While the boundaries to global commerce are clearly eroding, and no longer do companies operate only within the confines of their own countries, the fact of the matter remains that all is not as seamless as it may seem.
Changing global regulations about data sharing, complex AI-based technologies, a shortage of skilled data scientists and the need for greater collaboration between companies and their service providers are driving a renewed focus on U.S.-based nearshoring as the optimum way to reach business goals.
Companies are turning to U.S.-based nearshore providers because despite the growth in traditional offshoring, there have been bumps in the road. In some areas where the cost of labor is cheap, the workforce might be less educated and skilled, and they may rely on outdated frameworks and technologies, resulting in lower quality standards. And, with the rapid pace of business, distance can be a problem.
So how exactly are new market factors driving a resurgence in U.S.-based nearshoring?
Data privacy and other regulatory controls.
The growth of data-driven businesses and the ability to collect data on virtually anyone, has resulted in stricter data privacy regulations everywhere and the U.S. is no exception. For example, the U.S. telecommunications industry has rules governing the ability to share data overseas, and that includes sending data to software development providers. Since most of the AI applications that are created today, especially machine learning and analytics tools, require tons of training data it can be a major problem when the data can’t be easily sent to the provider without massive cleansing, obfuscation and encryption. Nearshoring to U.S. providers can eliminate this problem, enabling seamless transfer of vital data that fuels AI-based applications.
Complex AI-based technologies.
Given the rapid pace of technology advances, companies are under pressure to continually enhance software to improve business value, provide market differentiation and competitive advantage. Yet, emerging solutions that incorporate machine learning, chatbots and other smart apps are complicated to build and maintain, requiring the specialized expertise of software engineers and data scientists – who must remain involved for long-term training of AI algorithms. Because of the expertise that’s required for these cognitive solutions, as well as the need to truly understand specific business needs, working with nearshore providers that can relate to the local challenges and help companies derive valuable insights from smart solutions is becoming more crucial than ever.
A shortage of data scientists.
LinkedIn calculates that, in August 2018, employers were seeking 151,717 more data scientists than exist in the U.S. And, according to an article on The Quant Crunch report, demand is expected to rise 28% by 2020. These statistics indicate a major talent shortage when it comes to filling data science positions. Yet even without a talent shortage, many companies don’t find it cost-effective to hire internal data scientists to constantly maintain and grow AI solutions. Both of these factors are creating new demand for nearshore providers that have both the skill-set and understanding of local business needs to drive continued evolution of AI apps.
The need for collaboration.
The development of complex AI-based apps often requires close communication between the customer and offshore teams. While a major reason for the failure of software projects is a breakdown in communication, it’s hard to have real-time communication with an outsourcing partner when they are located several time zones away. Companies that conduct nearshoring from the U.S. typically experience less integration, cultural differences and other risks than European and APAC companies that more frequently outsource to neighboring countries with significantly different languages, currencies and regulatory requirements.
Nearshoring is clearly on the rise when it comes to today’s business needs for advanced software development. But to help ensure that they have a positive engagement, companies should consider the following in their software development outsourcing strategy:
- The education and skill of the workforce – with emphasis on quality commitments
- Specialized expertise and resources – especially when it comes to machine learning, deep learning and other specialties
- Language and cultural barriers
- Alignment between your approaches
- Proximity and the need for ongoing communication
- Regulatory issues. For example, in the U.S. government mandates require that work for many aerospace and defense contractors and healthcare providers is conducted by U.S. citizens, which would include U.S. territories such as Puerto Rico and the U.S. Virgin Islands.
With today’s fast pace of technology innovation, driven by AI solutions that need to think like the people they are supporting, companies know they can’t do it alone and are realizing the benefits of outsourcing in its many forms. Yet, we can expect to see the nearshoring segment of the market take off at lightning speed as companies begin to more fully grasp the added value of having a software partner closer to home, abiding by the same regulations and business practices and ultimately becoming a real extension of the business, as well as contributor to its overall success.