Subscribe
Close
  • Free for qualified executives and consultants to industry

  • Receive quarterly issues of Area Development Magazine and special market report and directory issues

Renew

Assessing Emerging Markets for Cross-Border Location Strategies

Conducting an accurate financial assessment of emerging markets for global manufacturing means the difference between project success and failure.

Winter 2011
Corporate real estate executives often take the lead in establishing operations in emerging markets. Given these markets' complexity and lack of transparency, this role comes with inherent challenges. The CFO must ensure an accurate financial view of a direct investment project. This might seem simple, but experience suggests otherwise. Internally, project teams must develop cohesive project specifications and project assumptions. Externally, the complexities of emerging markets, geographic variability of factors, and access to accurate data mean substantial research and validation. But there are better ways to develop a financial model for manufacturing direct investment decisions.

Assemble the Right Project Team
The only way to obtain an accurate view of an investment is to carefully coordinate project specifications, assumptions, and financial model architecture. For all three to work smoothly, input from a team of functional subject matter experts is needed. This project team should include representatives from company strategy, finance, tax, HR, supply chain, real estate, purchasing, sales and marketing, and engineering departments.

This team ensures that model logic for all inputs (project assumptions and specifications) that will drive the financial analysis is sound. It is not uncommon for the modeling exercise to require multiple rounds of refining until the team is satisfied with the harmony of the inputs. During this planning stage, the model philosophy and costs that the model should reflect as part of company responsibility, versus external to the model and the customer's responsibility, are paramount. This consideration will affect how to model revenue, logistics costs, and tax.

Five Categories of Financial Assumptions
The major assumptions supporting the financial assessment can be divided into five categories:

Revenue - volume of products sold or payments received from customers for company products;
Cost of Goods Sold (COGS) - the costs of developing, manufacturing, storing, and distributing products;
Operating expenses - general costs not directly associated with the production of products;
Direct tax - the amount of taxes a company pays to federal, state, and local governments based on its level of income; and
Other factors - other considerations that influence a project.

1. Revenue
Projected revenue assumptions of a new operation are critical to financial performance. Developing revenue assumptions is a challenging task, particularly for new investments into regions in which a company has limited presence or sales experience. The assumptions require a forecast from the strategy or corporate development organization and input from sales and marketing considering product mix, selling price, destination, and unit price increases for inflation or other pricing strategies.

Because an investment's financial feasibility is closely tied to revenue, the implications of inaccurate revenue assumptions can significantly impact ultimate output and the metrics of financial performance. To avoid overstating the financial performance of an investment and inflated stakeholder expectations, revenue should be modeled under best- and worst-case scenarios. Testing revenue assumptions using both potential customers and suppliers may be necessary.

Ask Area Development

If your company is seeking an overseas site and you have business questions on financial modeling, submit them below to Ask Area Development and the article authors will respond.
2. Cost of Goods Sold (COGS)
COGS inputs are the first of two categories of pre-tax costs. COGS inputs model the direct costs attributed to the production of goods sold by a company, such as raw materials, transportation, direct labor, and utilities. COGS data inputs can greatly vary geographically. A key consideration when modeling raw materials is the supply source and whether the company will continue to leverage its existing supply base or move to a higher percentage of in-region or in-country supply.

Transportation costs also vary greatly. Third-party logistics (3PL) provider rate quotes can range based on in-region and in-country capabilities of the 3PL, and will vary for each shipment segment. Labor practices and regulation vary significantly among countries, and developing inputs to accurately reflect shift premiums, overtime, collective bargaining agreements, and benefit loads takes time. Even obtaining utility costs can be challenging due to temporal cost variability based on consumption time or the variability in water charges based on industrial park capabilities, water capacity, and extraction rights.

Exclusive Research