{"id":506,"date":"2022-03-18T09:25:36","date_gmt":"2022-03-18T13:25:36","guid":{"rendered":"https:\/\/freedville.com\/blog\/?p=506"},"modified":"2022-03-18T09:26:46","modified_gmt":"2022-03-18T13:26:46","slug":"book-review-the-art-of-automation","status":"publish","type":"post","link":"https:\/\/freedville.com\/blog\/2022\/03\/18\/book-review-the-art-of-automation\/","title":{"rendered":"Book Review: The Art of Automation"},"content":{"rendered":"\n

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Besides having great insights, Cuomo\u2019s book has some really fun art!<\/figcaption><\/figure>\n\n\n\n

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I don\u2019t typically think of software and art in the same sentence.  After reading Jerry Cuomo\u2019s Art of Automation book<\/a>, I\u2019m going to think differently!  Jerry Cuomo leads an all-star cast of contributors (\u201cGang of 7\u201d) with diverse specialties and backgrounds.  Nearly every chapter has a quotable insight.<\/p>\n\n\n\n

The introductory framing is wonderful.  Cuomo\u2019s central thesis is that businesses have become computers that can be programmed.  This statement alone was worth the book purchase.  Further, Cuomo states (and his guests reiterate) \u201cyou can\u2019t automate an enterprise unless that enterprise is \u2018programmable\u2019 through APIs.\u201d  This \u201cfractal\u201d view of an enterprise means that the same principles that apply to systems design, and even to programming, can also apply at even higher levels.<\/p>\n\n\n\n

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Enterprises, computing sytems, APIs, and code all exhibit fractal properties, as does this leaf! Photo by Annie Spratt<\/a> on Unsplash<\/a><\/figcaption><\/figure>\n\n\n\n

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Even better \u2013 automation is not all or nothing.  And if you don\u2019t have APIs, there\u2019s still hope for you.  Many people think of automation as \u201ctask elimination\u201d, but Cuomo et al argue for \u201ctask augmentation\u201d.  In many scenarios, we want a human involved in a task, but want to automate tedious tasks so the human can achieve better results.  Claus Jensen notes that the question is not whether to use humans or<\/em> AI automation, but to combine them, since they generally perform better as a team than as individuals.  Cuomo and team repeatedly advocate for working in \u201cbite-size chunks\u201d, incrementally automating and delivering increased value.<\/p>\n\n\n\n

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Take many small steps to reach your goal! Photo by Jan Gottweiss<\/a> on Unsplash<\/a><\/figcaption><\/figure>\n\n\n\n

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The first automation deep-dive is chapter 2\u2019s focus on Robotic Process Automation (RPA).  RPA has a slightly cooler name than what it does – Allen Chan suggests we should call it Robotic Task Automation \u2013 since its unlikely that you can automate an entire process.  There are lots of business processes that include repetitive copy-paste-manipulate.  It may not be cost-effective to build fully API-based applications for these, but RPA can help lighten the load.  If you find yourself repeatedly copying from one application and pasting into another \u2013 RPA might be for you.<\/p>\n\n\n\n

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If you have this many people doing the same repetitive task \u2013 you might need RPA! Photo by Alex Kotliarskyi<\/a> on Unsplash<\/a><\/figcaption><\/figure>\n\n\n\n

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Haley Davis\u2019s chapter 3 suggests another birds-eye view of an enterprise, using process mining to perform a systemic review of an enterprise.  (\u201cWhy are things going to hell in a handbasket around here?\u201d)  Process mining reminded me a lot of running a profiler on software code to figure out where bottlenecks are.<\/p>\n\n\n\n

In chapter 10, Carol Poulsen suggests that RPA is a band-aid that you\u2019ll need to eventually refactor.  I agree with the sentiment, but also appreciate the book\u2019s perspective that RPA is often a valuable incremental improvement on the status quo.  The tension in these chapters shows the book\u2019s greatest strength: diverse perspectives, and a refusal to work in false all-or-nothing dichotomies.  The book even finds the middle ground on this topic: RPA and process mining help you find the places where you\u2019ll eventually want to build APIs.<\/p>\n\n\n\n

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Compromise! Sometimes you\u2019ll automate by RPA, sometimes by APIs! Photo by Cytonn Photography<\/a> on Unsplash<\/a><\/figcaption><\/figure>\n\n\n\n

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Chapter 4 has another brilliant insight, this time by Salman Sheikh, that a digital employee is \u201can employee first and digital second\u201d.  Sheikh explains that you need to focus on the digital employee\u2019s role \u2013 the same way you would give your human employees a role.  A digital employee often makes their human employee counterparts more productive.  A wonderful use case for digital employees is bridging multiple applications, so a human can stay in one application to perform their work instead of jumping between applications.<\/p>\n\n\n\n

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Ok, there\u2019s another reason why Chapter 4 was one of my favorites! I know that excellent chatbot book!<\/figcaption><\/figure>\n\n\n\n

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Chapters 5 and 6 take a tour through automated document processing (ADP) and automated application performance monitoring (APM).  Cuomo ties these together with a common thread: you can\u2019t automate or fix that which you cannot see.  ADP and APM support that mantra in different ways.<\/p>\n\n\n\n

Perhaps my favorite chapter was the 7th<\/sup>, written by Rama Akkiraju, on AIOps.  As a technologist, I wanted to inject this chapter directly into my veins!  AIOps combines the best parts of AI and Ops to keep your systems running smoothly.  In my career I\u2019ve encountered lots of different systems: source control, ticketing systems, incident databases, operational logs, runbooks, and more.  AIOps brings all these information sources together in exciting ways.  Of course, you could use these solutions to reactively solve problems.  But better yet, you can use them predict problems.  Akkiraju describes a scenario where historical data is used to assess a change request.  She stops just short of invoking a Clippy who asks you \u201cSay, it looks like you\u2019re about to do a risky deployment!\u201d<\/p>\n\n\n\n

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AIOps helps you assess risk before<\/em> you deploy new code! Photo by Ray Harrington<\/a> on Unsplash<\/a><\/figcaption><\/figure>\n\n\n\n

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Rob Nicholson delivers the 8th<\/sup> chapter, on APIs.  Fully automating without API integration is difficult.  API integration enables automation by allowing the enterprise to find and act on data.  A cool feature coming out of IBM is App Connect\u2019s \u201cSmart Mapper\u201d which uses ML\/NLP and rules to suggest likely mappings between pairs of APIs.  This would have saved me a lot of time as a young programmer!<\/p>\n\n\n\n

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IBM App Connect will help you wire together your disparate APIs! Photo by Steve Harvey<\/a> on Unsplash<\/a><\/figcaption><\/figure>\n\n\n\n

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Chapters 9 through 15 are transcriptions from Cuomo\u2019s Art of Automation podcast<\/a> where he interviews titans of industry.  These were delightful tours through a variety of industries.  I noted several insightful theses:<\/p>\n\n\n\n