How Do You Optimize Talent (And Salaries) Globally?


How do you optimize talent resourcing decisions? This question is particularly relevant for Shared Services Organizations (SSOs) with a global footprint, which can leverage locational advantages – but it also applies to regional or in-country operations seeking city-by-city comparisons.

One trend that weighs heavily into this question is the shift towards effectiveness trumping efficiency in Shared Services roles. In other words: the search is on for talent that can deliver the value-adding requirements of discerning customers, as opposed to simply providing lowest cost services. So, within these parameters, where do you find the right solution for your organization?


SSON Analytics, a data analytics center for the Shared Services and outsourcing industry, has developed a comprehensive database of Shared Services salaries, that are comparable across a broad range of functions, skill sets, education, seniority, and tenure – across 1,400 different locations [see also: City Cube]. The purpose of this resource is to support optimal recruitment practices for SSOs, which best align with the strategic objectives of the enterprise.

In this report we summarize some of the key findings from SSON’s salary database. For SSOs evaluating their talent management strategies, the ability to compare salaries for a specific functional resource across a broad range of variables, in both well established and less well established locations, is a key tool now at their disposal.*

By ‘slicing and dicing’ roles and salaries to compare them across locations, SSO leaders can, on the basis of solid data, tap into talent where it is most lucrative, and deploy it where it is most needed.

A recent trend in the US attempting to ban employers from asking job candidates about their salary history, is interesting. Although the intent is to prevent systemic underpayment, particularly considering the gender pay gap, anecdotal evidence suggests that the legislation is not achieving its objective. It does raise an interesting point, however, in that employers are being exhorted to “price the job, not the person” to arrive at a ‘fair’ salary for a given position.

A Harvard Business Review article suggests that ‘current salary’ should not be a starting point for what an employer is willing to pay. Instead, it says, “compensation should be a data-driven decision based on the current value of a given position in the talent market.” The HBR also comes down in favor of tweaking the process for setting pay expectations, by positioning a candidate within a salary range, based on their specific skill or experience level. SSON’s Salary Index  promotes this notion of matching salary levels to the market, the skills an individual brings to the table, professional qualifications, level of experience, and seniority, based on the forces of supply and demand.


In determining optimal human resource deployment, a key objective is the ability to ramp workloads up or down seamlessly, and therefore support the business as it expands or contracts, without undue bottlenecking. Optimal resourcing decisions are made not just on the basis of salary, therefore, but also on the basis of talent supply, availability, growth trajectories, and, of course, competition. In addition, where a key determinant of hiring includes access to a steady graduate stream, real-time data on entry-level salaries is important. 

Note: This article is an extract from the SSON Global Shared Services Salary Report 2017 – A comparison of salary cost, talent availability, market saturation, skill sets, maturity, and recruitment growth trajectories to help practitioners optimize their global staffing footprint. 

Download the full report to find out:

  • How to optimize talent resourcing decisions
  • How shared services roles are different
  • What drives salary
  • Which global cities are untapped and offer excellent potential to first-strikers