GE’s Predix predicament – an industrial giant finds software is hard

GE’s IoT predicament illustrates just how complex the engineering and management challenges of the Internet of Things really are.

Industrial giant General Electric is finding software is hard, reports Business Insider.

The company, which former CEO Jeff Immelt declared was a ‘digital industrial company’ is finding its Predix software system and associated cloud services are far more complex and difficult to manage than expected.

Back in 2015, I toured the head office of GE Software outside of Silicon Valley and interviewed the division’s boss, Bill Ruh.

Ruh was upbeat about the internet of things – or Industrial Internet in GE’s terminology – with an estimate the IoT was worth $14 billion to the company as it found new efficiencies and markets.

Today that vision’s looking a little tarnished as the company struggles with a 25% share price drop and a self imposed ‘time out’ on Predix’s development.

GE’s IoT predicament illustrates just how complex the engineering and management challenges of the Internet of Things really are.

The software needs of a sensor in a train brake pad are very different to that of fuel pump in a jet engine or the blade controllers of wind turbine.

Added to that is the challenge of organising, storing and securing the information these devices collect. This is the main reason why GE is moving its data management services to AWS and Microsoft Azure.

That a company with the resources and top level commitment of GE is struggling with this underscores the complexity of the internet of things. That complexity is something every IoT advocate and connected device vendor fails to consider at their, and their customer’s, peril.

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Securing the future workspace

HPI’s Secure the Future Workspace event focused on the risks of enterprise printing, but the discussion applies to all of the Internet of Things

This post is part of a corporate blogging assignment for HPI and IDC covering their Secure the Future Workplace event.

Security is probably the Internet of Things’ greatest weakness and probably the first devices to illustrate the weakness were networked office printers.

For HPI, the devolved printer and hardware arm of Hewlett-Packard, those IoT weaknesses is an opportunity to showcase their products. However the security of printers is only the tip of a frightening iceberg of technology risks facing businesses and homes.

Security starts at the top

The first keynote for the morning was Simon Piff, Vice President of IDC Asia/Pacific’s IT Security Practice Business.

Simon gave an overview of the challenge of digital transformation and the risks involved.

To Simon, digital transformation has five different aspects within an organisation – Leadership, omni-experience, information, operating model and workforce transformations – all of which have different demands upon management.

One thing he sought to emphasise during his keynote is an organisation’s IT security is a top down process. “If your CEO doesn’t care about cyber-security then how are you going to execute?” He asks.

For printers he makes an important point. “They are essentially a single function server.” He says, “this is another server.”

“There haven’t been headlines about printer hacks but we are about to hear about them.”

Simon’s points about enterprise security and networked printers are something that all computer users, be they in home or business, understand – almost every connected device can be a network server. Being hacked is a real risk for everyone.

Death of the perimeter

“Don’t accept complacency,” is the key message from the second keynote speaker, Edmund Wingate.

Edmund, HP’s Vice President and General Manager of the company’s JetAdvantage Solutions division, described how securing a company’s networking perimeter and relying on firewalls was “backward looking.”

In the printer world, that the typical office device has over 250 settings alone creates risks for network administrators and security officers.

Compounding that problem is the use of proprietary software in these devices. A plethora of custom operating systems, many of them based on outdated Linux distributions, opens opportunities for an infinite range of exploits.

It’s better for the industry and vendors like HP to be open about the systems they are using and any vulnerabilities they find as otherwise governments will be forced to step into the space, warns Edmund. “The absence of standards lets things percolate too long.”

Edmund’s point about proprietary and old software are important aspects in the entire Internet of Things security discussion. That there will be billions of devices ranging from network printers to traffic cameras and connected kettles running antiquated software is a problem the entire IT industry will have to manage.

When your networked is hacked

The day’s final session was a panel featuring Simon Piff, Managing Director ANZ for IDC; Carl Woerndle, Executive Director of Elevate Security; Hugh Ujhazy, Associate Vice President, IoT Practice Lead, IDC APeJ and Edmund Wingate.

Carl was the proprietor of Distributed IT, an Australian domain registrar that was spectacularly hacked in 2011. The damage done to the business was so debilitating that it eventually forced the company out of business.

The alleged perpetrator turned out to be an unemployed Australian truck driver with no formal  IT qualifications who had 700 other companies targeted. It’s a sobering lesson on how businesses are vulnerable.

Random attackers are the norm, Hugh Ujhazy pointed out, and ransomware is another factor which wasn’t widespread when Distributed IT was hacked.

Ujhazy sees Blockchain as the opportunity to rethink security. “We are on the cusp of changing the way we deal with devices and applications,” he says.

The consensus from the panel was all enterprise networks are vulnerable to inside threats – whether they are IoT devices like network printers, disaffected individuals, malware or hackers. For executives and boards, that’s an important message on how critical security is in the modern organisation.

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Juicing innovation

The Juicero’s expense, built in obsolescence and unnecessary waste is emblematic of everything that’s wrong with the current Silicon Valley culture.

Every tech boom has its excesses and it’s hard to go past the Juicero as the most egregious of today’s mania.

A number of high profile investors, including Google’s venture capital arm, have poured $120 million dollars into the internet connected device that squeezes juice from pre-prepared pouches of pulped fruit and vegetables.

Bloomberg found the devices don’t a great deal as the juice can be squeezed out of the packs by hand, which is just as well given the microchipped pulp containers can be disabled by the manufacturer.

While the Juicero aims to be the juicer equivalent of the Keurig coffee capsule, the device’s expense, built in obsolescence and unnecessary waste is emblematic of everything  that’s wrong with the current Silicon Valley culture.

The fundamental question of any business idea is ‘what problem does this solve?’ It’s hard to think of anything the Juicero fixes.

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Mining for jobs in an automated future

Increasingly automated mines show how the jobs of the future don’t lie in old industries.

While politicians clamour to ‘bring jobs home’, automation is increasingly taking those jobs away with the mining industry being the best example.

In 2015, McKinsey looked at the effects of automation in various US industries and found the production component of mining could lose over 80% of its jobs in coming years.

In a piece for Diginomica this week, I looked at a case study featuring Western Australia’s Fortescue Metal Group (FMG) from the recent AWS Summit in Sydney.

Slashing costs

When Fortescue planned their Solomon groups of iron ore mines in the Pilbara region of North-Western Australia in 2010, they estimated 75 manned trucks would be needed. As it turned out they only needed 49 robotic vehicles.

The savings, both in capital expenditure and operational costs was substantial and the entire operation saw its costs nearly halved.

It’s not just trucks becoming autonomous, functions like drilling and explosives laying are also being automated reducing costs and risks even further.

Dashed hopes

So mining communities like those in the United States hoping Donald Trump will bring back prosperity or Australians who believe a billion dollar subsidy to an Indian coal mining company will guarantee jobs are doomed to disappointment.

A modern mine is likely to employ more workers in an office thousands of miles away than on the site itself. Where once the surrounding region would get hundreds of jobs from a large mine, today it’s only going to be a handful.

It isn’t just the mine workers themselves though, McKinsey’s study also forecast the mining industry’s administrative workforce could see 90% of jobs going while senior management had the potential of being 99% automated.

Beyond blue collar roles

That this wave of automation will affect ‘white collar’ jobs as much as trades or unskilled workers isn’t new – this piece in 2015 for The Australian described how many of the ‘knowledge economy’ jobs will soon be done by robots or artificial intelligence.

Mining is a good indicator of where technology and employment is heading. We, and our political leaders, are going to have to think carefully where the future jobs are coming from as they aren’t going to be found in resurrecting old industries.

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Hacking the connected vehicle

American farmers hacking their tractors with Ukrainian software are a taste of what’s to come in the connected economy.

What happens when a vehicle manufacturer locks down their products’ software? John Deere’s customers are finding out as American farmers turn to Ukrainian software vendors for software to maintain their tractors.

John Deere’s behaviour is extreme as almost every component of a modern tractor has a software component which leaves farmers at the mercy of the company’s dealers and authorised mechanics.

So understandably the farmers are finding ways to hack their equipment to reduce downtime and costs, something permitted in the US after an exemption to the Digital Millennium Copyright Act (DCMA) was granted to vehicle software.

Vendor control over connected vehicles is a bigger problem for consumers than just maintaining the software, as the information collected from these devices becomes more valuable who controls that data becomes more important.

With global supply chains, increased regulatory requirements and demanding markets, the agricultural industries are probably leading the world in applying the Internet of Things and Big Data, so the challenges faced by farmers are things which will affect us all.

As everything from toasters to motor cars become connected and dependent upon code, the conflict between proprietary software, open markets and user rights is going to grow.

Consumers and the free market can only do so much to control the flows of data and who owns them. It’s hard to see how governments can’t become involved in how information is owned, traded and stored.

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Deeper in data and debt

Data tools are getting more powerful as the information collected about us grows. It presents us with some important choices

Data collection agency Experian’s deal with Finicity to collect and process borrower information is an example of the how Big Data is being used by the financial services sector.

Recently I wrote a piece for Fairfax Media on the Science of Money which included some quotes from Experian’s Australian managers. They were quite explicit about their use of data.

That a company like Experian is adopting more advanced analytics isn’t surprising given the power of the tools available. What’s also driving the adoption is the proliferation of devices available to track people.

Notable among those devices are personal assistants, as David Pogue writes in Scientific American, household technologies like Amazon Alexa, Google Home and Apple Siri are vacuuming up huge amounts of data on our behaviour, likes and dislikes.

Increasingly all of this is being fed into machines that determine our suitability for marketing campaigns, credit and financial services.

For companies like Experian this is a massive opportunity although the focus on credit suitability betrays a mindset more suited to the 1980s finance boom than the more complex times of the early 21st century.

It’s hard though not to think that given a choice the finance sector will happily use these tools to take us into another subprime lending crisis which would be a shame as these technologies’ potential for allowing us to make better decisions is immense.

How we use these tools will define our businesses, economies and communities over the next thirty years. We need to be careful about some of the choices we make.

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The science of money and data mining

The use of data mining by private and government agencies is widespread and only going to become more so. Do we care about the consequences?

Last week I wrote a piece for Fairfax Metro – the Sydney Morning Herald and Melbourne Age – looking at how government agencies and private credit companies are mining data.

That story sparked a range of interest with my doing a twenty minute segment on ABC Brisbane today on the topic which morphed into a deeper discussion on surveillance, particularly with the Australian government’s ‘metadata’ laws.

I’ll also be talking on ABC Radio Perth on Monday, March 6 about this story at 6.15am local time (9.15am Sydney and Melbourne).

In the wake of the Australian government’s Centrelink scandala national disgrace that is only getting worse – it’s worthwhile discussing exactly what data is being gathered and how it is being used.

The answer is almost everything with commercial operators like Experian pulling in data from sources ranging from credit card applications to social media services although store loyalty cards remain the richest information source.

As the Australian Tax Office spokesperson pointed out, none of this is particularly new as they have been collecting bank deposit data since the Federal government introduced income taxes in the 1930s.

The arrival of computers in 1960s changed the scale and scope of tax offices’ abilities to track citizens’ finances and gave rise to the major commercial credit bureaus.

With the explosion of personal electronics and internet connected devices in recent years along with increased surveillance powers being granted to government and private agencies, that monitoring is only going to grow.

The best citizens can expect is to have their data protected and respected with financial providers only using what is ethical and relevant in determining our access to banking and insurance products.

Politically the only way to ensure that is to make it clear through the ballot box, the question is do we care enough?

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