How RPA Will Win New BPO Deals
It’s no secret that robotic process automation (RPA) and business process outsourcing (BPO) are on something of a collision course over a shared value proposition: arbitrage of high volume, rules-based, and repetitive tasks. The business process outsourcer’s arbitrage is created by low cost, offshore resources; the RPA arbitrage is created by software robots that emulate and replace human users. The collision? It’s caused by robotic automation being as much as 65% less expensive than offshore-based employees; able to run 24/7 and immune to raises and benefits. This raises the question: how will this collision impact the ability of business process services (BPS) providers to win new deal opportunities?
It’s certainly clear what a provider cannot do: namely, it can’t deny the fact this RPA challenge to its offshore labor arbitrage business model will have a major impact on winning new deals. Granted, there may be powerful short term forces of self-interest fighting the conclusion that significant new changes are coming to the competitive equation.
After all, providers have spent years creating large employee headcounts specialized in various business processes; deals have been won year after year with that operational model; bonuses and promotions are tied to metrics around account growth through headcount expansion. Expecting senior management to easily embrace a radical transformation of their business model, performance incentives, and go-to-market approach is ambitious.
Regardless, there are compelling reasons for providers to do exactly that.
Third party research firms are independently validating RPA capabilities.
Clients have growing expectations that RPA arbitrage and performance will be part of a provider’s solution architecture and value proposition.
Industries are beginning to evangelize robotic tools as effective vehicles for internal process optimization initiatives.
How Robotic Automation Challenges BPS Competitiveness
In order to update the go-to-market approach and continue to win new deals, a BPS provider needs a plan of action that will accomplish two things: 1) establish precise RPA optimization metrics for solution architecture; 2) create predictive modeling for price-to-win forecasting.
Precise optimization metrics: BPS revenue growth depends on winning new deals; winning new deals requires a high value, compelling, solution architecture and global delivery model; any proposed solution architecture and global delivery model must survive the scrutiny of solution, delivery and risk management reviews; those three review boards expect to see a framework based upon proven deployment methodologies and known future state performance metrics. Citing a third party analyst’s confidence of 65% savings from RPA won’t get the job done.
Price-to-win forecasting: to be successful, a deal pursuit depends upon a provider’s ability to quickly produce a tight range of high level bid forecasts, based upon RFP data and informed assumptions fed into a proprietary modeling tool. These forecasts produce a price-to-win consensus that drives the solution architecture and delivery model. Unless a provider’s modeling tool can be modified to reflect both labor and robotic arbitrage, the resulting price-to-win will no longer be accurate. Worse, the pursuit team will know it’s not accurate, creating a speculative; second-guessing environment.
How Robotic Automation Increases BPS Competitiveness
If a BPS provider commits to investing in the steps that address these essential metric and modeling needs, it will significantly enhance its value proposition with RPA capabilities. In addition, through continuous improvement discipline, the provider will consistently increase its competitive edge over time, specifically:
Precise optimization metrics: the provider should act on two pieces of knowledge; the profile of processes in the RPA sweet spot and the incidence of those processes within the provider’s existing portfolio of BPO accounts. Based upon process prioritization, the provider should select a range of RPA tools and run pilot optimization projects for the priority processes – in parallel with existing offshore teams. Structured properly, these pilot projects – running parallel with existing labor arbitrage teams – will provide a baseline for arbitrage improvement metrics (or, just as importantly, not) that can be relied upon in solution architecture for similar processes within new deal opportunities. These pilot projects will also enable the provider to learn and apply reliable, effective, deployment methodologies in new deals.
Price-to-win forecasting: baselines for arbitrage improvement metrics, produced by the pilot projects, will allow the provider to make informed enhancements to its price-to-win model. Since the pilot projects will, at least in the beginning, only be accurate for a small percentage of any new deal scope, additional modeling adjustments must be made for the missed scope. This can be done by having the SME’s for all BPS verticals produce a percentage equivalency between the pilot processes and probable RPA-qualified processes within their vertical’s BPO work. In a simple, high level example: a new deal scope includes FAO processes that do not match any pilot project; therefore, FAO SMEs analyze and conclude those FAO processes have a 60% equivalency to a known pilot process and a 80% probability that competitors will leverage RPA tools for delivery of the FAO processes. The price-to-win architects will re-tool the model to reflect these factors.
While a thorough discussion of this topic requires more space than this blog allows, it is sufficient to answer the question: how does RPA impact BPO new deal competitiveness? The answer is: a great deal. Unless this is recognized by BPS providers, it is hard to see how they can remain competitive in the medium or long term. Fortunately, this impact is felt by the entire BPO marketplace and every competitor is faced with transitioning through the challenge. The differentiator between those who thrive and those who struggle will be the willingness to perform robust analyzes of go-to-market practices and tools, then invest in – and act on – clear and focused strategies to correct discovered weaknesses.