"Software eats politics" S-curve (purple) crosses "politics adopts software" S-curve (green)
1/ The New York Times ran an article yesterday about how the Trump campaign adopted Silicon Valley tactics to win. This is roughly right. Trump was a disruptive political startup.
2/ Not Karl Rove in 2000, not Howard Dean on 2004, not Obama's famed mobile outreach campaigns in 2008/12. The "software eats politics" moment was Trump's victory in 2016.
3/ Yes, like many of you, I don't like the way this played out. But nobody said my idea of the "nice" people had to be the ones who would pull it off, or do so with my political values driving them.
4/ The story of digital technology use in US Presidential elections is an object lesson for anyone involved in enterprise software development or sales on the vendor side, or buying/deployment on the customer side.
5/ Every election since Bill Clinton's 1996 second-term victory has seen breathless analysis about how some candidate or campaign staffer used "digital" means to win.
6/ In Adam Curtis' documentary, Century of Self, he argues that Bill Clinton's 1996 campaign was the first use of analytics-driven campaigning as some sort of dark superpower.
7/ In 2000, Karl Rove acquired a god-like reputation for his supposed masterful deployment of data technologies in service of George W. Bush's slim victory.
8/ In 2004, Howard Dean's campaign attracted breathless commentary on his use of grassroots campaigning and fundraising models. He didn't win, but defined the tech story of the election.
9/ In 2008 and 2012, people talked about Obama's effective integration of Howard Dean's models, mobile texting, Karl-Rovian analytics, and social media in his victories.
10/ In 2012, Romney's losing campaign came in for strong criticism for its poor technology adoption as evidenced by the failure of the Orca app the campaign used.
11/ But throughout this period -- 1996 to 2016 -- while software was eating the world, it was largely ignoring politics. The supposed technology story in politics was largely a theatrical sideshow.
12/ Though technology played an increasing role, it was the role of a commodity. The successive campaigns simply saw candidates buying better potatoes. Faster horses, digitally accelerated.
13/ In each of the elections, arguably, software did not provide the decisive strategic edge. This path is illustrated in the green S-curve above. Candidates won or lost for other reasons.
14/ The title of Nick Carr's famous 2003 article, IT doesn't matter argued the software-as-potatoes point clearly. Between 1996 and 2016, in politics, IT didn't matter.
15/ For 20 years, politics merely saw the theater of "technology adoption" where people were pretending they were deploying technology to strategic, transformative effect rather than as better potatoes.
16/ During the same period though, the forces of software actually eating politics were slowly coming together on a different S-curve, the purple one in the diagram above.
17/ The early events on this S-curve do not even look technological. Rush Limbaugh's rise to national fame on talk radio, as a thorn in Bill Clinton's side, used an old technology -- AM radio.
18/ But things got slowly more technology-based. Twitter, Facebook, Breitbart, and Wikileaks all emerged in a brief period around 2007, alongside the iPhone.
19/ The three main political subplots on the new S-curve -- the Tea Party, #Occupy, and the Birther conspiracy, all began a couple of years later as weird "political startups" on this new "stack" in the same period.
20/ The rest of course, is history. Between 2011 and 2016, an actual software-eats-politics force began gathering serious momentum on the margins. But the theater of adoption on the main S-curve still looked real.
21/ We don't yet know the full details of how Cambridge Analytica shaped the election, but its unclear role in Brexit and the Trump campaigns reveal it belongs on the lower S-curve.
22/ Despite superficial similarities in the technologies, it seems Cambridge Analytica was a very different beast from the data-driven analytics operations on the old green S-curve.
23/ With 20-20 hindsight, it's obvious to all of us now that 2016 was the moment when software actually ate politics. Because, by establishment criteria, a not-even-wrong candidate won.
24/ The elements came together -- demagoguery, marginal outsiders, Twitter, Facebook, 4chan, failed polling models, Russian hacking, leaked audio/video, Hillary's emails, trolls, "Fake news" -- in a story that feels viscerally real.
25/ It is noteworthy that it wasn't all bleeding edge. As is often the case in disruption, many old elements find renewed relevance. From AM radio to Andrew Jackson's strategies from the 1830s.
26/ The old commentary on 1996-2012 "digital campaigns" now feels like a bad "enterprise software adoption" webinar, with Howard Dean and Karl Rove as stock photos on ugly PDF brochures.
27/ Compared to what happened in 2016, 1996-2016 feels like "strategic digital transformation" lipstick on a potato-fed pig. The idea that IT mattered 1996-2016 seems almost precious now.
28/ What will happen now to governance itself, since the campaign part is already eaten? The story seems to be repeating itself. We're seeing real, as opposed to theatrical, e-governance.
29/ As with political campaigns, we've seen 20 years of bullshit "adoption theater" talk on "e-governance" that was really "digital governance potatoes."
30/ Though some of the sustaining innovations on the e-governance S-curve have been massive and huge (NSA surveillance, healthcare.gov, things like India's Aadhar card), they have still been potatoes.
31/ In other words, they are not about strategy or about "digital transformation." They are about doing the same old governance things, the same ways, except with "paperware" in software form.
32/ There have been the same sorts of poster-child "e-governance" stories: wiki constitution efforts in Iceland, e-citizenship in Estonia. Interesting and worth learning from, but fundamentally, theater.
33/ Those are cases of governance adopting potato software rather than software eating governance. We are only just beginning to see what the latter might end up looking like.
34/ So what lessons can you draw from this story? They matter whether or not you're involved in enterprise software. The big lesson is this: don't mistake buying potatoes for software eating you or you doing the eating.
35/ When software eats something, what comes out the other end is deeply, fundamentally transformed. A "not even wrong" answer like Trump. And the process isn't some thoughtful, deliberate "strategic adoption."
36/ Sure, read those Gartner and Forrester reports. Ponder the magic quadrants and hype cycles. Go to the conferences on the latest technologies (or fads). The current one seems to be AI.
37/ But this is all just potato-buying as an excuse for strategy theater. In the worst case, you severely damage yourself by wasting money and botching execution by breaking working things and substituting dysfunctional theater props.
38/ In the average case, you'll have some fun going to the theater and partying, and maybe learn a few things that may come in handy when the software-eats-you part actually gets going.
39/ But in the best case, you'll see the adoption theater for what it is, and switch to the actual "software eating my widgets" S-curve at the right time, so you can participate on the eating side.
40/ The biggest sign that you're switching from adoption theater on the old S-curve to disruption action on the new one is not technological, financial or managerial. It is moral/ideological.
41/ Inevitably, in switching to the disrupting S-curve your morality will be challenged. Sacred and profane will be flipped around, and you will have to rediscover your sense of sacred.
42/ Throughout the late 90s for instance, "respectable" Republican politicians shied away from the crude demagoguery of talk radio. The values dissonance was too strong.
43/ Even after the Tea Party started seriously reshaping the party from within and outside, and Ted Cruz rode it to power, the values of the disruptive purple S-curve were too profane for the old S-curve to touch.
44/ The story was similar on the Left: the insurgent Bernie campaign has roots going back to the Seattle anti-globalization/WTO protests of 1999. #Occupy was an arms-length thing for green-curve Democrats.
45/ But here's the good news. Once the S-curves have intersected, the game changes. The theater ends. People know what real digital transformation, as opposed to adoption theater, looks like. Shit gets real.
46/ What follows is often something like a counter-reformation, similar to how the Catholic church responded after being disrupted by Martin Luther and the Reformation.
47/ Potato-buying theater suddenly turns into an existential crisis/conflict within existing organizations and institutions. They are forced to actually change at the level of values.
48/ We see this in enterprise software all the time. Currently, the bullshit theater of "private clouds" that went on for a decade has finally seen the writing on the wall: it's a public cloud game now.
49/ A counter-reformation in the "private cloud" industry, now that their bullshit has almost collapsed, is likely. They'll either find a new, less theatrical/bullshitty value proposition, or die.
50/ For a blow-by-blow on this particular huge "adoption theater" story, follow my friend Simon Wardley on Twitter. He's something of a polemic/evangelist on the subject.
51/ So why do people indulge in the theater instead of doing the real thing? It's a classic disruption reason: the incumbents don't have any reason to take risks while they have their core markets locked up.
52/ During this period, technology has no strategic value. At best it has marketing value with customers and morale-building value with employees. Neither is strategic or decisive.
53/ You can show-off "innovation" poster children to customers (campaign donors in this case study). "Look at all our cool analytics charts and social media engagement metrics."
54/ For employees (campaign staff), there is an opportunity for live-action roleplaying (LARPing) disruption instead of actually taking the existential risks of disrupting. LARPing disruption is fun.
55/ Don't get me wrong: lots of money can get spent (of dubious value, hence the sub-cottage industry of bullshit "ROI" estimates) and engineers can work hard on hard technology problems.
56/ But without the element of ideological risk -- dropping certain sacred values, adopting previously profane values -- and risking existing value for uncertain lower returns, you're just pretending.
57/ These thoughts came together this week for me due to two provocations: a journalist asked me some questions about what it means for a CEO to be "tech-savvy" and somebody asked me for help with an enterprise sales problem.
58/ I ended up giving the journalist the CEO-tech-savviness version of this "adoption is bullshit" answer, and was forced to tell the second person I couldn't help with their sales problem.
59/ This "adoption is bullshit" and potatoes-prey-predator framework unfortunately means that most things that go on in the name of "strategic thinking about software" are just not worth doing.
60/ If you're a C-level leader, the only question that matters is: are you willing to take the ideological risks? The sign is that a seemingly low-value marginal market comes seriously into play.
61/ Note that Trump's voters included many who traditionally have low turnout. If your "digital transformation" isn't shifting the center of gravity of the business to an underserved marginal market, you're faking it.
62/ It doesn't actually matter that in this case, the leverage of new technology helped politically activate "non-elites" against "elites." The specific anatomy of core vs margin doesn't matter.
63/ What matters is that you recognize the core and margins for what they are and frame "digital transformation" in terms or a shift from the former to the latter.
64/ For an engineer, the only question that matters is: do you want to LARP disruption or actually disrupt? The test is whether what you're involved in has something like stock options that could pay off big.
65/ And finally, for a sales person, the test is: does it feel like you are selling potatoes against a strong headwind with bs "ROI" estimates, where customers are happy with their current potatoes?
66/ Or is a weird new kind of customer, who almost doesn't seem like they're worth your time, coming to you, with needs you're not sure you want to fulfill because the money isn't good enough?
66/ This applies incidentally, whether you're a sales person on the vendor side selling the "transformation" products, or on the buyer side, selling "transformed" things to your own customers.
67/ If your job is selling cars for instance, and your CIO is proclaiming "digital transformation" and buying all the latest goodies -- Big Data tools, AI -- but you're selling the same cars to the same customers, you're not "digitally transforming."
68/ Whatever your role, and on whatever side of the software buying/selling game, and whatever your organization sells, be it political candidates, cars, or databases, this is the reality of "adoption."
69/ In summary, whatever political lessons you draw from the election, make sure you don't draw the wrong lessons about technology. Don't mistake potato buying for eating or being eaten. Don't mistake LARPing disruption for the real thing.
70/ It has been hard for me to write this newsletter because as you guys know, I'm definitely on the disrupted "establishment" side here for non-technology reasons, as I wrote in my last ribbonfarm post.
71/ But that makes this all the more an important case to learn from. Don't ignore a lesson simply because you were on the losing side of it. You can still deploy lessons learned in the counter-reformation.
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