By Richard Eichen, Partner, Fortium Partners, LP
At a recent Institute for Robotic Process Automation and AI symposium, we were discussing who owns Intelligent Automation (iA), IT or the Business Units. Attendees were IT Senior Leaders, consultants/integrators, and vendors along with a smattering of industry analysts.
The vendors, implementers, and advisors say it belongs to the Business, Cloud-based, with 4–6 weeks to build a first, basic, process. From the seller’s perspective, it is an easier to control buying cycle as IT usually publishes standards and reuses common vendors/consultancies with context learned over time, while each Business Unit often goes its own direction and moves faster.
As for 4–6 weeks, the consensus was it is possible to automate a basic process having a large percentage of transactions following the Happy Path, and where the Exception conditions are few, limited in error types, and easy to auto-repair. In Financial Services and Insurance, this is called Straight Through Processing or Low Touch. Internal to a company, there are examples of this class of processes, which is why many early Intelligent Automation adopters start with inward facing processes. Real-world hands-on experience has shown, however, the more realistic estimate for a simple but useful first process is 8 weeks, where an upfront Process Dynamics Discovery process is used instead of expensive and potentially disruptive iterations.
IT tends to flow in cycles, decentralized followed 4 years later by re-centralization. By then technology has sufficiently changed to restart the ‘who owns what’ cycle. Today, many IT organizations are seen as expensive speedbumps, incapable of empowering the Business on its Digital Journey. Part of this is due to the ITIL and COBIT methodologies both of which are very procedural and predominately allowed outsourcers and governments to standardize their SLAs and operations across multiple clients and sites. Internally, its heavy guideline approach slows project initiation/funding, focusing on documentation standards more than results, even in Agile shops. IT’s culture aligned with these methodologies, becoming slow but well documented. The user experience was frozen between releases, even when customers started to compare IT’s UI to that of their smartphone apps, including the frequent updates. IT’s UI orientation took on the vendor’s vision, not the customer’s, and the customer’s vision is what drives Digital Transformation, particularly with a multi-generational workforce. IT wants to own this new paradigm, but the Business is rejecting that notion, often forcing IT to become the operator of legacy systems and networks, a necessary but not strategic partner, and a source of grab-back money to fund Transformation.
The Business, responding to rapid market changes and sophisticated customer expectations, adapted to this new reality via the growing trend of Business funded Shadow IT, most of which is AI-powered Analytics, and Intelligent Automation with the platforms and data hosted in a public cloud. This approach, however expedient becomes an issue when, post-implementation, the Business returns operations of these cloud-based systems to IT, commonly called a Data Boomerang, some of which may not be able to support increasing transaction loads beyond the initial pilot projects. It also manifests in Digital Transformation strategized, budgeted and executed by the Business, and not IT.
Forty-five minutes later, it was time to agree on how IT and the Business join in lock step into the Future of Work. The consensus was IT should maintain control of databases and operations, as well as security and SLA monitoring. To promote some degree of standardization to avoid vendor bloat, IT can promote a list of vetted and approved Intelligent Automation vendors, going further by creating reusable iA modules (“Lego blocks”) as well as APIs into legacy applications. From a transformative point of view, there isn’t much new in this approach. We propose a different tack.
Transforming IT from service providing utility to front-line customer and employee engagement enabler has to reflect the ways a multi-generational workforce approaches systems and their unique expectations of the user experience (also known as a Customer Journey). The vendors, analysts, and implementers talked about the “customer experience” ad nauseam, but when pressed, had no clear definition of what that should look like, making the job harder for IT. The vendors’ and implementers responses were typical — we’re agile, we iterate, forgetting to address who will pay for this or if it is even appropriate for each use.
Even the Business representatives could not definitively describe customer experience expectations. However, they did stress how important it is, and rightly so. Our solution is to establish a Technology User Insight Center within IT, gaining deep-mind user insights. This learning, going way beyond A/B testing will provide a day-in-the-life of users, achieving context necessary for optimized decisions and process flows, AI augmentation, and meaningful analysis of the petabytes of IoT data expected to flood companies. Use of tools capturing eye movements, emotional attachment and feature use at a granular level uncover ‘move the needle’ insights. Linking this data to AI-based tools designed to select processes best fit to be automated, the Technology User Insight Center can be the go-to source of application-level user experience requirements and the rank order of what processes will supply the largest ROI, all based on data. IT will replace the vendors in who is guiding the Business’ adoption of Digital.
In sum, IT has to rapidly morph to its next stage — from processor of transactions and infrastructure operator to user-insights and customer digital technology advocate, partnering with the Business as their strategic Digital Transformation Business Enabler. Some CIOs and their teams can make this switch; some may need a politically neutral outside trusted advisor to set up this new IT function, establish the methodology and tools with the Business’ cooperation, and lead the initial data analyses. CIOs who do not embrace this will soon find they are losing more and more Shadow IT funding battles and invited to fewer and fewer Digital Transformation meetings.