Smart machines are transforming the outsourcing world as we know it. By enabling software tools to perform repeatable tasks that require a high degree of skill, training and/or knowledge, Intelligent Process Automation (IPA) has the potential to fundamentally redefine existing service delivery models and contracting mechanisms, as well as reshape a number of specific processes and job functions within IT and business operations.
IPA in a broad sense comprises a variety of terms and a wide spectrum of capabilities including autonomics, Robotic Process Automation, cognitive computing and artificial intelligence. These capabilities range from completing very specific, clearly defined and repeatable tasks to tools that mimic human experts to those that can observe and "learn" from experience and apply that experience to perform sophisticated tasks. To summarize:
Robotic Process Automation (RPA) can be defined as software platforms that use "virtual robots" to manipulate existing application software in the same way that a person today processes a transaction or completes a process. RPA has broad applicability across process types, and requires business users to configure and deploy. Using rules engines and workflow, RPA systems are "taught" to perform a given business process.
Autonomics, meanwhile, are platforms used primarily for IT infrastructure operations where a "virtual engineer" applies high-level policies and algorithms to make decisions.
Artificial Intelligence (AI) refers to more advanced technology capabilities and can be further sub-divided into three categories. Artificial Narrow Intelligence (ANI) specializes in one area - such as, for example, playing chess better than a human world champion. Artificial General Intelligence (AGI) refers to a computer that is as smart as a human in terms of performing any intellectual task that a human being can. Finally, Artificial Superintelligence (ASI) is defined as a computer that is much smarter than any human in practically every field.
Both buyers and providers need to understand these various gradations of intelligence and how they can best be applied to real-world scenarios. In other words, the concept of "smart machines" is by no means a one-size-fits-all proposition.
Decisions around where outsourced work is located will be significantly impacted by IPA. Under the traditional model of labor arbitrage, the cost and availability for a given skillset is a key driver in determining the location of a service delivery center. Moreover, the value proposition of any sourcing location "hot spot" is based to a significant degree on skillsets and labor costs.
By enabling more work to be performed with fewer people, IPA undermines the basic premise of labor arbitrage. Put simply, cheap workers - however skilled or capable - now present a significantly diminished competitive advantage compared to software that doesn't require a weekly wage and never takes a holiday. Moreover, the processes most suitable for IPA - digital inputs and outputs, with rules-based decision making and no requirement for voice or in-person interaction - are the also the ones most likely to be offshored.
As the cost and availability of labor becomes a smaller component of overall service delivery, the weight of other factors such as language, culture, time zone and IP security will become increasingly important factors in service delivery location decisions. This change in priorities will force global enterprises to re-think their service delivery models, which today combine a complex mix of onshore and offshore locations designed to maximize the advantages of each location while making the hand-offs and touch points between locations as seamless as possible.
IPA also adds a significant wrinkle to end-of-contract decisions; specifically, by adding a layer of complexity to choices on whether to renew existing agreements, rebid work to new providers or repatriate services back in-house. First off, when considering renewal options today, clients must assess the impact of IPA on market pricing to determine if they are missing a potential opportunity to benefit. If they pursue an IPA initiative, they must decide whether their incumbent provider has adequate capabilities. If not, the challenge becomes to find the appropriate tool and/or solution provider.
Contracting mechanisms and pricing models will also be impacted by IPA, as FTE-based agreements (based on people and hourly rates) will be supplanted by outcome-based terms. This will give clients an opportunity to drive true transformation and significant cost reduction. Providers, meanwhile, will have meaningful incentives to protect margins by streamlining service delivery.
IPA is well-suited to a number of specific industry requirements, particularly in heavily regulated sectors such as healthcare, pharmaceutical and financial services. Banks, for example, must demonstrate rigorous oversight of third-party relationships across the service delivery chain; here, IPA tools offer enhanced speed and accuracy as well as a more detailed and sustainable audit log of activity - an essential criterion of compliance readiness. Another advantage is that tools can be easily scaled as well as quickly reconfigured or "taught" to perform a wide range of functions - ranging from invoice reconciliation to document review to data consolidation –without any need for training. Finally, by making onshoring increasingly viable from a cost standpoint, IPA gives banks operating in high-risk offshore locations a new lower-risk sourcing option.
In retail, meanwhile, IPA has the potential to significantly streamline support functions - consider customer service centers devoted to processing purchases and returns and providing basic product information.
Fundamentals Remain Constant
While IPA clearly represents a game-changer for the industry, in some respects the keys to successful outsourcing remain constant. The fundamental basics that still apply include the need to clearly define and articulate business objectives and requirements, find the right mix of providers, adjust to ongoing changes and apply governance mechanisms to effectively manage the relationship over the long term.