big data | Paul Wallbank - Communications Professional

Tomorrow Starts Here

Managing big data is one of the future skills of business.

Today was the main day of the Melbourne Cisco Live Conference; the company’s annual Australian event.

Much of the talk was around the Internet of Everything — which will be the basis of subsequent posts — with a constant theme around the explosion of data.

A favourite statistic was that of Cisco’s Executive Vice President who pointed out that US Department store Walmart collects 2.5 Petabytes of customers data every hour.

The reason for this was pointed out by GE’s Australia and New Zealand CIO, Mark Sheppard, who pointed out that twenty years ago jet engines had few sensors while today they have hundreds, a point also made by Team Lotus’ Engineering Director Nick Chester to Networked Globe.

Chester observes that when he started in Formula One racing two decades ago, there were four or five sensors on a racing car; today Lotus’ vehicles have over two hundred.

All of these sensors are creating massive amounts of data and the big challenge for businesses is to manage all of this information, something we’ll be exploring over the next few weeks.

Eliminating the donkey work

Ross Mason, founder of Mulesoft, sees Big Data as one of the challenges facing business

Mulesoft founder and CTO Ross Mason worries about how companies are going to manage the data generated by the Internet of Things.

“I don’t think we’re ready for the amount of data that these devices are designed to build up,” Ross observes in the latest Decoding the New Economy video.

Ross’ aim in founding Mulesoft was to eliminate the donkey work in connecting IT systems and he sees the data moving between enterprise applications being a challenge for organisations

“We have energy companies that have connected their smart grid systems to their back end systems and most of them delete almost all the data because of the cost of storing that much data without doing anything with it.”

“Big data is still in the realm of we’re figuring out the questions to ask.” Ross states, in echoing the views expressed by Tableau Software founder Pat Hanrahan a few weeks ago.

“There’s a little bit of hype around big data right now, but it’s a very real trend;” Hanrahan said. “Just look at the increase in the amount of data that’s been going up exponentially and that’s just the natural result of technology; we have more sensors, we collect more data, we have faster computer and bigger disks.”

The interview with Ross covers his journey from setting up Mulesoft to the future of big data and software. It was recorded a few days before the company announced a major capital raising.

Mulesoft’s elimination of software ‘donkey work’ is another example of how the IT industry is changing as much of the inefficiencies are being worked out of the way developers and programmers work.

In many ways, Ross Mason’s story illustrates how the software industry itself is being disrupted as much as any other sector.

The Internet of Racing Machines

Formula One racing gives us a glimpse of the technologies that will be commonplace in businesses in the near future.

For the Formula One racing circuit, the financial crisis of six years ago was an opportunity to reinvent the sport; today the teams use a combination of technologies to gain an advantage over their competitors.

“A few years ago you wouldn’t have been here today,” Francois Puentes, Head Of Account Management at Team Lotus told a group of journalists ahead of this week’s Melbourne Grand Prix. “F1 was a completely different sport.”

The 2009 financial crisis was the catalyst for the changes Puentes says; “we all sat down as teams at the same table to make the sport more sustainable, this obliged us to run the sport as a business.”

“Before we didn’t know what the unit cost was for a part. We would very often produce two of the same parts without even knowing what was going on.”

To tighten their management systems, Lotus bought in a range of cloud based business software such as Microsoft Dynamics and also accelerated its adoption of computerised manufacturing techniques.

Speeding up development

Lotus employs over 500 people to keep its two cars on the road and most of the vehicles parts are designed and manufactured at its headquarters in Oxford, England. During the season the team’s workshop may produce up to five hundred replacement or redesigned components each week.

This brings together a number of technologies including Computer Aided Design, 3D Printing and cloud computing.

The internet of racing machines

Massive rule changes have also accelerated Formula One’s adoption of in car technology with information being gathered from sensors throughout the vehicles.

During races data is transferred from the vehicles’ sensors by radio for the teams’ crews to analyse performance. This includes information like gear box temperature, tyre condition, and aerodynamic performance data.

Following the race larger volumes of data are downloaded from the vehicle for engineers to tune the car for the next event.

While Lotus has teamed with technology companies like Microsoft and EMC, rival team Caterham partnered with GE whose Global Research team worked to integrate the technologies demanded by the new F1 rules.

Global technology

Caterham’s cars use intercoolers developed in Germany, carbon fibre composites and fibre optic sensors from the United States, and big data analysis techniques developed in India.

Key to gathering that data are sensors throughout the vehicle that capture a constant stream of data about forces acting on the car during the race, transmitting this information in a far more efficient way than traditional methods which relied on load sensors attached to the suspension.

The result is massive volumes of raw data. On the track, Caterham cars generate 1,000 points of data a second from more than 2,000 data channels. Up to 500 different sensors constantly capture and relay data back to the team’s command centre for urgent analysis.

Learning from Big Data

By applying what the company has learned from its Industrial Internet projects, GE was able to help Caterham cut its data processing time in half, leaving the team in a stronger strategic and tactical position.

Thanks to these analysis techniques, the Caterham team can look at slices of its data across an entire season, pinpoint setups that were particularly effective, and identify reliability issues earlier.

Inside the vehicle, GE has also found a way to replace metal pipes with carbon fibre, reducing the overall weight of the vehicle.

These technology developments will continue to find applications beyond the 2014 Grand Prix season.

Carbon composites are being used extensively in the aviation industry and big data analysis is playing an important role in the renewable energy sector.

Lewis Butler, Caterham’s chief designer, says working with GE is helping the team deepen its skills base.

“GE are working with Caterham to help with the manufacturing process and knowledge transfer, and giving Caterham F1 Team the capability to manufacture its own parts,” he says.

All the Formula One teams are using Internet of Things technologies to gather information on their vehicles, Big Data tools to manage that information along 3D printing to accelerate their research and manufacturing processes.

The Formula One world is a glimpse into the future of business as various technologies come together to change the way industries operate.

Paul travelled to the Melbourne Grand Prix as a guest of Microsoft and Team Lotus.

Accountability and security

Experian’s massive data breach shows why we, and our governments, have to start taking security seriously.

Security writer Brian Krebs has followed up last year’s story that US credit reporting agency Experian had been selling personal data to Singaporean based identity thieves with the guilty plea from the scheme’s architect.

Krebs points out that the leader of the identity thieves, Vietnamese national Hieu Minh Ngo, could access up to 200 million consumers’ records.

It’s almost impossible to say how much theft, fraud and misery was inflicted on innocent Americans who had their personal details misused by Ngo’s customers.

The amazing thing is it appears that Experian’s executives or shareholders will not suffer any sort of penalty – civil or criminal.

In an age where companies are collecting masses of data on everyone, it’s inconceivable that those trusted to store and protect that information – particularly credit reporting agencies – seem beyond any accountability for failing in their core responsibilities.

There’s also the aspect of undermining the US credit system; if merchants and consumers find they can’t trust credit reporting agencies, then offering or getting credit becomes far more difficult and risky.

Until the management of companies like Experian are held accountable for their incompetence, any talk of safeguarding privacy is empty. It’s why we should treat claims that our data is held safely by government agencies or businesses with a great deal of caution.

“He looks like a geek”

The media scrum around alleged Bitcoin founder Dorian Nakamoto is based on some flimsy thinking

The unseemly media scrum around alleged Bitcoin inventor Dorian Nakamoto has not been the press’ finest hour.

What’s more worrying though is a Business Insider interview with Sharon Sargent a ‘forensics analyst’ who was part of the Newsweek investigative team.

A systems engineer by training with experience in computing security, military protocol analysis, and artificial intelligence, Sergeant said everything she found converged on an individual with a background apparently similar to hers — and who ended up sharing a name with Bitcoin’s creator.

“I said, ‘I think I know this guy — he wears a pocket protector, he has a slide rule, he comes from that genre,’ which was very different from other characterizations,” she told BI by phone Friday.

He wears a pocket protector and uses a slide rule? Hell yeah, not only did he create Bitcoin but he’s probably a witch as well.

One hopes Newsweek have found the right man.

Picture courtesy of forwardcom through sxc.hu

Customer service is no longer a department

Customer service needs to pervasive through modern organisations says Salesforce’s Alex Bard

When it comes to customer service businesses, Alex Bard calls himself a ‘career entrepreneur’, having founded four startups in the field since the mid 1990s.

In 2011 he sold his most recent business, Assist.ly, to Salesforce and became the company’s Vice President for Service Cloud and the Desk.com customer service offerings.

Bard tolds Decoding the New Economy last week how social media and Big Data are radically changing how organisations respond to the needs of their clients.

“I’ve been in the industry for twenty years and I’ve never been excited as I am now,” Bard says. “The real transformational things that’s happening now are these revolutions – the social revolution, the mobile revolution, the connected revolution.”

The philosophy of customer service

“What they’re really driving is this idea that customer service is no longer a department, it’s a philosophy.”

“It’s a philosophy that has to permeate throughout the organisation. Everybody in the company has a role in support. It’s not just about a call centre or a contact centre or even an engagement center which is what these things are called today.”

“I really don’t like the word ‘centre’ because I really fundamentally believe that everbody in that company has to interact with customers, has to engage and has to the information – no matter they are – about that customer to provide context.”

Abolishing the service visit

With the Internet of Things, Bard sees GE’s social media connected jet engine as illustrating the future of customer service where smart machines improve customer service.

“They’re going to capture more data in one year than in their entire 96 year history prior,” says Bard. “With that data they’ll be able to analyse and do things on behalf of that product or service that’ll reduce the number of issues.”

“Because the best service of all is one that doesn’t have to happen.”

In this respect, Bard is endorsing the views of his college Peter Coffee who told Decoding the New Economy last year that the internet of machines may well abolish the service visit.

“Connecting devices is an extraordinary thing,” says Coffee. “It takes things that we used to think we understood and turns them inside out.”

“If you are working with connected products you can identify behaviours across the entire population of those products long before they become gross enough to bother the customer.”

For Alex Bard, the customer service evolution has followed his own entrepreneurial career having evolved from being personal computer based in the 1990s to today’s industry that relies on cloud computing, big data and social media technologies.

As these technologies roll out across industry, businesses who adopt the customer service philosophy Bard describes are much more likely to adapt to the disruptions we’re seeing across the economy. Changing corporate cultures is one of the great tasks ahead for modern executives.

Learning to ask the right questions

What a three time Oscar winner can tell us about managing the data generated from the Internet of Machines

How do we make sense of the masses of data entering our businesses? Tableau Software founder – and multiple Academy Award winner – Pat Hanrahan thinks he has the answer.

A major challenge presented by the Internet of Things is in understanding the data that’s generated by devices, data visualisation companies like Tableau Software are making easier to interpret what machines are telling us.

“The streaming data coming from sensors is a very interesting opportunity,” Tableau co-founder Pat Hanrahan told Network Globe when discussing machine to machine technologies, “there’s so much potential.”

A Stanford Professor and winner of three academy awards for Computer Generated Imagery, Hanrahan founded Tableau with Christian Chabot and Chris Stolte in 2003 with a mission to help people to understand data. Today the company employs a hundred people after going public last year.

The origins of Tableau came from Hanrahan tiring of the movie industry which he’d been part of since joining Pixar on graduating in 1987, “I was thinking could we use computer graphics for other things, I want to find something more work related so I got interested in data visualisation.”

Hanrahan teamed with Stolte, who was one of his students, to set up a company called Polaris that became the basis of Tableau; “it was a classic Stanford start-up, Google was literally right next to us. I remember when the company started, Larry Page came to our office party.”

Making data accessible

“I’ve always been fascinated with taking the high end stuff and making it more accessible” says Hanrahan. “We’re in a transition phase, where we’re tying to figure out how to make it more accessible.”

Helping those who are passionate about facts and reasons is one of Tableau’s missions,”we have fanatical customers,” says Hanrahan.

“If you’re one of the rare people who use facts and reasons to solve the world’s problems then you are persecuted, you are on a mission, you’re going to convince those crazies that you’re right and you’re wrong and that’s why they’re so fanatical about our product.”

“There’s a little bit of hype around big data right now, but it’s a very real trend;” states Hanrahan. “Just look at the increase in the amount of data that’s been going up exponentially and that’s just the natural result of technology; we have more sensors, we collect more data, we have faster computer and bigger disks.”

A good example of the exponential growth in computing power is in how the smartphone has developed, citing how far computers have come since 1997 when IBM’s Deep Blue computer beat Kasparov, “at the time both Kasparov and the computer were rated 2700, the best chess programs now are rated 3800.”

“The chess program running on my iPhone is rated above 3000,” observes Hanrahan.

Despite the leaps in power, Hanrahan doesn’t see algorithms completely replacing the human touch, “you have the technology and resources to do this but you still need someone to figure out how to make it accessible.”

One of the keys to understanding information is to be literate in using it, “every student should be efficient in using data,” Hanrahan says and he sees data analysis skills as being essential in the future workforce; “we have to know how to ask the right questions.”

Making the data generated by connected machines accessible to the public, workers and managers is going to be one of the big challenges for organisations over the next decades; it’s an area where companies like Tableau are going to do well.

Seeing the full picture

Data visualisation service Encompass is an example of finding a business opportunity from a scarring experience.

Being able to make sense of data is one of the challenges of modern business.

In the case of data visualization service Encompass, the business was founded after its founders were caught out by not knowing all the information behind business deal.

The latest Decoding The New Economy video is an interview with Roger Carson and Wayne Johnson, the co-founders of Encompass, a cloud based data visualisation company.

Encompass takes corporate information such as credit information and business registration details and renders it into a form that’s easy to read for salespeople, bankers or anyone doing due diligence on an organisation or individual.

“A lot of it is about bringing the information together and making it usuable and simple to use,” says Wayne. “If you can’t get that information easily and it takes relationships with lawyers to put it all together or your own legal advisor takes a long time to get this together, it’s costly and you may miss things.

Wayne and Roger’s path to starting Encompass came from being caught out in a property deal where it turned out some of the business partners wouldn’t have passed close examination.

“The property venture we went into was not a success,” Roger explains. “If we had known about the people and the properties and the companies involved on the other side of that transaction we probably would not have got involved in it.

“The genesis of this product really came about because we were involved in a transaction where we didn’t have the full picture, we couldn’t get the full information quickly and we therefore realised there had to be a better way for people to look at commercial transactions and get the full picture.”

It’s often said that information is power, but the real power lies in being able to understand the data we’re being flooded with. Encompass are a good example of the new breed of business that’s helping others deal with the masses of information we’re all being inundated with.

Uber and the evolving business model

Where does the future lie for car hire service Uber?

Last year we looked at Uber and speculated the software that runs the business positions the company to be more than just a hire car booking service with applications in logistics and other sectors.

This week Uber’s CEO Travis Kalanick is getting plenty of coverage in the media with extensive profiles in both the Wall Street Journal and Wired.

Wired’s profile of Kalanick and Google raises Uber’s potential in logistics, funded by a $258 million fund raising led by Google Ventures last August.

“We feel like we’re still realizing what the potential is,” he says. “We don’t know yet where that stops.”

While Wired speculates about how Uber would perform against Amazon and Walmart, the car service is different in being more of a big data play than its established, possible competitors.

The three businesses would be very different creatures in the way they would address consumer markets, it may even be that Uber is more suited to being a B2B or wholesale operation rather than a retailer like Walmart.

Interestingly Kalanick looks at a target of 2,000 staff by the end of this year reports in his Wall Street Journal interview.

Mr. Kalanick: We have 550 employees. That’s approximate. We’re definitely going to be well over 1,000, maybe in the 1,500 to 2,000 range [by the end of 2014].

Having a staff target so high is interesting, it certainly indicates Kalanick sees plenty of growth ahead in the business.

Connecting the vending machine

Vending machines are leading the way in adoption of the internet of machines

Wired Magazine’s Klint Finlay speculates why Coca-Cole would want sixteen million MAC address for their vending machines.

That Coca-Cola has connected all their vending machines shouldn’t come as a surprise, probably the only thing moderately unusual from this story is that the soft drink company organises its own hardware rather than getting the machine manufacturers to do it.

Vending machines being connected isn’t new, back in the days of dial up modems some of the more advanced one would use phone lines for basic diagnostics.

Today most vending machines have a cellular connection used for payments, stock monitoring, fault warnings and vandalism detection.

A visit to my local swimming pool today showed this, the Coca-Cola branded machine machine outside the change rooms offers credit payments and in the not too distant future will probably include some sort of NFC type option.

On top of the the machine is a little aerial for the back to base communications. So the device can validate and bill cards, report back when stock levels are low and alert operators to anything untowards happening.

A big opportunity for the soft drink companies and their distributors is analysing the information about buying patterns at various locations — it’s a classic Big Data play.

So it’s not surprising Coca-Cola has registered a block of MAC addresses as the company will probably need several more 16 million blocks in the not too distant future as more of their operations from bottling plants to vending machines require unique connections.

Vending machines are a small but obvious example of how the internet of things is evolving, in the near future most consumer devices will have similar options.

King Canute and Google: When the algorithm is wrong

As society and business drown in big data we’re relying on algorithms and computer programs to helps us wade through the masses of information, could that be a weakness?

As society and business drown in big data we’re relying on algorithms and computer programs to helps us wade through a flood of information, could that reliance be a weakness?

British Archeology site Digital Digging discusses how Google displays Manchester United winger Ryan Giggs in the results search for Cnut, the ancient king of Denmark better known in the English speaking world as King Canute.

Apparently Giggs appears in the search results for Canute because of the footballer’s futile attempt to hold back a tide of information about his love life.

While Google’s algorithm seems to have made a mistake, it’s only doing what it’s been programmed to do. A lot of trusted websites have used the term ‘Canute’ or ‘Cnut’ in relation to Giggs so the machine presents his picture as being relevant to the search.

Confusing Ryan Giggs and King Canute is mildly amusing until we consider how critical algorithms like Google Search have become to decision making, there are no shortage of stories about people being wrongly billed, detained or even gaoled on the basis of bad information from computers.

The stakes in making mistakes based on bad information are being raised all the time as processes become more automated, a chilling technology roadmap for the US military in Vice Magazine describes the future of ‘autonomous warfare’.

By the end 2021, just eight years away, the Pentagon sees “autonomous missions worldwide” as being one of their objectives.

Autonomous missions means local commanders and drones being able to make decisions to kill people or attack communities based on the what their computers tell them. The consequences of a bad result from a computer algorithm suddenly become very stark indeed.

While most decisions based on algorithms may not have the life or death consequences that a computer ordered drone strike on a family picnic might have, mistakes could cost businesses money and individuals much inconvenience.

So it’s worthwhile considering how we build the cultural and technological checks and balances into how we use big data and the algorithms necessary to analyze it so that we minimise mistakes.

Contrary to legend, King Canute didn’t try to order the tide not to come in. He was trying to demonstrate to obsequious court that he was fallible and a subject to the laws of nature and god as any other man.

Like the court of King Canute, we should be aware of the foibles and weaknesses of the technologies that increasingly guides us. The computer isn’t always right.

Big Data, retail and the 80/20 rule

Retailers are using big data to apply the 80/20 rule – or Pareto’s Law – to reduce returns and shrinkage

Sorting out troublesome customers is one of the major benefits that big data offers businesses, a profitable example lies in reducing returns to online stores.

One of the banes of online retail is dealing with returns, the industry pioneers overcame objections to shopping over the web through no-questions-asked returns policies that’s trained customers into expecting they can send items back regardless of the reason.

The Frankfurt School of Finance and Management’s Christian Schulze surveyed nearly six million internet transactions and found returns are effectively costing online retailers half their profits, as The Economist reports.

Leaving that sort of money on the table is painful for any business and online retailers are trying to find ways to reduce those return costs by sacking their customers;

But this risks a backlash: rejected shoppers are likely to rush to the newspapers or social media to complain—and their gripes may turn other, more profitable customers against the firm.

Much of this comes down to Pareto’s Law, that 80% of your problems will come from just 20% of customers, and a key imperative in business is to get the troublesome, high maintenance customers buying from your competitors without being too obvious.

Identifying those troublesome customers is where Big Data comes into play, coupled with intelligent analytic tools businesses are able to identify who is more likely to return a product or dispute a bill before the sale is made.

As the Wall Street Journal reports many online retailers are exploring ways they can reduce the return rates using Big Data and analytics.

By giving buyers access to their purchasing history stores are able to suggest when a customer is buying something that isn’t appropriate or the wrong size.

The WSJ cites fashion retailer Rue La La, which lost $5 million in returns last year, as an example.

For instance, a customer who has continuously bought the same brand of dress shirts in both a small and a medium might see a note pop up saying: “Are you sure you want to order the small? The last five times you ordered both sizes, you only kept the medium,” Chief Executive Steve Davis said.

Another tactic for retailers is to discourage frequent returners from buying high margin goods through targeted vouchers and offers. One point the WSJ article makes is how differential pricing is going to be applied – if you regularly return goods then expect not to be offered the best discounts when you visit the retailer’s website.

Many returns though are the result of genuinely dissatisfied clients and this is where improving customer service kicks in, the WSJ describes how some retailers are now providing video tutorials for their products and increasingly smarter customer service can be used to avoid returns.

With the increased sophistication of customer analytics and support tools, we’ll see online retailers squeeze more profit out of their businesses as well as look after their most profitable clients.

The problem for ‘bricks and mortar’ retailers not deploying new technologies is they won’t have the tools to compete with their savvier online rivals.

A good example of legacy managers struggling in the face of chronic under investment are Australian retailers and this week the Myer department store chain had to shut down its online outlet after the system collapsed.

There is no timeline on when Myer’s website will be back up. It’s a tough time for those retailers that haven’t invested in modern system and an even tougher time for companies with legacy managers like those at Myers.

The use of big data in analysing shopping behaviours is one area where well managed retailers will out perform their poorer rivals, it’s hard to see how companies like Myer will survive in the modern era of business.