Learning the tools of online business

Accountants are faced with a great opportunity, but they have to learn the tools of online business

The accounting and professional services industries are uniquely positioned as the economy goes digital, while their own sectors are undergoing radical change so too are their clients.

Given the changes facing the accounting industry, the invitation to host last week’s CPA Australia Technology Accounting Forum‘s second day in Sydney was a good opportunity to see how the profession and its clients are dealing with major shifts in their industry.

The accounting profession has been one of the big winners of the Twentieth Century’s shift to a services economy. Last week’s story on how the workforce has been changing illustrates this with a chart showing how the occupation has grown over the past 140 years.

accountants-employed-the-uk

In many respects accountants should be well placed to benefit in a data driven economy given the training and skills they posses. The big challenge for existing practitioners is to shift with the times.

The transition from what’s been lucrative work in the past will be a challenge for some in the profession. Many of the manual tasks accountants previously did are now being automated with direct data links increasingly seeing operations like reconciliations and filing financial returns being done in real time without the need for any human intervention.

In private practice, the shift to cloud computing and direct APIs has stripped out more revenues with useful earners like selling boxed software petering away as services like Xero and Saasu arrived and established players like Intuit, Sage and MYOB moved to online models.

Shifting to the cloud

That shift has already happened with the presenter in one breakout session asking the audience how many practitioners used exclusively desktop software, purely cloud service or a hybrid of the two. Of the twenty in the room, the vast majority were using a combination with three being purely online and one sole operator still stuck with a desktop system.

For accountants the message from all of the sessions was clear; the future is online and businesses based around paper based models are doomed. The question though for them is how will they make the transition to being professional advisers.

Strangely, the big challenge for accountants in private practice may be their clients. A number of panel participants pointed out small business owners are slow to adopt new technologies and this holds both them and their service providers back. Divorcing tardy customers may be one of the more difficult tasks facing professional advisors.

The Technology, Accounting and Finance Forum showed the potential for accountants and professional services providers to be the trusted advisors in an online world, the task now is for practitioners and their clients to learn and understand those tools.

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Life at the data frontline

Google’s challenge with managing exponential data growth is something all companies will have to deal with

One of the defining features of the next decade’s successful businesses is how they manage data. No company has a greater challenge in dealing with information than Google.

In a feature tracking Google’s evolving data centres, Techcrunch describes how the company has dealt with the challenge of being the web’s repository.

The challenge has been huge, Google’s current Jupiter network delivers a petabit each second, a hundred times more capacity than its first-generation network and in 2005.

Google boasts 10,000 of their servers are capable of reading all of the scanned data in the Library of Congress in less than a tenth of a second.

While most businesses won’t need that sort of capacity in the near future, the exponential growth Google has dealt with is the same issue facing most managers and business owners as more devices, staff and customers become connected.

For most organisations, dealing with that dramatic growth is almost impossible and this is why automated services running on the cloud will become even more a part of daily working life. Those services will be running on the technology Google is developing today.

 

 

 

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Business and the workforce in an app driven world

As the workforce shifts to being mobile, so too must businesses

One of the things we know about the future is the workplace will be very different. Just as the Personal Computer changed offices in the 1990s, the smartphone and tablet computer are changing today’s.

Part of that change though is being driven by the change in generations. While this blog tries to avoid falling into the trap of generalising about different age cohorts – and contends the entire concept of baby boomers as an economic group is flawed – there are undoubtedly differences between the world of the PC generation of workers and that of the new mobile breed.

The key difference is the idea that work devices are different to those at home. Those of us bought up with the idea that the office computers would be tightly locked workstations – in the 1990s we also had the quaint idea corporate desktops were generally more powerful than what we had at home – are now seeing that way of working being abandoned.

For the next generation of office workers, accessing corporate resources through an app connected to a cloud service will be as normal as opening Windows NT to access the shared corporate drive was 15 years ago.

Along with the technology and generational change driving businesses into the cloud-app computing world there’s also the needs of a much more fluid and mobile workforce. The shift to casualisation began well before PCs arrived on desktops but the process is accelerating as we see crowdsourcing and the ‘uberization’ of industries.

Older workers will adapt as well, many came through the evolution of business computing from ‘green screen’ displays – if their businesses had any at all – through to the server based systems of recent years. For them the shift to smartphones might be troublesome for those with fading eyesight, but it won’t be the first change.

For businesses this shift means they have to start planning for the mobile services that will change workforces and industries. The shift is already well underway – accounting software company Intuit estimates small businesses already use an average of 18 apps to run their business.

We all have to start thinking about how these apps can be used to manage our staff and workforces.

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Engineering for change – the ethics of the new economy

What are the ethical and societal considerations we should consider with today’s technology?

Technologies like the internet of things, cloud computing, 3D printing and big data are changing our industries and society. At the ACI Connect event today, I gave a presentation on some of the opportunities, risks and ethical issues facing technologists and engineers in the connected economy.

While many of the engineering principles underlying these technologies aren’t new, their scale and the power they give businesses and governments means there are serious ethical, security and societal issues we have to consider.

This presentation explores some of those issues and the technologies and trends driving them.

Entering the Data era

A conceit among technologists is that we’re in an unprecedented era of change. This is not true.

The Twentieth Century saw massive restructuring of our society as the telephone, mains electricity, the motor car and television changed our society. Many of today’s settled industries came out of the huge technological steps forward over the last hundred years.

Just as cheap energy – delivered to us through the motor car and mains electricity – defined the Twentieth Century, this century will be defined by easily accessible and abundant information.

Those changes over the last hundred years give us some hint as to where we are going; the shifts that saw coal carters, newspaper sellers and night soil men eventually become extinct, along with a shift from a largely agricultural workforce to industrialised employment, is going to be repeated this century as information becomes abundant.

Harnessing the Internet of bees

Cheap and small sensors mean it’s easier to put a chip on something. In this case we have a CSIRO project tracking bee activity where Tasmanian scientists have put tracking devices on bees.

Those tracking devices would have weighed several hundred grams and cost hundreds of dollars ten years ago but today they are small and cheap enough to fit onto the backs of bees.

Being able to deploy these sensors means we can fit them to things we couldn’t have imagined a few years ago and the data they generate is going to give us insights into patterns and behaviours we couldn’t have contemplated.

However not all of this data is useful or necessary and some may even be damaging to individuals and groups. One ethical question we have to ask ourselves is whether it is in the community’s interests to collect this information.

Another aspect of connecting devices, or even animals and people, to the Internet or a network is it opens the possibility of hacking, as we’ve seen in the recent Jeep case where engineers showed they could control a vehicle remotely. The security and privacy aspects of the IoT are critical and something designers and product engineers can’t overlook.

Decoding the data

It’s often said that Data is the New Oil. In truth it isn’t, data is increasingly cheap and easy to access. Being able to analyse that information is where the power lies.

Data analytics is probably going to be one of the most important fields in an information rich economy and already we’re seeing companies springing up to help farmers estimate crop yields, truck drivers plan their routes and even organisations like the Royal Flying Doctor Service using cloud services to better plan their operations.

Again these services plan a lot but there’s also downsides as inappropriate data matching risks breaching consumers’ privacy and even drawing false conclusions from confusing correlation with causation. A good example of this is Facebook being used to judge credit worthiness.

Removing the human element

Automation – whether it’s through robotics, machine learning or algorithms – will change many industries and the workforces employed by them.

One understated field is management where many white collar supervisor jobs are at risk from business automation. It may be that the executive suites are the next sector to be decimated by computers and robots.

Similarly, many services industry jobs such as taxi drivers and baristas are at risk from robotics while large scale 3D printing of buildings threatens to put many building trades under pressure.

No more truck drivers

Driverless vehicles have a whole range of applications, in logistics were seeing them put forklift drivers out of work while mining companies are rolling out massive dump trucks in their new mines that don’t require $200,000 a year drivers.

One study estimates that half the police workforce in the United States would become redundant as law abiding driverless cars become common.

Similarly electric cars will have a massive impact on government revenues. Currently Australian governments raise $17bn a year from fuel excise and has ramifications for businesses involved in the supply chain for service stations.

Once driverless vehicles become commonplace we may well see them changing industries like daycare, public transport and couriers as it becomes possible to summon an autonomous vehicle, put the kids or the luggage into it and then send it off to its destination. If you’re worried, you can track the progress on an app.

The effects of the driverless car show how we have to think laterally about the effects of new technologies on our businesses, sometimes the effects of a new way of doing things could indirectly hurt our business or create new opportunities.

Squeezing out inefficiencies

One of the great promises for the IoT, Big Data and business automation is to remove inefficiencies from industry. Cisco believe that up to 14% of the Oil and Gas industry’s costs could be stripped away with today’s technologies. That in itself is worth over a 100 billion dollars a year in cost savings.

GE are deploying their technologies into a diverse range of industrial equipment ranging from jet engines to railway locomotives and wind turbines with spectacular results in reducing costs and improving productivity.

The effect of these improvements means less downtime and maintenance costs which are good news for customers and shareholder of these companies, but bad news if you’re a maintenance business. It also means the speed of change in business is accelerating.

Skilling the future workforce

In summary the skills needed today are very different to those of 1915 and 1965 and those of the next fifty years will be even different.

As a society we have to decide what skills we are going to give not our children but those currently still in the workforce who are going to be working longer and later into their lives as the workforce ages.

We also have to consider what sort of ethical compass we have. While the technology we have today is powerful and capable of great things, it’s also capable of great harm. We need to have an understanding of what the effects and limits are of our actions with the Internet of Things, Big Data and analytics.

Ultimately we need to ask what value we as individuals can add to our communities and society.

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Putting machine learning into wine

Two South Australian students are showing how the wine industry can use machine learning and cloud computing

As we gather more data, the opportunities to apply it become wider. A good example of this is Seer Insights, a South Australian company started by pair of university students that calculates the likely grape yields for vineyards.

Seer Insights’ product Grapebrain is made up of two components, a mobile app that the farmer uses to count the grape clusters on the vines and then a cloud service that analyses the data and produces web based reports for the farmers.

The current methods are notoriously unreliable with Seer Insights estimating mistakes cost the Australian viticulture industry $200 million a year as harvests are miscalculated resulting in either rotting fruit or wasted contractor fees.

Born in an elevator

Seer’s founders, Harry Lucas and Liam Ellul, started the business after a chance meeting on their university campus. “We started off doing this after being stuck in a lift together,” remembers Liam. “Originally we were looking at the hyper-spectrum imaging for broadacre farming but when we started looking at the problems we ended up talking to wine organisations about this.”

“The technology predicts how many grapes will be coming off the vineyards at the end of the season to enable people to sort out their finances,” Harry says. “The growth process grapes go through is difficult to model so we use machine learning to do that.”

For both the founders having an off the shelf product, in this case Microsoft’s machine learning tools, to run the data analysis made it relatively easy to launch the product.

As a winner of Microsoft’s Tech eChallenge, the startup has won a trip to the United States as well as being profiled by the company as a machine learning case study.

Over time as these tools become more accessible to small companies we’ll see more businesses accessing machine learning services to enhance their operations.

As companies face the waves of data flowing into their businesses over the next decade, it will be those who manage it well and gather valuable insights from their information that will be the winners.

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Goodbye to the media buyers long lunch

Big data and analytics are changing roles in the media industry, managers in other sectors should worry about the changes.

Yesterday Decoding The New Economy posted an interview with Michael Rubenstein of AppNexus about the world of programmatic advertising and being part of a rapidly growing startup.

The whole concept of programmatic advertising is a good example of a business, and a set of jobs, being disrupted.

Media buying has been a cushy job for a generation of well fed advertising executives. David Sarnoff’s invention of the broadcast media model in the 1930s meant salespeople and brokers were needed to fill the constant supply of advertising spots.

Today the rise of the internet has disrupted the once safe world of broadcast media where incumbents were protected by government licenses and now the long lunching media buyers are finding their own jobs are being displaced by algorithms like those of AppNexus.

A thought worth dwelling on though is that media buyers are part of a wider group of white collar roles being disrupted by technology – the same Big Data algorithms driving AppNexus and other services is also being used to write and select news stories and increasingly we’ll see executive decisions being made by computers.

It’s highly likely the biggest casualties of the current data analytics driven wave won’t be truck drivers, shelf pickers or baristas but managers. The promise of a flat organisation may be coming sooner than many middle managers – and salespeople – think.

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Dealing with the biggest of data

The CERN research project generates huge amounts of data however the human touch is needed to analyse and manage the information

How do you deal with the biggest data sets of all? Bob Jones, a project leader for the European Organization for Nuclear Research – commonly known as CERN – described how the world’s largest particle physics laboratory manages 100 petabytes of data.

The first step is not to collect everything, ““We can’t keep all the data, the key is knowing what to keep” says Jones. This is understandable given the cameras capturing the collisions have 150 million sensors delivering data at 40 million times per second.

Jones was speaking at the ADMA Global Conference’s Advancing Analytics stream where he was describing how the project manages and analyses the vast amounts of data generated by the huge projects.

Adding to Jones’ task and that facing CERN’s boffins is that data has to be preserved and verifiable so scientists can review the results of experiments.

Discovering the Higgs Boson for instance required finding 400 positive results out of 600,000,000,000,000,000 events. This requires massive processing and storage power.

Part of the solution is to have a chain of data centres across the world to carry out both the analytics and data storage supplemented by tape archiving, something that creates other issues..

“Tape is a magnetic medium which means it deteriorates over time.” Jones says, “we have to repack this data every two years.”

Another advantage with a two year refresh is this allows CERN to apply the latest advances in data storage to pack more data into the medium.

CERN itself is funded by its 21 member states – Pakistan is its latest member – which contribute its $1.5 billion annual budget and the organisation provides data and processing power to other multinational projects like the European Space Agency and to private sector partners.

For the private sector, CERNs computing power gives the opportunity to do in depth analytics of large data sets while the unique hardware and software requirements mean the project is a proving ground for high performance equipment.

Despite the high tech, Jones says the real smarts behind CERN and the large Hadron Collider lie in the people. “All of the people analysing the data are trained physicists with detailed, multi year domain knowledge.”

“The reason being is the experiment and the technology changes so quickly, it’s not written down. It’s in the heads of those people.”

In some respects this is comforting for those of us worrying about the machines taking over.

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