How to Choose the Right Shared Services Model to Optimize Operations and Reduce Costs

How to Choose the Right Shared Services Model to Optimize Operations and Reduce Costs

Over the years, I have seen many organizations turn to shared services with one clear goal in mind: reduce costs. While that goal is valid, it is rarely enough on its own. Shared services work best when they are designed thoughtfully and aligned with how the business actually operates.

Choosing the right shared services model is less about copying what others have done and more about understanding your own processes, priorities, and constraints.

Start by understanding how your operations really work

Before deciding what should move into shared services, it is important to take a step back and look at your current operations honestly.

Which processes are repeated across teams or locations? Where do costs keep increasing without improving outcomes? Which activities are largely transactional, and which ones truly need local or strategic involvement?

This clarity helps avoid a common mistake: centralizing everything in the name of cost optimization, only to create bottlenecks and frustration later.

Cost reduction matters, but it should not be the only goal

Shared services are often positioned as a cost reduction initiative. In reality, the strongest results come when cost savings are paired with better operational efficiency.

Some of the most effective shared services programs focus on:

  1. Simplifying and standardizing processes
  2. Improving turnaround time and accuracy
  3. Creating better visibility through data and reporting
  4. Building a model that can scale as the business grows

When these outcomes are clear, cost optimization becomes a natural by-product rather than the only measure of success.

Choose a shared services model that fits your business

There is no universal shared services operating model that works for everyone. The right approach depends on your size, geographic spread, risk appetite, and long-term plans.

Some organizations prefer a captive shared services setup to retain control and build internal capability. Others choose a hybrid approach that combines internal teams with selective outsourcing. Larger enterprises may evolve toward a Global Business Services model to bring multiple functions under one governance structure.

The key is to choose a model that supports your business today while leaving room to adapt tomorrow.

Fix the process before you centralize it

One lesson that comes up again and again is this: centralizing a broken process does not fix it. It only moves the problem.

Process optimization for shared services should happen before or alongside the transition. This includes removing unnecessary steps, reducing manual work, clarifying ownership, and aligning service levels with business expectations.

When processes are simpler and clearer, shared services can deliver both efficiency and consistency without constant firefighting.

Governance is not optional

Shared services succeed or fail based on governance. Clear roles, decision rights, and performance metrics make a big difference.

Strong governance typically includes defined service ownership, transparent cost structures, and regular performance reviews. It also creates a healthy relationship between shared services teams and business stakeholders, built on trust and accountability rather than escalation.

Think long term, not as a one-time project

Shared services should be treated as a long-term capability, not a short-term initiative. As the business evolves, the shared services strategy should evolve with it.

Organizations that take this view are better positioned to manage growth, control costs, and support broader transformation efforts over time.

Closing thoughts

Shared services can be a powerful way to optimize operations and reduce costs, but only when designed with intent. A clear understanding of your operations, a realistic operating model, and a strong focus on process optimization make all the difference.

Shared services for cost optimization