And remember, there’s no such thing as a bad idea

That is the cue – “remember, there’s no such thing as a bad idea” – for beginning the sport of suggesting ideas to my fellow brainstormers. However, instead of spurring me to reckless idea generation, it always stops me in my tracks while I re-evaluate the brainstorm facilitator. There is clearly such thing as a bad idea.

Playing in traffic while blindfolded.

Taste testing the contents of the laundry cupboard.

Stripping during a speech to parliament.

Assaulting an armed police officer.

It’s not hard to brainstorm them. So, why begin an exercise with people whose opinions you value by telling them such utter nonsense?

There are good intentions behind it, I admit. Even bad ideas may have the germ of a good idea hidden within them, and maybe one of the other brainstormers can bring that forth. Encouraging people to speak their ideas without thinking about their worth can improve the pace of the brainstorm session. Disruptive ideas can come from those outside of a field, because traditionally such ideas would have been considered “bad” by those inside the field.

On the other hand, perhaps merely being accepting of bad ideas is not going far enough. I’ve found that I can generate many more ideas of much greater variety if I focus on just generating bad ones.

Suggesting ideas in a language you don’t speak.

Brainstorming with just one person in the room.

Miming ideas to the other brainstormers.

Providing the same ideas as from the last brainstorm.

Overall, it is recognised that constraints enable creativity. The restricted forms of the haiku, sonnet or even limerick are able to result in enjoyable poetry. So, it’s understandable that coming up with “any idea, whether good or bad” will result in less creative ideas than coming up with “only bad ideas”.

Still, I don’t know why “only bad ideas” seems to work better for me than “only good ideas”. Maybe it’s simply that there are more bad ideas than good ones? Unfortunately, I can’t see a brainstorm session achieve a useful outcome if everyone involved is aiming for the worst ideas.

So, I’ve had an idea for how to harness the power of bad ideas in brainstorming. At the start of the session, the facilitator gives each brainstormer a note with either Good or Bad on it – which they keep secret from the other brainstormers – and this states the type of ideas they need to suggest. Maybe just a third of the brainstormers are given Bad, since their ideas will otherwise likely outnumber the Good ones.

This should help with improving the volume and diversity of ideas in brainstorms. In this case, the brainstorm facilitator will need to cue the start of the session with something like “Remember, I want to hear your ideas, even if they are bad.”

Tell me if this works for you, since I’m not sure if my idea for better brainstorming is a good or bad one.

Thinking of changes to traditional brainstorming.

Putting those thoughts out in public.

Lessons from NYT on innovation

The Kindle New York TimesWhatever the circumstances that led someone at The New York Times to leak their report on Innovation, I am thankful. Published (internally) in March, it is the fruits of a six month long deep-dive into the business of journalism within a company that has been a leader in that industry for over a century, and provides an intimate and honest study into how an incumbent can be disrupted. It is 97 pages long, and worth reading for anyone who is interested in innovation or the future of media.

The report was leaked in full in May, and I’ve been reading bits of it in my spare time. Just recently I completed it, and felt it was worth summarising some of the lessons that are highlighted by the people at the Times. As it is with such things, my summary is going to be subjective and – by nature – highly selective, so if this piques your interest, I encourage you to read the whole thing.

(My summary ended up being longer than I’d originally intended, so apologies in advance.)

Organisational Division

Because of the principle of editorial independence, the Times has clear boundaries between the journalists in the newsroom and those who operate “the business” part of the newspaper, which has been traditionally about selling advertising. This separation is even known as “church and state” within the organisation, and affects everything from who is allowed to meet with whom (even during brown-bag lunch style meetings) to the language used to communicate concepts. This has worked well in the past, allowing the journalism to be kept at the highest quality, without fear of being compromised by commercial considerations.

However, the part of the organisation that has been developing new software tools and reader applications is within “the business” (not being journalists), and has hence been disconnected from the newsroom. Hence new software is not developed to support the changing style of journalism, and where it is, it is done as one-off projects. Other media organisations are utilising developers more strategically, resulting in better tools for the journalists and a better experience for the readers.

Lesson: Technology capability needs to be at the heart of an innovation organisation, rather than kept at arms-length.

Changing Customers

For a very long time, the main customer of the Times has been advertisers. However, print media is facing a future where advertisers will not pay enough to keep the organisation running. Online advertising pays less than print advertising, and mobile advertising even less again. Coupled with declining circulation due to increased digital readership, the advertising business looks pretty sick. But there’s a new type of customer for the digital editions that is growing in importance: the reader.

While advertising revenues had the potential to severely compromise journalism, it’s not so clear that the same threat exists from reader revenues. In theory there is a good alignment: high quality journalism results in more readers. But if consideration of attracting readers is explicitly kept away from the newsroom as part of the “church and state” division, readers may end up being attracted by other media organisations. In fact, this is what is happening at the Times, with declines in most online reader metrics, and none increasing.

In the print world, it was enough to produce a high quality newspaper and it would attract readers. However, in the digital world this strategy is not currently working. Digital readers don’t select a publication and then read the stories in it, they discover individual articles from a variety of sources and then select whether to read them or not. The authors of articles need to take a bigger role in ensuring those articles are discovered.

Lesson: When customers radically change, the business needs to radically change too (many true-isms may be true no longer).

Experimentation

The rules for success in digital are different from those of traditional print journalism, although no-one really knows what they are yet. That said, the Times newsroom has an ingrained dislike of risk-taking. Again this made sense for a newsroom that didn’t want to print an incorrect story, and so everything had to be checked before it went public. However, this culture inhibits innovation if applied outside of the news itself.

Not only does it a culture of avoiding risks prevent them from experimenting and slow the ability to launch new things, but smart people within the organisation risk getting good at the wrong things. A great quote from the report: “When it takes 20 months to build one thing, your skill set becomes less about innovation and more about navigating bureaucracy.”

Also, the newsroom lacks a dedicated strategy and operations team, so doesn’t know how well readers are responding to experiments, or what is working well for competitors. Given that competitors are no longer only other daily newspapers, it’s not enough to just read the morning’s papers to get insight into the competition. BuzzFeed reformatted stories from the Times and managed to get greater reader numbers than the Times was able to for the same stories.

Lesson: If experimentation is being avoided due to risk, then business risks are not being managed effectively.

Acquiring Talent

It turns out that people experienced in traditional journalism don’t automatically have all the skills to meet the requirements of digital readers. However, the Times has a bias for hiring and promoting people in digital roles based on their achievements as journalists. While this likely worked in the past to create a high quality newspaper, it isn’t working in digital. In general, the New York Times appears to be a print newspaper first, and a digital business second. The daily tempo of article submission and review is oriented around a daily publication to be read in the mornings, rather than supporting the release of stories digitally when they are ready to be published. Performance metrics are still oriented around the number of front page stories published – a measure declining in importance as digital readers cease to discover articles via the home page.

The lack of appreciation for the digital world and digital people in general has resulted in the departure of a number of skilled employees, according to the report. Hiring digital talent is also difficult to justify to management given that demand has pushed salaries higher for skilled people even if those people are relatively young. What could be a virtuous circle, with talent attracting talent, is working in the opposite direction with what appears to be a cultural bias against the very talent that would help the Times.

Lesson: An organisation pays for the talent either by paying market rates for capable people or paying the cost in lost opportunities.

Final words

When I first came across the NYT Innovation report, I expected to read about another example of the innovators’ dilemma, where rational business decisions kept them from moving into a new market. Instead, the report is the tale of how the organisation structure, culture and processes that made The New York Times great in the past are actively inhibiting its success in the present. Some of these seem to have become sacred cows and it is difficult for the organisation to get rid of them. It will require courage – and a dedication to innovation – to change the organisation into one that is able to compete effectively.

Wolfram’s Folly?

Back in the 80s, I read Robert Heinlein’s sci-fi novel Friday, where the main character did an amazing trick with a computer. She discovered a correlation between a number of seemingly unrelated factors and the incidence of the plague – information that allows her to avoid the next plague outbreak. I thought it would be pretty cool when computers reached the point that this sort of thing could be done.

I suspect Heinlein and Stephen Wolfram had a similar idea. Wolfram has just launched a web site called Wolfram Alpha that provides a way for non-sci-fi-characters to discover strange and interesting facts. It is sort of a cross between a cloud-based version of Mathematica and the CIA World Factbook. You can ask what is “2+2” or the “Population of Australia / New Zealand”. They state they have “10+ trillion pieces of data” in their database already.

But the most interesting thing about it for me is that it can answer questions that have never been asked before. Unlike Wikipedia or Google, which offer up information that people have already written down somewhere, Wolfram Alpha computes answers from its data. For example, I asked it for the “next solar eclipse in Melbourne” and got back the answer Friday, July 13, 2018 (along with a heap of other information and charts). Such information is not easily obtainable from Google.

However, while it is clear how ambitious and innovative this project is, it’s not clear to me when people would typically use it. Why would someone use it to, say, find weather information rather than going to a weather website, or movie details rather than going to a movie website. Given that Wolfram Alpha has to gather and “curate” the data in their database, specialist websites are likely to have an advantage in timeliness or breadth of their data. This is indicated in a TechCrunch article that shows they are sometimes using 2006 statistical data when 2009 data is available.

Even if ordinary people won’t regularly use it, perhaps it could get used for specialist projects or assignments. However, another issue is the black box nature of Wolfram Alpha. While Wikipedia considers itself a “tertiary source” and Google is more of a catalogue than a source, Wolfram Alpha may be the only source of a particular piece of information, given that it computed it. So, how would this data be referenced? Can it be considered a trusted source? Will specialist projects or assignments be able to use it if it isn’t? And if it can’t be used by them, then by who?

Given that Wolfram Alpha is so cool, I hope it doesn’t prove to be a folly. I enjoyed reading Stephen Wolfram’s A New Kind of Science, which he ended up provided online for free as a bit of a philanthropic service. I really wonder if that could be possible for this new project.