Paul Wallbank | Paul Wallbank - Communications Professional

When does a digital strategy matter?

Some businesses are obsessing too much about their digital strategy, a UK based business professor believes.

Should a business spend a lot of time on its digital strategy? A recent article in the Harvard Business Review suggests many businesses, and consultants, are focusing too much on the technology.

Freek Vermeulen, an Associate Professor of Strategy and Entrepreneurship at the London Business School, describes how strategists may be making a mistake in responding to digital disruption. He argues many industries are learning the wrong lessons from disruptors like Amazon, Uber and Google.

In Vermeulan’s view, the world is not a globalised as we’d like to think and the network effects that work so well in internet based industries don’t necessarily translate to other sectors.

As a consequence, businesses that work on the assumption their industries will be affect the same way as, say, the taxi industry with Uber or newspapers by Google and Facebook may well be making their own strategic mistakes.

Digital is changing the nature of competitive advantage in many businesses – just like major technological developments have done before. However, the change will not be uniform across all industries. Digital technology is affecting and will affect different businesses in different ways. Miss these nuances and your strategic decisions could lead you seriously astray.

That’s certainly true and how technology or a rapidly changing economy affects each industry, or business, is far from uniform.

One of the case studies Vermeulan uses is that of a consulting firm that has largely eschewed digital platforms and focused on its human assets – primarily the skills and connections of its associates and staff.

While that’s undoubtedly true of all consulting businesses to some degree, the use of digital tools and marketing is changing that industry dramatically as well.

Vermeulan is right in that some industries may want to respond more slowly than others to digital or economic changes, however a business that disregards them or reacts too slowly may not know what hit it.

A broken trail of government digital dreams

Until Australian governments commit to longer term visions, it’s unlikely any of their digital dreams will be achieved.

Last August the centrepiece of the Australian government’s digital dream came to an end. The Canberra Times this week described how “the Turnbull government has quietly killed off one of its biggest plans for ‘digital transformation’; the hugely ambitious gov.au website project”.

The abandonment of the project was an ignominious end of the plans for a Prime Minister who had promised so much at the time of his appointment, and that a cabinet submission would be pulled minutes before it was due to be tabled indicates the convoluted politics behind it.

Bizarrely, that story ran the same day the Federal Treasurer revealed the government would be running a ‘pilot project’ to put more services online as part of their attempts to harness the digital economy.

That the Australian Federal government is looking to run some pilot projects this year is remarkable given twenty years ago, in 1997, the then Prime Minister John Howard announced all appropriate government services would be online by 2001.

Australian taxpayers would be well justified asking what has happened over the last twenty years.

It could be argued that Australian governments are not particularly good at technology projects given ongoing disasters like the current Centrelink debacle, the failure of the 2016 Census and the collapse of the Tax Office’s portal shortly before Christmas.

Probably the main reason for Australian governments’ technology failures is the lack of focus, as shown by the Digital Transformation Office barely surviving one year.

That lack of focus is even more problematic as digital transformation projects are more about changing cultures than revamping technology, often making them a decades-long process.

Without a long term commitment to projects and policies, initiatives such as the Howard government’s 1997 Investing for Growth or Turnbull’s 2015 Innovation Agenda are doomed to failure. Until Australian governments commit to longer term visions, it’s unlikely any of their digital dreams will be achieved.

When governments misuse data

The Australian government’s misuse of data in harassing welfare recipients is something that should worry all citizens

Last year the Australian Federal government had a smart idea. To fix its chronic budget deficit, it would use data matching to claw back an estimated three billion dollars in social security overspending.

Unfortunately for tens of thousands of Australians the reality has turned out to very different with the system mistakenly flagging thousands of former claimants as being debtors.

How the Australian government messed up its welfare debt recovery is a cautionary tale of misusing data.

Data mis-match

At its core, the problem is due to the bureaucrats mismatching information.

Australia’s social security system requires unemployment or sickness benefit claimants file a fortnightly income statement with Centrelink, the agency that administers the system, and their payments are adjusted accordingly.

Most of those on benefits only spend a short time on them. According to the Department of Social Services, two thirds of recipients are off welfare within twelve months of starting.

Flawed numbers

Despite knowing this, the bureaucrats decided to take annual tax returns, average the individual’s income across the year and match the result against the fortnightly payment.

That obviously flawed and dishonest method has meant hundreds of former welfare recipients have been falsely accused of receiving overpayments.

Compounding the problem, the system frequently mis-identifies income because it fails to recognise employers may use different legal names, leading to people having their wages double counted and being accused of not reporting work.

Shock and awe

Under pressure from their political masters, the aggressive tactics of Centrelink and its debt collectors have left many of those accused shocked and distressed.

I can barely breathe when I think about this. My time period to pay is up tomorrow. I asked them for proof before I pay and I have heard horror stories of debt collection agencies, people being asked to pay so much, people being told there will be a black mark on their credit. I am so terrified. It’s so stupid for me to be terrified but I can’t help it. I am a student, I can’t afford anything!

Reading the minister’s response to criticisms, it’s hard not to come to the conclusion that intimidation was a key objective.

The numbers of people involved are staggering. The department of Social Services reported 732,100 Australians received the Newstart unemployment allowance in 2015-16. Should 66% of those have moved off the benefit during the tax year then up to 488,000 people will receive ‘please explain’ notices.

Nearly half a million people being falsely accused of welfare fraud is bad enough, but that is only last year’s figures – due to a law change by the previous Labor government, there is no limit to how far back Centrelink can go to recover alleged debts.

The System is working

Claiming the Centrelink debacle is a failure of Big Data and IT systems is wrong – the system is working as designed. The false positives are the result of a deliberate decision by agency bosses and their ministers to feed flawed data into the system.

How this will work out for the Australian government as tens of thousands more people receive unreasonable demands remains to be seen. Recent comments from the minister indicate they are hoping their ‘tough on welfare cheats’ line will resonate with the electorate.

Regardless of how well it turns out for the Australian government, the misuse of data by its agencies is a worrying example of how governments can use the information they collect to harass citizens for short term political advantage.

Beyond welfare

While many Australians can dismiss the travails of Centrelink ‘clients’ as not concerning them, the same data matching techniques have long been used by other agencies – not least the Australian Taxation Office.

With the Federal Treasurer threatening a campaign against corporate tax dodging and the failure of the welfare crackdown to deliver the promised funds, it’s not hard to see small and medium businesses being caught in a similar campaign using inappropriate data.

More importantly, the Australian Public Service’s senior management’s incompetence, lack of ethics and proven inability to manage data systems is something that should deeply concern the nation’s taxpayers.

In a connected age, where masses of information is being collected on all of us, this is something every citizen should be objecting to.

Goodbye to Yahoo!

The demise of Yahoo! shows eyeballs are not enough for a mature online business.

And so Yahoo!’s journey comes to an end with the company being renamed Altba and most of its operating assets given over to Verizon.

With the changes both CEO Marissa Mayer and original co-founder David Filo will leave Altba’s slimmed down board.

Mayer’s failure is a lesson that being an early employee at a successful, fast growth tech startup isn’t a measure of leadership. It may even be a hindrance given companies like Google were inventing new industries during her tenure there which develops different management skills to what a business like Yahoo! needs.

The biggest lesson of Yahoo!’s demise is how even the most powerful online brands isn’t immune from disruption itself, with what was once the internet’s most popular website being eclipsed by Google and Facebook.

Interestingly, as Quartz reports, Yahoo! is still one of the US’s most popular sites and only slightly behind Google and Facebook in unique monthly views.

Despite this, Yahoo! has struggled to grow for 15 years and has struggle to make money although it remains a four billion dollar a year business.

Which shows eyeballs aren’t enough for a mature web business, at some stage it has to show a return to justify its valuations.

Among Yahoo!’s many properties remain some gems like Flickr and it will be interesting to watch what Verizon does with them. Sadly any successes will be tiny compared to what the company once promised.

Uber’s sharing strategy

Ubers offer to share information with city governments and agencies is part of their bigger data strategy

For most of its existence, Uber hasn’t been shy about claiming to be at the forefront of the future of transport which fits into yesterday’s announcement of Uber Movement which promises to provide aggregated and anonymised trip data to give communities and businesses an overview of road usage in their districts.

Jordan Gilbertson, one of the company’s Product Managers, and Andrew Salzberg, Head of Transportation Policy, described how Uber intends to make transit time data available.

Uber trips occur all over cities, so by analyzing a lot of trips over time, we can reliably estimate how long it takes to get from one area to another. Since Uber is available 24/7, we can compare travel conditions across different times of day, days of the week, or months of the year—and how travel times are impacted by big events, road closures or other things happening in a city.

As the Washington Post reports, transport agencies do already have a lot of data on some aspects of commuter behaviour – particularly public transport usage – and the Uber information fills as ‘missing part of the puzzle’.

Taxis and buses are also increasing equipped with real time tracking equipment that also gives this data while traffic services like Wayze have been collecting this information for a decade.

So agencies aren’t short of this data and the concentration of Uber’s customer base in more affluent areas means their information may be skewed away from poorer areas. Recently a Sydney taxi driver mentioned to me how he’d stopped driving for Uber because most of the city’s sprawling Western Suburbs where he tended to drive didn’t use the service.

Uber’s offer is another piece in their data strategy that sees the company being a data hub for the logistics industry. It also helps if you’ve co-opted governments into your scheme.

Medium and the broken media model

Medium’s Ev Williams finds online advertising isn’t enough to sustain a hundred million dollar publishing company. The rest of the industry is not surprised.

How do you make money from online publishing? Medium’s Ev Williams shows he is as far away from the answer as the rest of us.

In a blog post yesterday Ev announced his company is firing fifty staff as online advertising revenues fall short.

Online advertising’s disappointing revenues are no surprise to pretty well anyone observing the online publishing industry for the past five years, it seems to have come as a revelation to Ev and the investors who’ve staked an estimated $140 million in the venture.

That money, which most online publishers would gag for, seems to have gone on a bloated headcount given the company can afford to fire fifty people. It’s a shame the company’s investors didn’t appoint a board that checked management’s hiring practices.

Something that should worry other publishers is the organisation’s Promoted Stories division is being shut down as part of the restructure. This underscores how branded content doesn’t scale the same way traditional advertising does and won’t represent a major revenue stream for online publications.

It isn’t the first time Ev Williams has got it wrong, in founding Twitter he and his team turned their back on ordinary users and developers to focus on courting celebrities in the hope big brands would pay large amounts to be associated with them. It didn’t work.

Contrasting Ev’s Twitter and Medium experiences with that of Buzzfeed founder Jonah Peretti is interesting. While Buzzfeed still hasn’t found the formula for profitability, Peretti and his team have gained a deep understanding of what works in online publishing.

To be fair to Ev, we’re all trying to figure out the revenue model that will work for online media, his travails with Twitter and Medium show just how hard it is to find a way for publishers to make money from the web. What is clear though is burning a lot of cash on sales staff is not the answer.

Jonah Peretti’s seven digital advantages

Buzz Feed founder Jonah Peretti laid out his vision of the changing media industry in his year end memo but he missed the one item most important – revenue.

Buzzfeed founder Jonah Peretti laid out his vision of the changing media industry in his year end memo but he missed the one item most important – revenue.

“Print revenue is decelerating at a rapid pace, cable subscriptions and TV ratings are starting to decrease even for live sports, and traditional media businesses are at various stages of a terrifying decline,” writes Peretti in accurately describes the challenges facing the industry.

Buzzfeed’s success has largely relied on sharing across social media, particularly Facebook. In his memo Peretti lays out how he sees the modern social and personalised publishers as having seven digital advantages over the push model of the mass media days.

Instant access to fresh content
On-demand access to entire media libraries
Nearly free distribution enabling many free ad-supported services
Global distribution providing access to content from every market
Data about audiences allowing personalization and customization of content experience
A feedback loop between audiences and content creators making media production more dynamic and responsive
Social experiences where people can use content to communicate and connect with the people who matter to them and weave media into their daily lives

Peretti is absolutely right, those digital advantages put online platforms far ahead of print publishers and broadcasters although the advertisers haven’t quite figured out how to make these positives work for them.

That advertisers can’t get their models to work on the digital platforms is also a problem for Peretti and Buzzfeed and the site had to half its 2016 revenue estimates earlier this year.

In the search for new opportunities, Buzzfeed hired a new Vice President of Marketing earlier this month as it appears the branded content model is too labor intensive and video isn’t proving to be the river of gold most online publishers hoped.

The advertising model appears to be just as broken for online publishers as it is for the traditional channels.

As Peretti has pointed out in previous end of year memos, new media platforms always struggle in their early years.

The difference in the modern media world is the internet destroyed the scarcity of publisher and broadcaster controlled advertising space, replacing it with an almost unlimited inventory supplied by Google, Facebook and other services that take most of the profit.

A better comparison to today’s online advertising conundrum are the early days of radio where it took RCA’s David Sarnoff to figure out how to make broadcasting profitable.

Like radio, online has great advantages over the older distribution methods but the revenue models that worked for those more traditional businesses don’t work on the newer medium.

Peretti, like every online publisher, is trying to find that new model and it seems he’s as further away from discovering it as the rest of us.

Rethinking artificial intelligence and the smarthome

Facebook founder and CEO Mark Zuckerberg spent 2016 experimenting with artificial intelligence in his smarthome and came to some interesting conclusions about AI and machine learning

What happens when the founder and CEO of one of the world’s biggest tech companies decides to create a genuinely smart home? Facebook’s Mark Zuckerberg spend 2016 finding out.

“My goal was to learn about the state of artificial intelligence — where we’re further along than people realize and where we’re still a long ways off,” Zuckerberg writes in a blog post.

The immediate problem Zuckerberg faced in creating his home made Jarvis automation system was many household appliances are not network ready and for those that are, the proliferation of standards makes tying them together difficult.

For assistants like Jarvis to be able to control everything in homes for more people, we need more devices to be connected and the industry needs to develop common APIs and standards for the devices to talk to each other.

Having jerry rigged a number of workarounds, including a cannon to fire his favourite t-shirts from the wardrobe and retrofitting a 1950s toaster to make his breakfast, Zuckerberg then faced another problem – the user interface.

While voice is presumed to be the main way people will control the smart homes of the future, it turns out that text is a much less obtrusive way to communicate with the system.

One thing that surprised me about my communication with Jarvis is that when I have the choice of either speaking or texting, I text much more than I would have expected. This is for a number of reasons, but mostly it feels less disturbing to people around me. If I’m doing something that relates to them, like playing music for all of us, then speaking feels fine, but most of the time text feels more appropriate. Similarly, when Jarvis communicates with me, I’d much rather receive that over text message than voice. That’s because voice can be disruptive and text gives you more control of when you want to look at it.

Given the lead companies like Amazon, Microsoft, Google and Apple have over Facebook in voice recognition, it’s easy to dismiss Zuckerberg’s emphasis on text, but his view does feel correct. Having a HAL type voice booming through house isn’t optimal when you have a sleeping partner, children or house guests.

Zuckerberg’s view also overlooks other control methods, Microsoft and Apple have been doing much in the realm of touch interfaces while wearables offer a range of possibilities for people to communicate with systems.

The bigger problem Zuckerberg identifies is with Artificial Intelligence itself. At this stage of its development AI struggles to understand context and machine learning is far from mature.

Another interesting limitation of speech recognition systems — and machine learning systems more generally — is that they are more optimized for specific problems than most people realize. For example, understanding a person talking to a computer is subtly different problem from understanding a person talking to another person.

Ultimately Zuckerberg concludes that we have a long way to go with Artificial Intelligence and while there’s many things we’re going to be able to do in the near term, the real challenge lies in understanding the learning process itself, not to mention the concept of intelligence.

In a way, AI is both closer and farther off than we imagine. AI is closer to being able to do more powerful things than most people expect — driving cars, curing diseases, discovering planets, understanding media. Those will each have a great impact on the world, but we’re still figuring out what real intelligence is.

Perhaps we’re looking at the what intelligence and learning from a human perspective. Maybe we to approach artificial intelligence and machine learning from the computer’s perspective – what does intelligence look like to a machine?

De-hyping the hype cycle

One of the useful tools in describing how technology is accepted by the market and society is the Gartner Hype Cycle.

Developed by the consulting firm, it describes the typical pattern of a technology product where at first it is ignored, then hyped before falling into the ‘Trough of Disillusionment” before maturing to find a productive role in the marketplace.

The curve though isn’t perfect – many products crash without making the ‘plateau of productivity’ and every technology has its own unique timeframe. Gartner’s role as technology analysts as commercial considerations come into play as well.

Given those imperfections, it’s worthwhile tracking how some of the technologies did on the hype cycle and how Gartner’s predictions went and on Imgur, Anton Tarasenkno has posted all the the Gartner end of year hype cycles from 2000 onwards to give us that opportunity.

PDAs and Smartphones

The ‘Personal PDA’ illustrates how technologies evolve and the original concepts become a dead end.

In 2001, the Personal Digital Assistant – devices like the Palm Pilot, Sharp Zaurus and HP iPac – were the productivity must have for connected workers and Gartner flagged them to be on the ‘Plateau of Productivity in between three to five years.

They never made it. The entire category crashed due to to poor product releases, confusing software wars – the buggy mess that Microsoft Windows CE scared many consumers away – and the rise of smartphones.

PDA’s vanish from the Gartner cycle in 2003 and three years later Smartphones make an appearance grinding their way up to the ‘Plateau of Productivity’.

There is a fair argument that smartphones are an evolution of the PDA – although not one of the PDA vendors or operating systems actually made it onto successful smartphones – but it does seem a bit of a sleight of hand simply to substitute one for the other.

As it turns out though, the 2006 prediction for the smartphone was spot on given the iPhone was released the following year.

Cloud computing

The evolution of ‘cloud computing’ is an interesting tale in itself. At the time of the 2000 Gartner hype cycle is was being described as Application Service Providers (ASPs) although the concept and technology could claim to be the descendent of the much earlier time shared mainframe computing systems leased out primarily by IBM.

In the 2000 Hype Cycle Gartner has ASPs just past the ‘Peak of Inflated Expectations’ and this was a fair call as ASPs were dragged down by the general ennui following the Tech Wreck a year later which saw the technology close to the ‘Trough of Disillusionment’.

ASPs then vanish for four years before reappearing as ‘Software as a Service/ASP’ in 2005 on the grind up to the ‘Plateau of Productivity.’

Portal mania

In the early days of the World Wide Web, portals were hot. On the public web, Yahoo! and MSN were expected to be the go-to destination for surfers while within large organisations, the intranet page was expected to be the centre of all corporate knowledge and the first place employees were expected to log into in the morning.

For the 2003 hype cycle, Gartner’s analysts certainly believed in portals with twelve different types of portals or related technology listed. The following year, the number had grown to fifteen.

Interestingly, the most advanced portal technology on the curve, ‘mobile access to portals’, was stuck climbing out the trough for both of those years. That probably indicates even Gartner’s enthusiasm for the term and the technology was enough to prevent the idea being overtaken by search and social media.

Looking to the future

While it’s entertaining with the benefit of hindsight to look at where Gartner’s predictions of more than a decade ago, it is worthwhile considering what the company’s analysts are predicting this year.

Virtual reality is the tech clawing its way up out of the ‘Trough of Disillusionment’ while augmented reality is hurtling towards the depths. Both are flagged to be mainstream on a five to ten year horizon.

At the ‘Peak of Inflated Expectations’ sits Machine Learning with the connected home and Blockchain approaching the top. Towards the start of the curve are technologies like Quantum Computing and human augmentation, both are flagged to be more than ten years away from gaining mainstream adoption.

Picking apart the Gartner Hype Cycle is a useful exercise in understanding the limits of the idea as well as reminding us of just how difficult it is to predict how technologies will mature and be accepted by society and industry.

Mapping digital divides

A survey of Australia’s digital divides shows access is improving but some of the gaps are growing

Earlier this year, Telstra released the Digital Inclusion Index along with its report on measuring Australia’s digital divide.

Last week in Sydney the company hosted a half day conference to look at the ramifications of the 2016 report.

Overall the report was good news with most indicators showing improvements although the gap between the connected and the most disadvantaged has widened since the first index was compiled in 2014.

In general, wealthier, younger, more educated, and urban Australians enjoy much greater inclusion. All over the country, digital inclusion rates are clearly influenced by differences in income, educational attainment, and the geography of socioeconomic disadvantage. And over time, some Australian communities are falling further behind.

The one factor the survey found that is declining nationally is affordability which the authors put down to Australians’ increasing reliance on the internet.

The Affordability measure is the only dimension to have registered a decline since 2014, but this outcome does not simply reflect rising costs. In fact, internet services are becoming comparatively less expensive – but at the same time, Australians are spending more on them.

Sadly affordability isn’t going to improve should the government’s proposed broadband levy of seven dollars a month become reality to subsidise rural users.

That such a levy would be proposed by a government that was opposed to a National Broadband Network and to ‘Big New Taxes’ while in opposition is an irony left for Australian political historians to discuss but it shows how comprehensively the NBN project has failed.

Even sadder is the NBN isn’t delivering for businesses as it increasingly becomes apparent the network being built will struggle to deliver 21st Century services to most of the nation.

That businesses are struggling to connect emphasises just how serious the digital divide is becoming for the economy – as supply chains in every industry become increasingly globalised regions that aren’t connected risk being isolated from their markets.

Policy makers have to consider the costs of those communities and groups being isolated from the modern economy. If we are going to be serious about building a twenty-first century society then we have to consider how disadvantaged groups and regions access global networks as well as making sure they have the skills to benefit from these technologies.

Mapping the areas of the disadvantage is a good first step but we have to look at how we address the segments of our society that are being left behind.

Shipping dead products

Google will need to focus on shipping good consumer products if it is going to compete with Amazon and Apple

A scathing review of Google Home raises questions about the company’s ability to ship hardware and its executives’ commitment to consumer markets.

“I was so excited,” recalls Business Insider’s Ben Gilbert about the announcement of the revamped Google Home last may. Sadly, he found the device lacking integration with the rest of the company’s services and unreliable in connecting with his Wi-Fi network.

He returned the device and now vows to wait until “AI technology to improve dramatically.”

While Gilbert may wait, the market won’t with Amazon’s Alexa and Apple’s Siri cementing their market positions and a range of startups promising to change the market.

Google – or Alphabet’s – failure to execute with the Home product should worry shareholders as the company has shown it hasn’t been good at getting consumer devices to the market and the organisation’s notorious management attention deficit disorder seems to have crippled this device very early in its development, a far from good sign.

The Google Pixel smartphone shows the company is capable of shipping good products, but that commitment has to extend across all their hardware and consumer software products.

In highly competitive market with well cashed up and focused competitors like Amazon, Facebook and Apple, Google will have to ensure good products are shipped in their name. Substandard will not survive in this marketplace.

Old king coal loses his merry men

Desperate rural communities look to obliging politicians to get mining jobs back. Sadly they won’t be returning.

The industrial revolution’s most important energy resource was coal, even today it generates most of the world’s electric power.

However, the last half century hasn’t been good for those communities and workers whose incomes are dependent upon coal as the industry has moved away from labour intensive ways of digging the stuff up, alternative sources of energy have developed and the consequences of dumping billions of tons of carbon into the planet’s atmosphere come to be understood.

The US Energy Information Administration’s annual report on the nation’s coal industry makes grim reading, with both production and employment levels falling.

Coal industry jobs were one of the touchstone issues in the recent US Presidential elections. As The Guardian reported, former staunch Democrats in the mining regions – some of America’s poorest counties – supported Donald Trump on the strength of the promise to reinvigorate the sector.

Sadly, as the EAI reports, those coal jobs are never coming back even if the world starts using more. Since World War II, the productivity of US coal mines has increased from .72 tons per worker to 5.22 in 2011.

Despite a recent slight drop in US productivity at the end of last decade – apparently due to spoil recovery during a period of booming prices – the trend is not good. As Australian academics warn, increased mine automation means jobs in that industry are going to become increasingly scarce.

Like Donald Trump and the distressed US mining regions, Australian politicians believe that coal mining will provide the jobs of the future. They are wrong.

Those communities and politicians hoping for jobs in the 21st Century may well be better off looking to the future rather than the past. Nineteenth Century thinking is not going to provide answers.