New digital world, new pricing models: Time to get relevant – fast!

By Nuria Mor

Service delivery models are experiencing significant changes due to the introduction of disruptive technologies such as robotics process automation (RPA) and artificial intelligence (AI). Now, in the digital era, is the time to transform the way business process services are delivered, including new ways to contract with clients to better share risks and rewards in a way that is realistic and executable for a digitized operating model.

Fixed-price or full-time equivalent (FTE) commercial models are no longer sufficient, primarily because they don’t resolve essential client needs in two ways:

  1. Prices cannot be mapped to the actual consumption of new types of resources, such as robots.
  2. The models are static and don’t provide an incentive to transform processes, change behaviors or share gains.

A need exists for a “hybrid workforce pricing model” that combines agents, robots, virtual operators and automation applications.

Many business service providers recommend the use of outcome-based pricing models to put “skin in the game” and share commercial risk. The reality, however, is that few have put such a model into practice.

Through recent Business Process Services (BPS) engagements, DXC Technology has increasingly adapted pricing mechanisms to fit these new transformation requirements. Here are two pricing models DXC is using more often with existing and new clients:

    • Smart transaction-based pricing (STBP) Transaction-based pricing models have been in use for some time. However, to adapt to the new digital era, it is important to define “smart transactions” with differentiated prices. For example, an invoice that can be processed end-to-end by a robot is priced lower than an invoice containing exceptions that require manual intervention. This incentivizes clients and outsource providers to move to a “near-perfect,” exception-free automated type of transaction, improve processes and reduce costs. STBP models are designed to be simple in measuring and reporting. They are comprehensive, so they will incentivize continuous improvement for clients and providers alike. STBP models are recommended for business processes that have reached high levels of maturity and standardization — perhaps across different geographies; are delivered in a consistent manner (same technology and, often, delivery locations); and where technology allows for accurate volume reporting. When calculating price, it is important to develop a baseline (volumes, effort, cost) rooted in historical data and to plan for a shadow run period after the go-live date to confirm the accuracy of the calculations and business case realization.
  • Virtual operator-based pricing (VOBP) In a world where more and more workloads are being shifted from human agents to robots, a virtual operator is defined as an automation resource that delivers a workload equivalent to that of a human (e.g., 8 hours / day workload equivalent). Naturally, the cost of a virtual operator is well below that of a human agent. DXC therefore uses simple virtual operator rates as the basis for pricing. The beauty of this model is its complete transparency with regard to the immediate savings achieved in comparison to existing physical resources.

The pace of technological innovation expected by our global clients continues to increase rapidly. Technology innovation is a client metric. Leading edge pricing models are required to align to new technology capabilities, thereby ensuring that real value and savings materialize quickly. In turn, this gives our customers the competitive edge and stickiness with their clients.

Learn more about DXC Agile Process Automation.

Nuria Mor is a senior BPS solution architect at DXC Technology. She has almost 15 years of experience in architecting and delivering finance and accounting outsourcing services. Recently she has been engaged on several opportunities with billion-dollar revenue businesses to deploy robotics solutions at scale. DXC calls this Agile Process Automation.


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