The process automation, process mining, and integration categories are blurring. Vendors, by making indistinguishable claims about digital transformation and process automation, suggest similar outcomes. However, what differs are their fundamental approaches, which I call the \u201cautomation DNA\u201d that dictates customer outcomes. In many cases, the outcomes are limited to efficiency. But the market demands something more, in the form of end-to-end automation capabilities that push beyond efficiency into other outcomes such as innovation, growth, and true business resiliency.\n\nDNA matters\n\nEvery few years, a viral story breaks about how identical twins, separated at birth, discovered one another as adults. These discoveries highlight the power of genetics, which dictate similar outcomes across the siblings\u2019 lives. The documentary film Three Identical Strangers tells the incredible story of triplets unethically separated at birth in the name of science. The tragic tale is also fascinating; Despite three completely different upbringings, patterns of behavior and life outcomes repeated across their lives.\n\nWhether biological or technological, the power of DNA is unavoidable. Today, society is reckoning with how \u201ctechnological genetics\u201d dictate outcomes, such as how algorithms impact democracy. I have been researching and thinking more deeply about how platform architectures can lead to intended or unintended consequences.\n\nIt is time to look closely at the technological genetics of automation platforms. I\u2019ve spent time in leadership roles at the three largest robotic process automation (RPA) vendors and now advise several organizations in the broader automation category. As the process automation, process mining, and integration categories have evolved, the outcomes that vendors promise to have are sounding the same. Despite this, the DNA of automation platforms still leads to different outcomes for customers.\n\nProcess automation began with two promises: uniting disparate systems together and unleashing the massive trove of data that sits within your processes and back-office functions. In its current teenage years of growth, unfortunately, both these promises are unfulfilled. \n\nWhile task automation tapes systems together, the underlying bot architecture makes it superiorly difficult to address bot fragility, scalability, and most importantly integrating various automation technologies, i.e. process mining, intelligent document processing, AI\/ML, bot operational analytics, business value analytics and process lifecycle analytics together.\n\nEqually so, the massive trove of business-specific data is still a distant reality as technology vendors leapfrog to the next best phrase, featuring hyper-automation and an extremely efficient and very flexible autonomous enterprise. \n\nDigital transformation cannot be achieved through purely tech-enabled, service-led approaches, with the promise to build autonomous enterprises with low code, flexible applications, etc. In the meantime, many customers are simply looking for automation to fulfill the core, initial promises made.\u00a0\n\nBetter, faster, cheaper\n\nI recently read a post that confidently listed the author\u2019s opinion of what defines automation success: it must be \u201cbetter, faster, or cheaper\u201d in order to be considered of any value to the business. This is not surprising. \u201cBetter, faster, cheaper\u201d perfectly captures the dominant narrative about automation: pure efficiency. The assumption is that companies should create economic value with automation by improving the same tasks that they are already doing.\n\nThe efficiency narrative is driven by platform DNA (think enterprise architecture). Its popularity coincides with the rise of RPA and process mining. UiPath, Automation Anywhere, Celonis, and others spend a lot of money (approximately $4 billion) to convince business leaders that there is a gold mine hidden in their processes, and if they only make them better, faster, and cheaper, they will succeed. The approach has value, evidenced by the size of the RPA and process mining markets.\n\nEfficiency is great, but is it enough to help businesses win over the next decade? If history is a guide, the answer is no. In technology, innovation beats efficiency. To that end, business leaders cannot allow the better, faster, cheaper mindset to cloud their view of automation\u2019s potential. In fact, automation offers incredible chances for innovation and growth, pushing organizations into greenfield areas of opportunity.\n\nA deeper dive into automation genetics\n\nLet\u2019s take a look at a few different process automation solutions in the market today and talk about how their solutions have evolved vs. how their DNA will impact their outcomes:\n\nRobotic Process Automation: Although the last two years have seen multiple M&A rounds with RPA vendors buying up API connectors such as UiPath acquiring Cloud Elements, and Blue Prism nearly merging with Tibco, the underlying architecture of RPA solutions remains bot-based. In other words, the platforms are architected for bots to mimic a series of steps that humans take. RPA platforms, no matter what is bolted on by M&A, are still fundamentally designed to offer better, faster, cheaper because the easiest way to design a process is to copy what humans in your company are already doing, regardless of if the information is accessed by screen scraping or API.\n\nProcess Mining: Aptly named process mining vendors map out what happens in companies and by design take a historical point of view: examine what you are already doing and make it better, faster, and cheaper.\n\nIn both of these approaches, use cases that are completely greenfield and innovative are rare. A quick glance at the Gartner list of RPA use cases or process mining use case list makes it clear that each technology is simply rehashing work that people have been doing in companies for decades.\n\nAll you need is love autonomy\n\nThere is no doubt that automation powers the autonomous enterprise. But that\u2019s not enough, if one\u2019s definition of automation is RPA. AI-based analytics with predictable and actionable insights, machine learning and behavioral analytics, perdurable governance and possibly more are needed for an effective, truly autonomous enterprise. We are not there yet.\n\nThis future statement, while achievable - "Ultimately you will have processes that compose themselves on the fly and then decompose themselves\u201d, requires a different level of thinking, architecture, and sound governance. Should we march towards it with unbridled passion, without learning the lessons of how a sub-segment of automation has grown up, we might leave behind a wake of failed customer expectations.\n\nEstablished companies go through five stages of enterprise architecture maturity \u2014 moving from business silos to standardized technology to optimized core to business modularity and then a digital ecosystem.\n\nSearching for innovation DNA\n\nAutomation approaches that are built on a foundation of integration appear nimblest in what they can accomplish and most valuable in the long term. You can certainly still accomplish better, faster, cheaper, but you can also do more.\n\nThe DNA of the integration approach (you could also call this the API-first approach, as some vendors have) is not a replication of what has been done before, but the ability to weave disparate systems together to achieve new things entirely. While other categories make existing processes better, faster, cheaper, integration platforms beckon companies to don their chef hat and mix up a collection of platforms to see what new recipe they can achieve.\n\nSome have expressed that in terms of \u201cIf data is the new oil, APIs are the new pipelines\u201d or still others in terms like Deloitte\u2019s: \u201cAPIs are the cornerstone of what is widely seen as the next iteration of business development and revenue generation.\u201d It is no surprise, then, that players in the RPA and process mining categories have been buying up API vendors. Gartner notes that by 2023, \u201calmost all major RPA vendors will offer a broader process automation and integration platform combining screen scraping with APIs.\u201d\n\nDespite this trend, some are correctly observing that the DNA of built-in platforms offer towering advantages over bolt-on. \u201cMergers and acquisitions often confirm a market need but don't necessarily solve the customer's pain point,\u201d observes Workato CEO Vijay Tella. \n\nIn Who Moved My Bots I led a conversation with Microsoft and Hanover Insurance where Prashant Hinge, VP of Automation at Hanover Insurance says, when he makes vendor decisions that need to last for 3-5 years, he is going to choose built-in vs. bolt-on every time.\n\nToday, the market demands automation for end-to-end processes. Last year Gartner noted that they did not recommend RPA as a long-term strategic business strategy. Others have labeled the tech a \u201cquick and dirty\u201d solution. Truth is, RPA and process mining bring efficiencies, but fall short on true business resiliency.\n\nBusiness resiliency \u2013 and success in the next 10 years \u2013 will come from the same place it always has: the effective and efficient capture of greenfield opportunities through innovation.\n\nAutomation is no exception to this rule. Enterprise architecture (DNA) matters.