Local Content policies are enacted by governments to provide incentives to local industry so that it can develop and attain global competitiveness. The goals of the Brazilian local content policy are to increment participation of the national industry on a competitive basis, develop technologies in Brazil, increase the competence of the technical community and generate employment and income in Brazil (ANP, 2008).

The additional dimension of local content directly affects both the schedule and cost of execution of the project. This makes the job of the project manager much more difficult and much more critical. The purchasing situation is much more complex than in traditional project management. Traditional tools such as Gantt Charts and S-Curves are no longer sufficient for the work of a project manager.

Global sourcing of products is a pre-requisite for economic project execution in the competitive oil and gas equipment market. The requirement to meet a certain local content places restrictions on the purchase of the best available global option. Often the price of a product with high local content is also higher than the best available price in the global market. Local content requires the project management function to be good at evaluating the premium they are willing to pay for local content. Which option should a project manager select - A supplier with 50% Local Content and a price of 100 or another supplier with 60% Local Content and a price of 105? This is not a theoretical question but a very practical one. This paper proposes a framework that allows the project management personnel to optimize the three dimensions of Lead Time, Local Content and Cost.

A recent study on the competitiveness of Brazilian O&G industry concluded, as confirmed by our experience, that equipment highly dependent on scale or with relatively small levels of sophistication present higher differences in prices between global and Brazilian sources. The marginal cost of local content increases with increasing local content. The slope of a graph of cost vs. Local Content is asymptotically increasing.

If all the products that make up a system had a similar price vs. local content function, the optimal system price would be achieved when all the constituent products are purchased at the system required local content. Any other system is non-optimal. In case of complex systems, it is more advantageous to purchase higher local content for more complex products and lower local content in less complex products.

This insight is counter intuitive. EPIC companies purchase their most complex systems first - at the best prices and try to make up LC in the lesser complex products. This results in a non-optimal system cost. At a more abstract level, this observation has significance for Brazil local content policy. It is much better to incentivize and focus on higher technology Local Content as this has a higher probability of being cost competitive on a global scale. The hurdles for achieving global competitivity for lower technology equipment are higher. If the government policies and the market economics are aligned, this policy could bear better results - faster.

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