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Bill Bennett


Tag: software

Controlling digital subscription spending

We spend a lot on digital subscriptions. More than people think.

You can buy streamed television entertainment, sports coverage and music. When these options bore you, there are services that deliver computer games over the net.

Newspapers and magazine publishers now sell digital subscriptions.

Then there are online storage services. These includes those that specialise in looking after your photographs.

You can pay monthly for small business accounting, for security or productivity applications. Xero, Microsoft Office or Adobe Photoshop are popular examples.

Little and often

Subscriptions tend to be monthly or annual. Although there are those who charge for three or six months at a time.

Each monthly payment might be small in itself. But they soon add up to a hefty recurring commitment.

Estimates of how much people spend depend on what you include. Should you, say, include your mobile phone and broadband bills when you tot up your total spend?

Few people can tell you how much they spend on subscriptions. A US consulting firm asked Americans to guess their monthly spend: They underestimated by a huge margin. The average spend was three times people’s first guess.

It would not be that different if you asked New Zealanders.

When ignorance is not bliss

Not knowing your spend should be a wake up call. It would make a budgeting expert flinch. When you’ve no idea how much money is dribbling away, it’s hard to make rational spending decisions.

The amount people spend on subscriptions climbs each year. In part that’s because there’s more to buy. A year ago Netflix, Neon, Lightbox and Amazon Prime were the main New Zealand streaming video options. This year Disney joined the party. And there is a revamped Apple TV along with a fleet of niche alternatives.

Another reason spending climbs is we connect more and more devices to the Internet. One way or another these devices need feeding.

Weird subscription economics

There’s a lot of weird economics in digital services. On one level it all makes sense. On another it might not.

The price of individual digital services is usually low. When software companies switched to selling online subscriptions, it looked like a bargain.

Lower headline prices seduced customers. Take Microsoft Office. The annual NZ$120 subscription looks a bargain compared with five times as much for a packaged version. Knowing that you’d always be up-to-date and compatible with others helps ease fears about long-term costs.

Software purchased the traditional way can go on working for years. There are people with ten-year-old versions of Word. If you keep software that long, subscriptions are expensive compared with buying outright.

Software updates

After all, it’s not as if, say, Microsoft Word has changed much in ten years. This goes for a lot of subscription software.

Xero is newer than Word. There is no pre-subscription era to look back at.

In the early years, Xero developed fast. It grew up with its customers.

As far as what ordinary customers see, the product is now stable. There may be updates, but its core functionality for small business owners has not budged in a while.

Sometimes the upgrades to subscription software are the digital equivalent of a lick of paint and a rub down. Things look new and fresh, but nothing important has changed.

Renting music

Music subscriptions obey a different set of economic rules. Many fans have hundreds, even thousands of dollars invested in vinyl, CDs and digital downloads.

My non-streaming digital music collection has more than 40 days of listening material. That’s 40 times 24 hours. I can go the best part of a year without hearing the same track twice.

Paying NZ$20 a month on top of this, when a lot of what is served up is sitting on my computer, doesn’t make sense. In effect, people in this position are paying an algorithm to find new songs. Which is great if you thirst for new songs. Otherwise, it’s an indulgence.

Tracking your subscription spend

As we’ve seen, one worrying aspect of digital subscriptions is that it is hard to keep track of them all.

It is even harder to know if you get value from each of the services in your portfolio.

Take, my Amazon Prime subscription. It is ‘free’ (that’s free as in marketing language, not free as a in free beer) as part of my broadband plan. In the last year we may have watched five or six hours of Prime material. If we paid for the subscription, the cost per show would be prohibitive.

It’s clear this would not be a good service to purchase when the broadband ‘free’ offer expires.

Not knowing is part of the business model

The point earlier about people not knowing how much they spend on subscriptions is more than an anecdote.

Allowing people to forget about subscriptions but carry on paying the small monthly fee is part of the business model. It’s like gyms. They collect a sizeable slice of their revenue from people who rarely show up to use the equipment.

One reason people sign up for a streaming service is to watch an original series or two. Think of those who joined to watch Game of Thrones.

The service providers know that once customers have sucked dry the handful of programmes they signed for, their subscription can tick over for months before they realise they are no longer getting value.

Audit your subscription spending

It’s a good idea to audit your spending on digital services. There’s a chance there will be at least one active subscription that you don’t get value from. There will be annual and monthly payments, perhaps others.

One nasty trap many fall into is the free trial period. Often you are asked for credit card details when you sign on. It may take a few cycles before you realise what happened. This is extra hard when the trial is for an additional service from a provider you already buy something else from as the charge can be buried with something else in your bank statements.

Work through your card or bank statements. You’ll need to look at the last 12 months to capture all annual subscriptions. If you can, pull the data into a spreadsheet and count up the subscription total. Look for double-ups and services that seemed like a good idea at the time, but are no longer used. Cancel the repayments now. You’ll forget later.

Watch for extras. These can be hidden. Streaming services may charge more for 4K content or for not including advertising. You may pay for more cloud storage than you need or for options that don’t get used.

If this all sounds confusing, and it is, remind yourself this is not an accident. Keeping you confused about subscriptions is worth billions to service providers. Vast sums are at stake when millions of customers forget to cancel at the end of popular series.

Open source: Why you should care

To most people open source means free software.

Anyone can download this kind of software without paying a fee. It doesn’t break any laws. You have the original developer’s permission to use it.

You can run the software, copy it and pass it on to friends and colleagues.

Free software is only part of the story. It isn’t the most important thing about open source. Yet free software is liberating.

Open source lets you look at code

What matters more is that you can look at the code used to write the software. This means you can see how the developers made the program.

If you have coding skills you can figure out what the developers did. You may be able to understand the assumptions and decisions they made when they wrote the code.

You can tinker with the code and release your own customised version.

Or perhaps you might spot a flaw or an area where the original developers could have done something better. When that happens you can send what you found to the developers and have them fix it, or you can fix it yourself and send them the improved version.

Improving software

This is how software evolves and improves over time. The same process can work with software that isn’t open, but letting everyone interested take a look speeds things up and often means better results.

When you tinker with, improve or fix open source software, you are expected to make your new version as freely available as the original. That way others can follow your work, improve or fix it.

This is a virtuous circle.

Any piece of code can be open source. There are libraries of code snippets you can use to perform simple tasks or include in your own projects.

There are applications and even operating systems. Some of the best known software is based on open source.

Beyond free

While ‘free’ is an important part of the philosophy, there can be open source paid-for software. That is you can look at the code, but you have to pay to use it. The money is often used to pay for further development.

This approach has many of the same benefits. It means that people and companies can earn a living at the same time.

There are also many commercial and semi-commercial products and services that are build on open source foundations.

The opposite to open source software is often known as proprietary software. You can think of this as closed source. It is where someone, usually a company, owns the intellectual property. In some cases this can include patents.

As a rule you don’t get to see proprietary code and you pay to use the software. Until about 30 years ago all software was proprietary. A lot of enterprise and software used by government still is.

Open source now dominates the software world. Most of the world’s systems run on it. The web is open. Most phones run Android, which is a form of open source.

Turns out I’m almost certainly a bot

According to Botsight, I am “almost certainly a bot”. Or at least my Twitter account is.

Botsight says it uses artificial intelligence to decide if there is a human or a bot behind a Twitter account. The software was developed by NortonLifeLock, which was formerly part of Symantec.

The goal is to help fight disinformation campaigns. It’s hard to argue with the sentiment behind this.

Botsight in a browser

You install Botsight as a browser extension. NortonLifeLock says it works with the major browsers. It turns out that mainly means Chrome. There’s no support for Safari and when I first tested the Firefox version that wasn’t delivering. These things happen with beta software. It’s no big deal.

Then, when Twitter is running in your browser, Botsight flags whether an account is likely to be human or a bot. You have to use the office Twitter website. A green flag shows an account that is likely to be human, red tells users to be wary.

The flags also show percentages. In my case the score is 80 percent, that’s enough for alarm bells to ring.

At Botsight says, I’m “almost certainly a bot”.

Botsight report

The developers say they collected terabytes of data then looked at a number of features to determine if an account is human or not. The software uses 20 factors to make this decision.

More AI nonsense

NortonLifeLock says its AI model detects bots with a high degree of accuracy. It’s a typical AI claim and like many of them, doesn’t stand up too well when tested in the real world.

No doubt a lot of Botsight readers who encounter my Twitter wit and wisdom will assume the worst.

It’s not going to happen, but that could be grounds for a defamation action. Sooner or later someone is going to sue a bot for character assassination.

Like it says at the top of the story I’m on the wrong side of this equation.

Bot gives?

I asked NortonLifeLock how come I’m identified as a bot. Daniel Kats, the principal researcher at NortonLifeLock Research Group says there are three main reasons.

The first is my Twitter handle: @billbennettnz.

Kats writes:

“The reporter’s handle is quite long, and contains many “bigrams” (groups of two characters) that are uncommon together. This is a sign of auto-generated handles (ex. lb, tn, nz). It’s also quite a long handle, which in our experience is common of bots.”

I didn’t have much choice here. My given name includes that tricky LB combination. I doubt changing Bill to William would have made any difference.

There are a lot of other Bill Bennetts in the world. Others got to the obvious Twitter handles first. Mine tells people I’m in New Zealand. Trust me, the alternatives look more bot-like.

The only practical way to change this is to kill the account and start Twitter again from scratch. It is an option.

Following too many

Botsight’s second alarm is triggered by my follow to follower ratio. It turns out that following 2888 people is ’an usually high number, especially in relation to the number of followers”. Kats says it is no common for a human to follow that many others.

Well, that’s partly because I use Twitter to follow people who might be news sources.

The idea of letting bots or AI bot detectors dictate behaviour bothers me. Yet, if Botsight thinks I’m a bot, it’s possible other researchers and analytical tools looking at my account think so too. We can’t have that. Perhaps I should cull my follow list.

So, please don’t take offence if you’re unfollowed. I need to look more human. Only up to a point. On one level I don’t care what a piece of software thinks about me. On another, I get a fair bit of work come to me via the Twitter account so it may need a bit more care and attention.

Not enough likes

The third sign that I’m a bot is that my number of favourite is low. Favourite is the official Twitter terms for liking a tweet. Apparently I don’t do this as much as other humans.

On the other hand, I link to a lot of web posts. Linking lots and not favouriting much is, apparently, a sign of a bot.

The Botsight software could take note that I often get involved in discussion threads on Twitter. That’s something that a human would do, but would be beyond most bot accounts.

From the bot’s mouth:

Well, there you have it. I’m a bot. Perhaps that means I should put my freelance rates up.

Of course, any AI model is only as good as the assumptions that are fed into it. This is where lots of them fall down. We’ve all heard stories of AI recruitment tools or bank loan tools that discriminate against women or minorities. Bias is hard coded.

This is nothing like as bad. On a personal level I’m not unduly worried or offended by Botsight. Yet it does give an insight into the power and potential misuse or misinterpretation of AI analysis.

COBOL back from the dead… again

Many US systems that process unemployment claims still run on COBOL, a 60-year-old programming language that relatively few coders understand.

IBM plans to offer free COBOL training to address overloaded US unemployment systems:

“IBM is releasing a free training course next week to teach the 60-year-old programming language COBOL to coders. It is also launching a forum where those with knowledge of the language can be matched with companies in need of help maintaining their critical systems.

“The moves come in response to desperate pleas by state governors for anyone with knowledge of COBOL to volunteer their time to help keep unemployment systems functioning, a critical need as the coronavirus has resulted in an unprecedented surge in people being laid off and having to claim unemployment benefits.”

Younger readers may be mystified by this. COBOL is a programming language from the early 1960s. It was mainly used to write business applications1 on mainframe computers.

It wouldn’t be accurate to say COBOL is like Basic, but there are some similarities. If you’ve used Basic, especially an early version, you’d recognise some of the concepts.

Printing numbers, text

One big feature back in the day was the ability to carefully place printed numbers and text in the right places on forms… so that computers could, among other things, write paper cheques.

This was a strength, but, in a sense it turned out to be a weakness, as we shall see later.

Another big feature of COBOL something newer programming languages might learn from, is that it is self-documenting. That is, it is easy to write code in a way that other programmers can follow. This was important as it meant others could pick up the pieces at any point.

In 1975 I studied Computer Science A Level at a technology college in the UK. We mainly worked in Fortran, another early language, and Assembler, which is a kind of half way house between machine code and a formal language. There was some Basic and some COBOL.

COBOL obsolete in the 1970s… sort of

At that time a computer science lecturer introduced us to COBOL. I remember him saying that the language was still important, if we were going to end up as programmers it would probably be what we would use at first. However, he went on to say  COBOL probably wouldn’t be around much longer.

That was 45 years ago. It is still going strong.

The headline mentions that COBOL is back from the dead again. That’s because it had a come back in the late 1990s. Much of the problem that was known as the millennium bug or Y2K, was to do with COBOL code.

In the late 1990s, many important programmes, especially those used for billing systems and for government, used COBOL. The printing features had standard ways of handling numbers and, in particular dates.

From memory, correct me if this is wrong, COBOL could handle the year number in more than one format, but almost every programmer stuck to using just two digits to show the year. So they represented 1975 as 75. When the year 2000 rolled around, most COBOL programs interpreted this a 1900. The error would then cause problems elsewhere in a program.

COBOL’s second coming

So in the late 1990s, industry dragged COBOL programmers out of retirement to fix up the software some of them wrote in the first place. I fielded calls from recruiter offering me huge money to work on fixing COBOL code.

Keep in mind that I have never worked as a programmer. I did one year of university Computer Science before realising this was not the career for me. And my only brush with COBOL was a few lectures during the mid 1970s. This tells you just how desperate businesses were to get their code fixed in the late 1990s.

Now COBOL is back in the spotlight as many US unemployment systems still use the language. They are busy right now with US unemployment rates going through the roof. IBM is training people to fixed COBOL code.

Undead software

Here’s the weird thing about COBOL. It wasn’t even remotely cutting edge technology by 1980, yet a lot of mainframe programs depended on it. Companies rarely reworked programs with more modern programming languages. Instead they employed teams to keep maintaining and tweaking ancient code. Over time they dropped many old programs for newer technology, but not at the pace you might imagine.

Because everyone knew COBOL was past its sell-by date, people didn’t worry about the looming Y2K problem until the late 1990s. They assumed the old code would be replaced by then. But it wasn’t. Those programs kept churning on.

I found this reference at the Six Colors website:

Back in 2015 my pal Glenn Fleishman found the oldest computer program still in use for MIT Technology Review, and guess what:

In 1958, the United States Department of Defense launched a computerized contract-management system that it dubbed Mechanization of Contract Administration Services, or MOCAS (pronounced “MOH-cass”). The system was designed to use the latest in computation and output technology to track contracts in progress and payments to vendors.

Fifty-seven years later, it’s still going…. MOCAS is written in COBOL.

On and on

That same attitude applied in the late 1990s. Programmers patched code on the assumption that the clunky old COBOL programs that had made it to 2000 were not going to stay in use much longer. This lead to another problem.

It’s not only COBOL that carried on this way. Microsoft Windows retained many original lines of code from the 1980s well into this millennium. I’m not sure if it is still true today, but for decades Microsoft Word included segments of ancient code. In many cases the app didn’t actually use the code, but developers were often unwilling to remove it until the next big clean up.

  1. In those days people rarely talked of applications. If they did, it was more often about the application of the computer to a task than a synonym for program. Likewise, the people who wrote programs were always programmers, I don’t recall hearing the term developer until well into the PC era. Again, if you remember otherwise, feel free to comment. I’m not infallible. Nor is my memory. ↩︎

Skeuomorphism: A user interface Catch 22

If I didn’t promise to help you out in the next sentence, you’d probably have to look up skeuomorphism in a dictionary.

In simple terms the word means something that resembles whatever it was that used to do the job.1

The word may be unfamiliar. The idea is not.

Take the old Macintosh Address Book app. Before Apple modernised its software, the Address Book app looked like a paper address book.

You might also remember when computer operating system desktops had waste paper bin or trash can icons to tell you this is where you throw things away.

Skeuomorph central

The smartphone is skeuomorph central. Every iPhone has icons showing a torch, a telephone handset, a camera and so on. What each of these does is obvious. The envelope icon isn’t quite so apparent, yet you don’t need a PhD to figure out it is for email. Android phones have similar skeuomorphs.

Skeuomorphs don’t have to be software. Houses might have cladding where manufacturers made the building material resemble wooden boards or brick.

Soon electric vehicles in Europe will have to make noises so that pedestrians and others get an audio cue to take care.


The idea behind skeuomorphism is that it helps you to better understand what you are looking at. It’s a visual clue telling you the purpose of the object. You see something familiar and, bingo, you know what that thing is going to do.

There’s a special breed of skeuomorph idea where the visual cue lives on long after the original item has disappeared from use.

Mr flippy floppy

Perhaps the best known is the floppy disk icon you sometimes see used to indicate the save function.

It’s getting on for 20 years since computers had built-in floppy disk drives. An entire generation has entered the workforce without every having seen a floppy disk in action. And yet, everyone knows what that image is supposed to mean.

No doubt you have heard stories of young people encountering a real floppy disc for the first time. While they may not know what the item is, or how it is used. They often recognise it from the icon.

Time to put skeuomorphism to bed

While the thinking behind skeuomorphism makes sense, as far as software and operating systems go, it’s best days are in the past. Skeuomorphic designs are often fussy and ugly. They clutter things up. The images are often meaningless and what is represented is not always clear cut.

Yet there’s a Catch 22 here. I prefer minimalist design. It’s easier to focus on the job in hand when the software stays out of the way. I was about to say that when I’m writing, I prefer to start with a blank sheet of paper. Which is, of course, itself a skeuomorphism.

  1. 1 My Mac’s dictionary says: An object or feature which imitates the design of a similar artefact made from another material. ↩︎