Many energy companies have embarked on significant digital transformation projects utilizing emerging technologies such as big data, cloud, mobile, APIs (Application Program Interfaces), natural language processing, machine learning and RPA (Robotic Process Automation) to reduce costs and streamline operations. In a recent discussion with an organization contemplating a major RPA initiative in the commercial and logistics area, the possibility of investing some time up front on process improvement, along with RPA implementation, was raised.
A Case for Process Improvement
The response from the client was basically, “No, why do I need to spend time optimizing or reworking processes anymore when I can just automate them?” The query appeared simple on its surface, but it calls into question the role that process improvement methods ranging from TQM, to ISO 9000, to Lean and Six Sigma plays in a world filled with software bots and AI workers (especially outside of manufacturing). It challenges the notion that master data management and governance are foundational for technology-enabled operational excellence and questions the value proposition of simplification in the form of reduced customization and application portfolio rationalization.
The reality is that it’s not quite so black and white but, rather, lies somewhere along a continuum for most companies contemplating how best to leverage automation. Below are four key reasons to consider combining process improvement/optimization with any major RPA initiative:
1. Lower Technology Implementation Costs
Implementation cost almost always represents one of the highest initial hurdles to any information technology initiative. Adding a process optimization lens to RPA projects can serve to reduce implementation cost in a number of different ways. Perhaps most obviously, automating fewer and simpler processes will require less IT resource effort. Time spent up front to clarify process owners, actors, steps/tasks, hand-offs, information inputs and outputs, etc. will pay dividends by simplifying requirements gathering. Standardizing and simplifying processes will reduce the amount of complex exception logic that must be configured or developed. Removing unnecessary or unrelated steps in the process may also present opportunities to reduce the number of integration points between systems, which can be a significant cost driver. These benefits continue to accrue throughout the implementation project lifecycle as the more focused process scope streamlines development/training of the bots, compresses testing complexity and effort and reduces delivery risk by eliminating many unknowns. Finally, many RPA solutions are licensed in a manner that increases cost based on the number of bots or processes being managed, so rationalizing the number of actors and process steps may provide some relief both at project kick-off, as well as in steady-state operations.
2. Reduced Ongoing Maintenance & Support Costs
The introduction of virtually any new technology such as RPA into an organization has the potential to increase IT operating cost by consuming infrastructure resources either on premises or in the cloud be it CPU, memory, storage, bandwidth or otherwise. On the other hand, many of the benefits of including a process improvement component in an RPA project compound over time long after the initial system implementation. Calling out these savings opportunities can help establish the benefits case necessary to secure project approval and ensure that funding can be made available for other value-generating investments across the IT portfolio. In many instances, the time savings on the business side alone are insufficient to justify the investment; however, identifying and articulating recurring IT cost reductions can help substantiate the business case. Fewer, simpler processes will result in a smaller sustainment burden for business subject matter experts and IT support staff given a lower number of processing errors that require troubleshooting. These savings multiply when the cost of shadow IT within the business necessary to compensate for poor data quality resulting from ineffective processes is taken into consideration. Patches, upgrades, extensions and enhancements to the underlying systems utilized by the automated processes will be less costly as a result of more straightforward integration and more compact regression testing requirements.
3. Enhanced Reliability & Resiliency
Recent business continuity events such as Hurricane Harvey or the Shamoon cybersecurity attack experienced by energy companies have highlighted the importance of an organization’s ability to operate and meet commitments to key stakeholders even in the face of significantly impaired IT capability. Process automation certainly has the potential to compensate for many of the mistakes of the past by powering through unnecessarily arduous tasks in a very cost-effective manner. However, energy companies should carefully consider how they will continue to operate if the RPA platform and/or related systems were rendered unavailable. During a business continuity incident business teams will need to fall back on manual transaction processing and during such episodes the benefit of optimized and well documented processes will be highly visible. Ensuring that the most critical processes are simple, well understood, documented and built to operate effectively in a business continuity context will be of increasing importance in the future.
4. Greater Enterprise Value Creation
The focus of most RPA initiatives in the past has been on taking cost out of the organization by automating repetitive steps performed by employees in transaction processing. However, adding a process improvement component from the outset can help identify opportunities to eliminate unnecessary processes altogether, streamline those that remain and create value in new and differentiated ways. While automation can simplify what oil and gas companies do today some of the most powerful prospects for its application lie in the ability to offer incremental value-added services to customers that cannot be provided in a cost-effective manner today. Leveraging a company’s past investment in skillsets such as BPR/BPM, TQM, ISO 9000, Lean, Six Sigma, etc. and partnering with outside experts can help identify and unlock these opportunities to make the most from a technology investment in process automation.
RPA offers significant opportunity as a central component in any oil and gas company’s digital transformation strategy. The ability to capitalize on the base investment to maximize return by controlling costs, increasing resiliency and delivering new value-creating capabilities can be significantly enhanced by putting early emphasis on process using time-tested methodologies and proven business insight. Project sponsors and managers of automation initiatives should carefully consider building these elements into their projects from the outset.
Oil and gas companies are regularly faced with many industry-specific issues to overcome. Such issues, including exploration and drilling, are often complex and intricate processes with many unique challenges to overcome. Data analytics can play a massive part in streamlining some of the most fundamental operations that are involved in the oil and gas industry.