The Three Ways Operations Execs Can Cut Through the Hype in the Automation Software Market

Featured article by Adam Devine, Vice President of Marketing, WorkFusion

Marketing hype has always made selecting enterprise software challenging, but business process automation has been a particularly challenging market for end users to navigate for three reasons. First, the capabilities and benefits of the early wave of process automation products have been over-touted. Second, there are no two automation products that are exactly alike, and thus defining and comparing them is difficult. Third, illuminating case studies are scarce because most enterprise operations have only just begun to adopt automation in a significant way. Despite the challenges, the world’s biggest and smartest enterprise operations are cutting through the noise and rapidly adopting. Read on for a more in-depth diagnosis of the obstacles and how buyers are overcoming them.

1. Grand marketing of narrow solutions and false AI promises

Good product marketing is made of factual product capabilities plus insights learned from customers coated in a mercifully thin layer of varnish to catch the eye of prospective customers. Bad marketing is just the varnish, and that’s what’s covered much of the automation market. “Robotic Process Automation” (RPA) vendors have oversold the capabilities of their products with shiny, bold marketing, and some even market their products as artificial intelligence (AI) solutions when their technology provides strictly rules-based robotics.

After about a decade of seeking its place in the enterprise software stack, rules-based automation software has achieved mainstream awareness as RPA. It is an excellent solution for automating routine, binary tasks that human workers perform on legacy applications—like entering passwords into and operating the user interfaces of SAP and Oracle—and moving structured data from one system to another. Given the waning benefits of labor arbitrage and mounting pressure to reduce costs, the BFSI industry in particular blazed a trail into RPA, focusing on common horizontal business processes like eInvoice processing, Procure to Pay (P2P), Record to Report (R2R) and vertical challenges like KYC, AML, settlements and claims processing. In other words, the labor-intensive middle and back-office work that has for decades been mostly offshored.

One or two years after kicking off POCs and, in some cases, full deployments, customers look at their results and ask, “Where is the 90 percent cost reduction I was promised? What about the suffocating volume of manual, unstructured data work in the rest of the business process? How do I affordably handle the exceptions in the process that need human action? How do I automate the rest of the process?” This is a bit of a paraphrase, but it’s a fair synthesis of how end users react after using RPA-only products.

The problem with RPA as a category is not the technology. It’s how vendors have marketed their RPA products.

RPA does indeed automate the operation of desktop application user interfaces, and one “bot” can deliver about 1.5x the productivity of one worker provided the work only involves structured data. It’s “hand” work  –  tasks that a human can perform without thinking, performed in accordance with a strict and rigid set of rules. RPA does not process unstructured data (PDFs, docs, email messages, news feeds, web content, etc.), nor does it have human-in-the-loop exceptions processing for when the rules governing a “bot” change. Additionally, some RPA solutions are not deployed at a server level, which, for customers who value security, means occupying a desktop and exposing passwords and other sensitive data to human workers.

RPA is a powerful feature that delivers great results when applied to structured, rules-based tasks, but it belongs as a feature in a complete suite of automation capabilities, and it must be paired with machine learning to automate a complex process from end-to-end.

2. Many vendors competing for dominance

The best analysts and advisors have examined the product offerings of every vendor and come away with the conclusion that the market looks like a fruit stand with only one of each fruit on display. These differences are architectural, functional, horizontal and vertical. The various players in the market started with different theses, built different products based on their origins, and marketed to different sizes and types of businesses. Automation is halfway through the three classic software market phases: develop, compete and dominate. Let’s looks at these phases through the lens of a well understood market: social networking.

Friendster began as a platform for creating digital ties between people who already knew one another. MySpace started with this functionality, along with increased discoverability between strangers and, interestingly, music. Facebook started as a way for students at elite universities to poke one another. We all know how this played out. Friendster and MySpace didn’t aggressively evolve their products out of initial development during the competition phase, and Facebook became the dominant player by developing a wider range of user-friendly capability for a wider range of users.

Automation has just now entered the competition phase. Some of the early players have already cashed out, other players are marketing capabilities they do not have, and still others are only just now coming to market. Buyers find it hard to compare them because there isn’t a standard set of features to shop for, and some buyers don’t yet know what they need. After all, only a few years ago, offshoring was state of the art and business process automation was an expensive, uncertain scripting endeavor imposed upon data science and IT teams.

But one thing is true about all of these offerings: before long, there will be only one scalable, widely deployed and battle-proven model, and there will be only one (maybe two) vendors who competed well and took the dominant position.

3. A dearth of evidence

Yelp reviews make it easy for diners to choose restaurants. Product reviews makes it easy for shoppers on Amazon.com to buy things. Clear, relatable, quantitative case studies from seasoned customers make it easy for enterprise software buyers to select a technology. These case studies are only just now surfacing, and that’s made it more challenging for buyers to make decisions.

Because business process automation is new and there’s still confusion between the features and benefits of robotics, cognitive automation and AI, there aren’t many real, believable case studies to help inform new buyers. Most buyers are only a year or two into their business process automation journey, few of them will continue to use the platforms they started with, and many companies have only just begun their due diligence. Making meaningful bets is difficult without hard data.

Three steps to cutting through the confusion

The first step is centralizing control of the buying process in centers of excellence (COEs). The fastest and most efficient purchase and deployment efforts have leveraged this model, which brings together operational requirements from user groups across different divisions, product knowledge and decision-making liberties. These COEs typically begin with reports and briefings on smart automation and digital operations from Everest, Gartner, Forrester, HfS and other leading analyst firms that are shedding light on the market. The COEs create a long list that becomes a short list that become a pragmatic, informed product selection.

The second step is selecting business processes for a meaningful proof of concept (POC) with one or more vendors (and a good vendor will be able to help you select the right processes). These processes should represent the way the business operates. If you’re a global banking or insurance operation, thousands of people ingest and process a combination of both structured and unstructured data and leverage and feed dozens of systems. You have some legacy technology that you do not wish to disrupt, and you have some point tools that you wish to rationalize out. You have both internal and external demands to accelerate transaction times and reduce manual work while improving accuracy. You are under the gun to cut costs immediately, and any solution you consider must pay for itself in under a year. So, a good set of processes for a POC will take these factors and challenges into account.

The third step is an actual POC. The visionary and dynamic CIO of one of the biggest European banks once declared at a conference that if a technology could not demonstrate results in one quarter, it had no place in the operation. This is an excellent rule for automation.

POCs should also have executive sponsorship. POCs are often affordable enough for divisions within companies to execute without executive support, but full deployments across an enterprise are not. There’s no point to doing a POC if your organization is not committed to modernization or transformation at the executive level. Get buy-in early. The POC is not only a chance to see how a product performs, but it’s a chance to see how a product would deploy. Does the vendor deploy directly? Through partners? As an on-premises solution? Cloud? Desktop or server, or both? POCs are your opportunity to not just kick the tires but to drive the car, and you should drive the car hard and fast in many conditions before you buy it.

It takes a suite, not a single tool

Enterprise operations professionals have the hardest, most important job in business right now. The markets might be up, but revenues aren’t. It’s up to ops to return the glory to margins, and technology is how they will do it. Automation software buyers deserve transparency from vendors about what their products can and cannot do so that ops leaders can make fast, informed decisions that deliver value to the business. RPA is a great feature, but it isn’t enough on its own. To both transform and run their businesses, ops teams need a suite of capabilities that include business process management (BPM), RPA and AI-powered cognitive automation, and they need these capabilities to be usable by business people. Most of all, they need marketing hype to evolve into practical communication about capabilities.

About the author:

Adam leads market development, product and brand marketing and strategic partnerships at WorkFusion. He began his career in management consulting in the Financial Institutions Group at BearingPoint and has spent the past 14 years in tech product marketing and advertising. He was most recently director of strategy at 360i. Adam holds a bachelor degree from the University of Vermont.