Unlocking Local Content: Harnessing the Power of Data-Driven Decision Making

As new reserves of oil, gas, minerals, and other natural resources crop up around the world, multinational companies are seeking to enter new markets and invest in establishing supply chains. Increasingly, developing local content has become a popular means of maximizing supply chain resilience, lowering costs, reducing risks, and building relationships with key local actors. At the same time, policy makers in both new and mature markets are advocating for local content as a way of generating further benefits from extractive industry operations to the local economy.


While local content is more relevant than ever, designing an effective local content strategy remains a critical challenge. Companies must balance meeting regulatory requirements with achieving business objectives and have traditionally relied upon spotty qualitative and anecdotal information to drive these decisions. This approach leaves companies prone to missed opportunities and supply chain disruptions. The next big thing in supply chain management is transitioning from a reliance on ad hoc information to a systematic use of rigorous quantitative data and analytics to drive local content decision making.

A Crucial Component of Modern Supply Chain Strategy

Local content, also known as “national content,” “indigenous content,” or “local participation,” refers to the goods and services sourced from domestic vendors and their broader economic impact in terms of value add and employment. Local content can include the procurement of goods and services from local vendors, employment and training of national workers, development of local business institutions, improvement of local technological capabilities, and joint ventures and partnerships.

The DAI Sustainable Business Group provides solutions to multinational companies in the oil, gas, mining, and power sectors in the areas of local supply chain optimization, corporate social investment, and government and community engagement.

Multinational companies are driven to prioritize local content by various business benefits:

  • Government relations. Providing clear, quantifiable benefits to the local economy enhances relationships with host governments, increasing the likelihood of competitive differentiation in bidding rounds and negotiations.
  • Supply chain resilience. Disruptions can be minimized when vendors are in close proximity and when local communities have an economic stake in the project.
  • Cost reductions. Costs savings can be realized in the longer term through a clear understanding of cultural expectations, return on investment from training programs, and local business process optimization.
  • Community engagement. Providing jobs and other economic benefits to local communities is a vital element of securing and maintaining a social license to operate.
  • Reputation. Companies that deliver on local content enhance their standing among shareholders.

In addition, a growing number of governments are establishing local content policies that require multinational companies to stimulate broad-based economic development through local purchasing, adding a legal and compliance imperative to engage with local vendors.

The Problem with Common Practices

While the case for local content is clear, creating an effective local content strategy is easier said than done. Local content decisions are often ad hoc in nature and based on anecdotal, qualitative information, sometimes from entirely different contexts (e.g., “When I ran a project in Kenya, we sourced security services locally but IT services internationally, so we will do the same here in Ghana.”). Worse yet are decisions based entirely on one-off conversations or personal relationships, as these lead to operational inefficiencies and perceptions of unfairness among local stakeholders.

These approaches leave multinational companies without the hard data they need to make strategic decisions on local spending. When relying on qualitative information alone, supply chain managers can end up procuring goods and services from underdeveloped local sectors or, conversely, sourcing them internationally without knowing that they are available locally at a comparable quality and lower cost.


Optimizing Supply Chains With the Power of Data

Sound data analysis can fill information gaps to help companies optimize the efficiency of their local content investments. Economic analysis tools, such as DAI’s Local Content Model (LCOM), match the demand for goods, services, and labor associated with a particular investment project with available local supply. Ultimately the analysis reveals, sector by sector, the most promising opportunities in the local economy for local content capture.

Armed with this information, companies can optimize spending decisions based on a clear-eyed understanding of what the local supply base and workforce can realistically offer.

Quantitative analysis can also increase return on investment associated with corporate social investments in workforce and enterprise development. For example, already sophisticated sectors would benefit relatively little from additional investment—as would sectors with extremely low capacity. By assessing the local supply base, companies can understand growth in an economy across sectors and use this data to determine, based on their needs and risk appetites, which corporate social investments will have a material impact on local economic development as well as their bottom line.


The Future of Local Content

Data-driven decision making is the future of local content strategy. Approaching local content policies reactively, with a compliance mentality, results in missed business opportunities and less productive government relationships. A rigorous quantitative approach certainly has its own challenges, such as finding and accessing reliable data and designing the complex economic models that underpin the analysis. However, with the right tools and know-how, multinational companies operating in emerging markets can harness the power of data and turn local content from a regulatory burden into an opportunity to de-risk investments and maximize shareholder value.