The Future of Outsourcing – From Traditional to Next-Generation

Stan Lepeak from KPMG explains how new forms of next-generation outsourcing are on the rise while traditional outsourcing models are declining, and the different types of measurement required for this growth beyond simple deal size.

The outsourcing industry is moving into a period of great flux, a reality driven by declining benefits from labor arbitrage, buyers’ shifting focus from cost savings to process improvement and value-added capabilities, general industry fatigue, and the growth in the maturation of intelligent automation (IA) technologies.

All of the above changes, especially those driven by IA technologies, will significantly impact the industry in both positive and negative ways on both the buy and sell sides.

Recent findings from KPMG highlight the declining interest among buyers of both ITO and BPO, as shown in figure 1.

Figure 1 – Traditional Outsourcing’s Decline

But the reality is more nuanced than this. While traditional outsourcing models are declining, new forms of next-generation outsourcing (Figure 2) are on the rise, though this growth requires different types of measurement beyond simple deal size.

Figure 2 – From Traditional to Next-Generation Outsourcing

Advancements in capabilities and the increased use of IA will have the greatest impact on the future trajectory and nature of outsourcing. Some of the impacts of IA include:

  • Organizations may choose to use IA technologies, especially RPA, in lieu of outsourcing.
  • Service providers that aggressively build RPA into their offerings will be able to lower their operating costs, and improve performance (e.g., through faster throughput, and less errors and rework), and gain competitive advantage against laggard peers, and secure or retain clients that might otherwise undertake RPA efforts independently.
  • Machine learning and AI, while more complex to design and implement than RPA, offer benefits beyond cost savings and modest to moderate process effectiveness improvements. They enable organizations to start to achieve true process transformation.
  • Service providers that can efficiently, expediently, and in a targeted fashion use ML and build AI capabilities into their offerings to meet customers changing needs will gain competitive advantage.
  • Outsourcing change management and governance efforts will become increasingly important as more work is automated and fewer humans are needed.

Outsourcing’s future

What will outsourcing deals look like in the future, and how will the market for these services change overall? Here are a few likely outcomes and scenarios:

  • The industry will move beyond a fixation on cost savings, focusing instead on delivering more value-added and strategic services.
  • End-user organizations increasingly embrace RPA as an alternative to outsourcing transactional work. But notes of caution on RPA here:
  • Building bots is not as easy as advertised, and more bots may be needed than originally estimated to automate a process
  • It does not make practical sense to automate inefficient or ineffective processes, and some processes are better off completely eliminated
  • Enterprises may not be able to automate and eliminate as many jobs as they assume, primarily because that bots typically automate tasks, or portion of jobs, not full jobs.
  • Building bots is not a one-and-done. As business needs change and business processes  evolve to address them, bots need to be modified,  overhauled, or replaced; this requires work to monitor process changes and understand their impact on existing bots, and a rework of the bots themselves
  • RPA is not an endgame. It is primarily a cost-savings play with some potential effectiveness benefits. But to achieve the full potential of IA, organizations must also pursue the more complex ML and AI efforts in tandem with RPA investments.

“While traditional outsourcing models are declining, new forms of next-generation outsourcing are on the rise, though this growth requires different types of measurement beyond simple deal size.” – Stan Lepeak, Global Research Director, KPMG US Management Consulting.

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Global business services organizations (GBS) in more progressive environments will take the lead on managing the breadth of firms’ outsourcing efforts in conjunction with shared services efforts; they will also drive cross-functional adoption of data & analytics (D&A) and IA.

  • Labor arbitrage will continue to wane in importance as an outsourcing driver as RPA becomes an alternative to lower cost labor.
  • The need for access to hard to find, highly skilled labor (e.g., data scientists, industry and functional D&A experts, and workers with advanced ML and AI skills) will continue to drive outsourcing to gain access to these skills.
  • Change management and governance will increase in importance as organizations implement more automation into outsourcing and shared services efforts and continue to pursue more strategic and complex goals.
  • The service provider market will continue to bifurcate and consolidate; providers that possess strong business acumen and horizontal process and vertical industry expertise will rise above those that just provide lower cost labor.
  • The controversial nature of outsourcing will change; “controversy-mongers” will focus more intently on the pros and cons of IA and its impact on workers and markets and hand-wringing over the “demise” of the white collar worker will grow.

The changes occurring today ushered in by the evolution of advanced D&A and IA, will have a profound impact on the global nearshore and offshore shared services and outsourcing markets.

Buyers that can co-opt these technologies will both lessen and limit their reliance on third-party providers, and gain significantly greater benefits from their efforts and investments.

Service providers that can integrate and exploit D&A and IA will strengthen their positions and breadth of services in the market, and end up on the top side of the bifurcation split. Even so, those that lag face likely insurmountable, long-term competitive challenges.

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