Confronted with too much tech FUD and FOMO?
According to research on loss aversion, FUD (fear, uncertainty, and doubt) is more powerful than FOMO (the fear of missing out), but technology executives and their organizations liberally use both to hype the goods and services they’re promoting.
Trying to work your way through everyone’s claims and counterclaims? Here’s what to do.
Read all the papers, reports, analyses, proposals, white papers, and books you want, and listen to all the relevant TED talks, podcasts, and lectures you can find, but you very well could be fighting a losing battle. The fundamental mission of the technology-industry-complex (TIC) is to get you to part with more money more quickly than you should or otherwise would. The “hype machine” is in full-frontal assault mode. All TICs – players in the technology-industry-complex – are in on it.
- Business schools
- Academic researchers
- The trade, business, and general press
To achieve their objective, TICs are willing to shade the truth, distort surveys and data, selectively filter experiences, and put the fear of imminent destruction and the fear of missing out on desirable outcomes squarely into the consciousness of everyone they can reach.
Caveat emptor – let the buyer beware – isn’t enough. Relying on published expert opinions and carefully curated references isn’t either.
Carefully question the authors and speakers. Respect matters. Empathy is important. Help them discover the truths they may not even admit to themselves and share with you their honest feelings about the questions and issues at hand. You will not succeed with this technique all the time. That means you’ll need to learn from the process each time that you use it. As you aggregate your experiences, the results should be compelling.
Behind the scenes
This line of research explores some of the dimensions of the TICs problem and how to avoid being misguided by TICs’ deceptions while still exploiting the most appropriate opportunities underneath the layers of hype.
This summer, 2021, two significant articles appeared in the business sections of the Wall Street Journal (Christopher Mim’s Why Artificial Intelligence Isn’t Intelligent) and the New York Times (Steve Lohr’s What Ever Happened to IBM’s Watson?) If you haven’t read them, I urge you to do it right now.
These two articles raise questions about “AI,” one of the latest revolutionary, disruptive technology bandwagons (techno-manias) that TICs have generally told buyers they have to buy into right now to avoid missing out and being buried by more aggressive competitors.
More than AI
Over the last 20 years, other bandwagon marketing programs that appeared include big data, enterprise 2.0, network computing, algorithms, cloud computing, digitalization, and service-oriented architecture. (Please do send me your favorites to add to this list.)
TICs invent new bandwagons every three or so years. But my analysis suggests these revolutions do not happen overnight; many transformations are rarely complete in less than 20 years. And what they look like when complete may be far different than what the bandwagon promoters urged you to adopt at the start of the 20 to 40-year technology diffusion cycle.
My reaction to both Lohr’s and Mim’s work was,
What took you so long?
Where were the reports in 2012 and following saying what you’re saying now?
This line of thinking led me to ask myself the more pointed question:
Why didn’t the analyst firms – big and small – challenge the orthodoxy around “Artificial Intelligence” and “Watson?”
There are many potential benefits to “AI” technologies, whatever we call them. The same is true for most other “bandwagon” efforts. But there are also many problems that the industry hype machines do not discuss. This error of omission has occurred in all the major technology bandwagons that TIC has introduced every one to three years.
This isn’t new
The creation and overpromotion of technology bandwagons predate the current era. There is evidence of techno-manias over the last 200 years.
The issues around E.M. Rogers’ Diffusion of Innovations research and the work of Schumpeter and Carlota Perez on the nature and duration of waves of change have been with me since I was exposed to Thomas Kuhn’s The Structure of Scientific Revolutions in graduate school in the early 1970s. I’ve had 50 years of observations and ruminations on the phenomena operating broadly – across business, society, the sciences, and technology.
In 1994, I wrote a note Is All This Hype Really Necessary? I concluded that, despite its deceptions, rampant technology hype was valuable because it improved the speed of adopting significant new technologies.
My analysis was defective. I was wrong. I committed an error of omission: I failed to account for the cost and risk of premature adoption and industry misalignment, which I will explore in subsequent notes.
Let’s look at a vital component of the technology-industry-complex, the industry analyst as intelligent mouthpiece.
Vendors generally look to analysts to serve as megaphones repeating the vendor’s claims. Vendors benefit from analysts rewording their claims in a way that reinforces the vendor’s strategy while showcasing analyst creativity or “thought leadership.” Creativity and thought leadership expand the audience that receives the vendor’s message.
This is usually not a quid pro quo, no pay-for-play. But almost all TIC analyst firms depend on vendors buying their services. Industry analysts operate under the unspoken threat of vendors withdrawing their support of analysts’ activities. Support includes
- Access to power, confidential plans, partners, and customers
- Recommendations to the vendor’s customers
- Participation in vendor events
- Indirectly, revenue for analyst services and rights to reprint selected analyst products
A careful minuet
The most prominent vendors are pretty savvy about dealing with the biggest analyst firms. And vica-versa.
- Analysts generally back away from threatening vendors. After all, who provides revenue to the analyst firms?
- Vendors are usually more subtle about backing off support of offending analyst firms. But they do it.
Crowdsourced analysis doesn’t address your needs
Some analysts have come to rely on crowdsourced ratings of vendors, products, and services to avoid friction with vendors. That lets them shift responsibility to the crowd (and cut the cost of analyst headcount.)
Crowdsourced ratings are problematic in many ways. They’re difficult to interpret; they tend to lack analytical depth and reflect non-representative respondent biases.
Get to know the analysts who wrote the opinions that are important to your specific decision process. Your goals should be to understand the analyst better and draw them out beyond what they wrote.
They need to see you at least as a source of support and even more, if possible, as a valuable source of information. Since you want them to open up, they should see this as a two-way street. They need to trust you and privately share some of their unpublished misgivings, just between the two of you.
Don’t settle for conclusions. Ask why, how did you come to that conclusion? Don’t accept cliches. It’s OK to be dumb when the analyst repeats a pearl of conventional wisdom. How do you know that? What alternatives did you reject? Ask them about how they worked so you can appreciate the job they do – and they can appreciate your questions.
Dig into their sources if they’ll let you. Keep excellent notes. Where legally permitted and with their permission, record the calls to give yourself a chance to listen instead of trying to write everything down.
Ask them to send you follow-up notes, summarizing findings and recommendations attuned to your specific needs.
In later calls, go back and softly revisit the numbers, anecdotes, sources, references, and examples used in earlier calls.
- Are their comments identical to what they said before? Too identical?
- Are they inconsistent?
- Do they sound hyperbolic or embellished?
If they’re identical, maybe it’s just a script – can they send it to you? If they’re inconsistent, don’t confront them. Ask them to explain further.
Regarding vendors, ask the analysts:
- How well they know each of the vendors relevant to the specific market segment.
- Who is new to them?
- How many of them have they known for a long time?
- How many do they know intimately?
- Have they all been clients at one point or another?
Regarding written research and presentations, make sure to ask these questions:
- What didn’t you say?
- What parts of this research generated controversy in the review process?
- What content was cut to not rock the boat?
- If you had more time or more space, what would you add?
Expand the Scope
Do some special prep work beforehand. Look for divergences between this author’s work and the work of others. Include the work of
- Other analysts in the same firm
- Analysts in different firms
- Article writers
- Salespeople from vendors you’re asking about.
Ask the analyst their opinion of the divergent positions. Can they rationalize the divergences? When and where might the divergent positions be correct?
Dig in where you might pick up more valuable unpublished insights. The purpose isn’t to attack the analyst who’s giving you their time and thoughts; it’s to dig more deeply into their thinking and extract value that might never see the light of day without your asking the questions.
Big Red flag
Look for another analyst firm to rely on if the one you’re working with will not give you access to the analyst-author of reports essential to your decision process.
- Note that not every bandwagon is a hype-mobile. Some of these themes are well justified (at least for some buyers.)
- Seek our support; ask us to provide a countervailing opinion where appropriate.
- Contact me at The Analyst Syndicate to see whether and where we think the wisdom you’re considering acting on is misleading.
- Talk to us well before you sign the contract.
- Finally, watch for future installments in this line of research. Send me your suggestions for topics to include. Current pieces in development include
- The perils of premature investment
- Why industry differences matter
- How the industrialization of analyst relations impacts you
- Data, surveys, and analysis sometimes don’t add up
- How to predict which predictions will fail