enable effective and precise budget planning and avoidance of superfluous costs. Category and commodity buyers used the platform developed as part of the solution to simulate the impact of expected market movement on their contracts.

The exercise delivered tangible business benefits to the client, with typical yearly savings of:

  • $20m through dedicated commodity forecasting
  • Over $6m impact of market movement neutralised through improved supplier negotiations
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