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Are You Getting the Most Out of Your Nearshore Digital Transformation Partner?

Published February 4, 2021

Written by: Carlos Meléndez
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Carlos Meléndez

Carlos M. Meléndez is the COO and Co-Founder of Wovenware an artificial intelligence and software development company based in San Juan, Puerto Rico. Mr. Meléndez has a bachelor’s degree in Electrical Engineering and a Juris Doctor both from the University of Puerto Rico. Mr. Meléndez is also the Vice Chairman of the Board of ConPRmetidos a non-profit organization that connects people to foster commitment with the personal, social and economic development of Puerto Rican communities wherever they are.

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Given the supply chain disruption, business shut-downs and economic uncertainty caused by COVID-19, it’s never been clearer — doing business closer to your own shores is coming back into vogue.

With recent restrictions on H-1B workers and a tech talent shortage, selecting a nearshorer is fast becoming the first step on a company’s digital transformation journey.

The benefits of working with an outsourcing provider close to home have long been touted. It provides the cost and time savings of working with an offshore firm while avoiding the challenges that arise with different time zones, languages, culture and varying regulations.

Yet, for firms seeking to undergo digital transformation via AI or other disruptive technologies, it’s no easy task selecting the right nearshorer for the job. Digital transformation is an ongoing process and requires constant collaboration between a business that wants to reach the next milestone and expert professionals who can create the vehicles to get them there.

With this in mind, it pays to do your homework and consider the following eight recommendations before selecting a nearshore partner:

  1. Broad experience, expertise is key. It’s important that the firm you hire has deep experience and certifications in the most current AI, software development platforms, methodologies, and applications plus considers training to be an ongoing process.
  1. Location, location, location. If you’ve vetted several firms and have confirmed their expertise, select the firm closest in proximity to you. It will provide better opportunities for collaboration as well as an understanding of local laws and regulations. While nearshoring doesn’t necessarily mean working with a company from the same country, it’s a good idea for a company in Italy to work with a nearshorer in Italy – even if a firm in the U.S. seems more appealing.
  1. Hire team members not just nearshorers. While you most likely will hear from senior management when reaching out to a nearshorer, always ask to speak to the actual professionals who will be working on your team. Request to see their resumes and meet with them as you would with any job candidates. 
  1. Be wary of outsourcers that outsource. One-stop-shopping is always a time saver. For those nearshorers that promise to do it all, the full lifecycle of software and AI services, it’s important to dig deeper and find out if they have in-house talent to handle it all or if they use specialized service providers to work on parts of the project. Often, you will never know who handled your project and there’s greater risk of error and delays when one firm is transferring the project to another one. When it comes to AI projects that utilize your private and sensitive data, it’s important to keep it with one outsource provider.
  1. Speak to the problem clients. Before selecting a nearshorer, ask to speak to clients with projects that didn’t go as smoothly as planned. It’s quite predictable what clients who are highlighted on the website will say about the nearshorer, but interesting insights can be found when you talk to a company that had problems. It’s good to learn how the company resolved them and how they worked with the client.
  1. Inquire about data privacy procedures. As mentioned above, AI projects are very data intensive and require the sharing of confidential information. Inquire about the firm’s compliance to international security standards and whether or not it has been audited. For AI projects involving data specialists, it’s also important to find out if they are all under a non-disclosure agreement (NDA). Data specialists are private groups of employees who perform data labelling to prepare an algorithm for training. Firms that use public crowdsourcing means for labelling data have no way to ensure data privacy or secure NDAs. 
  1. Diversify the team. When outsourcing an AI project, it’s always a plus when the team who will be training your algorithm to make decisions is comprised of professionals with diverse backgrounds and experiences. It helps eliminate bias in AI and can provide you with the objectivity you need to make sure your own unintentional bias is not being built into your solution.
  1. Look for soft skills. Unlike the days when software developers worked in siloes, in the back office or data center, today’s complex solutions and AI applications require more than technology expertise. When reviewing your nearshoring team members’ qualifications and credentials, also inquire about their ability to be empathetic, understand the challenges of specific industries and take on a business mindset. AI needs to think more like humans and less like linear technology solutions. 

Nearshoring is fast becoming the key to accelerating AI and other digital transformation projects, but it requires a partner you can trust that will be with you for the long haul. Yet, despite all of the key indicators that can help you determine if a firm is the right fit for you, what may be most important is trusting your gut and selecting a firm with whom you can feel most comfortable. After all, collaboration is the real key to digital transformation success. 

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