Breaking the glass-ceiling of Robotic Process Automation (RPA)
Introduction
Robotic Process Automation (RPA) describes a computing platform that automates data processing tasks by mimicking the behaviors of humans; effectively automating the actions of a human like a software robot. Many of the tasks RPA software apps fulfill are simple ones; like displacing the need to key in data, or to take data from one app to put it into another, maybe even to replicate data cleansing, analysis, and reporting admin activities that humans would otherwise have to perform. It’s particularly successful in financial services, customer service centers, back-office shared service centers, and in supply-chains that have previously depended on hard-copy documents.
RPA is big. According to Gartner Inc., RPA is the fastest-growing segment of the global enterprise software market, with software sales growing in 2018 by 63.1% in 2018 to $846 million. What’s more, Gartner expects RPA software revenue to reach $1.3 billion in 2019.
Like many technologies (so-called ‘knowledge management systems’ and ‘enterprise mashups’ come to mind), RPA has enjoyed a honeymoon period when it could do nothing wrong. However recent press articles are pointing to a glass ceiling on the true business potential of RPA as a sustainable long-term solution rather than a rapidly applied sticky plaster to a seismic fracture in enterprise computing architectures.
In this article, I outline the problem RPA was born to solve, why it works ‘some of the time’, and what causes it to fall short of an end-game solution. Does it offer a long-term solution, or is it just a temporary ‘sticking plaster fix?’
Read the full article to find more…
The problem Robotic Process Automation (RPA) was born to solve
RPA software has been able, in part, to overcome one of the biggest challenges facing enterprise IT. It’s what some market analysts describe as the ‘long-tail of demand for enterprise apps.’ Here’s why it’s so important.
How most enterprises prioritize their spending on IT
Since the origins of business computing, the largest share of the enterprise IT money pot has gone towards IT systems that operate the core functions of business. Organizations develop their business-critical _Systems of Record_ around core departmental structures and process areas. For most of us, that means financial systems, Human Resources, perhaps e-commerce stores, manufacturing systems, parts and services, etc. These BIG and HIGH RISK areas of enterprise computing house the Crown Jewels of company data and therefore need to be guaranteed to work day-in-day-out without hick-ups. That’s the promise of companies like SAP, Oracle, and Microsoft that offer Enterprise Resourcing Systems, Financials, and Human Resource Management.
The emergence of two-speed enterprise IT
Big-ticket IT systems (such as Enterprise Resource Planning platforms) are costly and slow to change. In many respects, companies buy these applications to purchase the hard-coded best practice processes they imprint on the enterprise. That means, no single organization gains a competitive advantage from their investments in this kind of enterprise IT. What they _do get _is the ability to reliably ‘keep the lights on.’
This slow pace of innovation in IT teams — otherwise focused on upgrades and a long list of legacy migrations — has starved business leaders of the competitive advantage and agility they need to survive and thrive in the digital age. IT teams that prioritize core systems implementation and maintenance over the needs of users have been accused of being ‘sales prevention departments’ or ‘the department that says no more often than yes.’ In consequence, some organizations have grasped the nettle and appointed dedicated Digital Leaders to create a two-speed approach to IT; one team (i.e. ‘fast-IT’) is oriented around fail-fast prototype-led skunkworks innovation, the other (i.e. ‘slow-IT’) left in the back-office to keep the lights burning.
According to McKinsey, ‘A two-speed IT architecture will help companies develop their customer-facing capabilities at high speed while decoupling legacy systems for which release cycles of new functionality stay at a slower pace.’
There are challenges with such a progressive approach to tackling the issue of slow-paced IT. Inevitably, those employees in the ‘fast-paced IT’ department find themselves on the fast track to promotions because they are seen to be doing more to progress the business. Leaders and workers responsible for legacy systems can find themselves marginalized and treated as second-class citizens. The opposing cultures that exist in fast and slow IT teams can ultimately create a ‘who’s best’ war that results in proactive attempts to de-rail projects.
The need for business agility and continuous change is the new normal
In a world where business plans change so frequently, and digital technologies continuously offer smarter and more cost-effective ways of doing things, additional apps are needed to achieve a competitive advantage. The fundamental shortfall in enterprise IT has been the gap created by the shortfall in the agility of ‘everyone gets the same meal’ enterprise Systems of Record to adapt to the specific business model demands of an enterprise.
The unresolved long-tail of demand for enterprise apps
How this shortfall manifests itself is in the long tail of demand from departments and users for apps that can fulfill their data processing needs. The global workaround for this is found in desktop apps like Spreadsheets, used to create self-service apps that ‘get the job done’ or the provision of more man-power to key-fill records, copy and paste from one app to another — or contract third parties to get the job done. It’s also no secret that, in most companies, paper documents take the load for many of the shortcomings of systems. They perform the key role of temporary data gatherer, transporter, and filing records for millions of business-critical workflows.
What every company wants is an enterprise IT architecture that ensures business continuity, that installs best practice business process workflows and compliance practices, and that ultimately serves its user community in an optimal way to deliver a competitive advantage; by translating the customer value an enterprise produces ‘into cash’ at the lowest operational cost.
When RPA came on the enterprise IT scene, around seven years ago, it was seen as the solution to this unforeseen gap in enterprise computing capability. Increasingly though, practitioners have become more alert to the strengths and sensitised to the limitations of the technology. I dig deeper in the next section.
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Why RPA works albeit ‘some of the time’
The Upside of RPA Software
Robotic Process Automation software is very good at mimicking humans. For example, it can be programmed to reliably cut data from a browser or application page (we used to call that screen scraping in the easy years) and paste it into a new application. It does the jobs humans would otherwise have to do manually. Indeed, many of the tasks you do today using spreadsheets can probably be performed using RPA tooling. It enables departmental managers to pay a small fee to automate a task that frees up workers to do more useful things.
At a time when Human Resources are expensive, it offers an alternative to growing the payroll or offshoring work.
One of the most influencing factors in the success of RPA software lies in its ability to act immediately on ‘the job that needs to be done’ without requiring an organization to program new systems integrations or adapt their processes. This means any given task (suitable for RPA automation) can be implemented without CHANGING EVERYTHING ELSE.
Ultimately, this is a double-edged sword. Replicating a manual task doesn’t necessarily optimize or improve it fundamentally. That’s why organizations adept at implementing RPA software embrace a ‘now, next, and new’ approach to operational improvements, namely:
- Offer a ‘quick-fix’ NOW by mimicking the human task through an RPA software automation
- NEXT, do what can be done to fine-tune the activity (perhaps by installing proper data integrations and APIs with back-office systems) to create a more robust solution
- Finally, offer consultancy services to build something turnkey that offers a NEW way of getting the job done better.
For simple automation of repetitive manual data processing and reporting tasks, RPA software can be a useful and effective tool in the box of IT departments. It can be a great stepping stone used in digital transformations — but it’s only an interim solution to overcome the log-jam of demands on IT for effective apps.
The inability of RPA technologies to do more than ‘neat, short-term task automations’ will ultimately forge a glass-ceiling this genre of technology was never equipped to break through.
The Down-side of RPA Software
Embracing RPA Software can install some hazardous behaviors and outcomes in organizations that can ultimately cause IT effectiveness to suffer. I highlight them here.
Generating conflict: IT teams at war — The first point on this list I mentioned previously: In a move to encourage two-speed IT, organizations can create a war between progressive IT teams paid to fast-track new applications developments using fail-fast methods, and the legacy IT function paid to _keep the lights on_.
Compromising the power to make smart IT decisions — Given that RPA software is appealing to departmental managers who ‘just want to get the job done and free up their people’, it can encourage maverick leadership behaviors that create conflict between management roles paid to keep systems working and data safe, and those departmental and functional leaders charged with achieving operational outcomes. Most would agree, although it’s not always true, that IT leaders should ultimately be the people to make IT decisions.
Adding to the legacy burden — At a time when IT teams are hard-pressed to keep up with existing demands for legacy migration and the unification of data repositories (to make data more re-usable), RPA can create hundreds of more apps that fragment data and create an _even longer-tail _of legacy burden stretching out for years to come.
Ignoring better alternatives
There’s more than one way to solve any business challenge. In the case of process automation, assuming RPA is the solution to automation challenges can blind decision-makers to alternative technologies and solutions. For example, it’s sometimes a better solution to offshore tasks end-to-end processes to an expert provider rather than attempting to automate steps in a process.
Starting automation at the bottom / a solution looking for a problem
In the hierarchy of business automation efforts, the top line goes to automating business models. The second level is about automating processes, and the third, task and activity augmentations. When business models change, inevitably processes are adjusted or completely negated. Equally, when processes are re-designed, many of the data processing activities (that RPA software is designed to approve) become redundant. It could be argued that project teams charged with implementing RPA become obsessed with finding ‘tasks to automate,’ ultimately creating unnecessary automation costs that could otherwise be avoided.
So what’s the alternative?
Like any discipline, enterprise IT has its fads and on-trend tools (think CRM, big data, ECM). RPA has enjoyed its time in the sun, but enterprise IT teams are now turning to smarter development ware to install the agility they need in their systems architectures. In short, they’re looking for a more robust and integral tech platform that serves to extend their core ERP to the outer boundaries of their (ever-adapting) business model demands.
The newly emerging genre of technology to displace RPA is called High-Productivity-Platform-as-a-Service, or HPaPaaS, proving once again that the enterprise IT industry loves its acronyms and really struggles to come up with good names for its tech genres!
HPaPaaS tech platforms are cloud-based ecosystems for designing, deploying, and operating business applications. Key players include Appian, AgilePoint, AppSheet, Betty Blocks, Caspio, Encanvas, Mendix, ServiceNow, Outsystems, and Zudy. More advanced solutions unify data governance to ensure all data gathered and used in applications is accessible to the enterprise and always safe. Unlike the traditional model of app stores, think of HPaPaaS platforms as a way to progressively build apps for departments and small teams to fill the gap that exists between inflexible systems of record and the full extent of computer processing needed to fulfill turnkey business models.
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Many of the common-to-all characteristics of applications (such as user management, user groups, site structures, organizational designs, process escalation models, etc.) are underpinned by shared tables in app ecosystems. It means app designers don’t need to keep re-inventing the same wheel time and again; dramatically reducing time-to-value for new solutions.
Modern HPaPaaS solutions are either code-free or code-light which means, that by using them, it takes much less time to produce new apps, and they prevent a new legacy burden from being created. Killing the coding and scripting overheads reduces testing, tuning, and integration costs. In the most advanced solutions, code-less interfacing tools make it much easier to produce robust data integrations with both legacy and cloud (SaaS) platforms.
Through the emergence of HPaPaaS technologies, enterprise architecture approaches are more likely to start from the top of the automation tree — by considering what capabilities and processes are needed to automate business models — rather than a bottom-up approach, as is the norm with RPA deployments.
Unlike RPA technologies, HPaPaaS solutions equip IT teams with the rapid authoring and deployment tools they need to orchestrate robust (and sustainable) IT solutions to satisfy departmental and small team demands for task automation.
About the Author
Ian Tomlin is a seasoned marketer, entrepreneur, and business leader with a 30+ year career at the intersection of strategy, technology, and marketing. As the founder of successful businesses, including Newton Day Ltd, Ian brings a wealth of expertise in guiding companies toward compelling brand stories. Reach out to Ian via LinkedIn to transform your marketing approach and tell your brand story effectively.
