KPMG recently released via Webcast the results of the 2018 edition of its annual joint market study with HfS Research on the state of operations and outsourcing.
As the title implies, this year’s edition of the study focused on the state of business operations among global enterprises in general and as it relates to the use of alternative business and information technology (IT) services delivery models, such as shared services, outsourcing, and global business services. As with last year’s study, strong focus was placed on assessing the impact that intelligent automation (IA) will have on service delivery models, best practices, and investments.
Defining intelligent automation
Results from the study find that near-term expectations are high for returns from advanced data and analytics (D&A) and IA investments. In some respects, IA is viewed as a cure-all or perhaps even panacea solution and enabler for a broad range of organizational strategic and tactical needs and demands, including being a major driver for business and services delivery operating model changes.
Figure 1 illustrates the main drivers for operating model changes and highlights the need for organizations to determine how to best balance efficiency and effectiveness goals.
Figure 1 – Main drivers for operating model changes
These operating model changes continue to drive increased centralization of business and IT services delivery (see Figure 2). Functional shared services is anticipated as the top service delivery operating model in three years, followed by global business services, the latter of which is expected to over triple in propensity in this time frame. Greater use of GBS, however, does not equate to greater maturity of GBS operations, with greater maturity implying delivering benefits above and beyond cost savings and process efficiency gains to enable greater process effectiveness and deliver more value-added and strategic benefits to the business (e.g., predictive and prescriptive analytics, greater back-, middle-, and front-office integration, improved customer experience, and faster and more effective M&A efforts). Greater use of IA technologies is one means through which GBS organizations expect (hope?) to gain more strategic and value-added capabilities.
Figure 2 – Operating models in use continue to shift toward centralization
To this point, Figure 3 illustrates the top enablers for these organizational changes. Clearly, the emphasis has shifted from changes to service delivery models—more use of shared services, outsourcing, global business services—which were the prevalent and preferred drivers for changes a few years back to a much greater emphasis on the use of advanced technologies, such as IA, cloud, and advanced D&A. While these technologies continue to mature and their usage expands, it is still much easier to adopt and deploy them than to maximize the potential benefits of their deployment.
Figure 3 – Top enablers for organizational change
Expectations of gains from IA investments are often unrealistic given relative lack of organizational maturity in pursuing advanced D&A and IA investments. This is particularly the case relative to possessing requisite skills to deploy and manage the technologies, having the talent to fully exploit these tools and services, and garnering adequate investment levels, both to deploy and manage D&A and IA. Many organizations also struggle with prioritizing investment areas, coordinate and integrate efforts across functions, business units, and geographies, and suffer from the current state of weak data integration and master data management capabilities.
Skills and talent are especially vexing challenges, and IA efforts and ambitions will continue to suffer from talent and skills shortages and uncertainty over how to deal with leftover talent—full and partial head count—from process automation efforts. While job losses from automation are inevitable, an optimistic 76 percent of survey respondents expect to retrain and retain at least one half of affected employees and 48 percent expect to retrain and retain over 75 percent. This may prove wishful thinking given the more complex and strategic skills required for staff to work with and fully leverage IA tools and services in the future and the historically poor track record for organizations retraining large swaths of legacy workers.
It is clear that business operational models will continue to focus on centralization. Effective use of IA investments will gain in importance and priority over increased usage of various alternative service delivery models. What is more uncertain is what shape and form these centralized models will take, how much automation will replace human workers, and how and how much can legacy back-office operations, primarily historically focused on ongoing cost reduction and increment process efficiency gains, step up to deliver more strategic services in a coordinated manner across functions, business units, and geographies. These are daunting challenges for organizations but ones that if not met will accelerate the ongoing demise of the legacy business and IT services organizations and models. For additional information on this topic, please visit www.kpmg.com/us/gbs.