Category: Big Data

Retail and the internet of machines

Paypal and eBay are using the Internet of machines to put service station cashiers out of work.

Online retail and payment giants Ebay and PayPal hosted a media lunch in Sydney yesterday to publicise their Australian Business Update.

While eBay dominates the online selling market, PayPal’s position in the payment market place is extremely powerful with Internet monitoring company Comscore reporting in their Digital Wallet Roadmap how PayPal dominates the US market and does likewise in other markets like Australia.

PayPal's US market lead

Their update confirms the trends which have been obvious for some time, particularly in how mobile devices are now driving retail. eBay’s research indicates properly implemented multichannel strategies drives six times more sales than just having an online presence.

What was particularly notable with eBay’s presentation was how the Internet of Machines is changing the retail and logistics industries as smartphones and connected point of sales systems are cutting out jobs and middle men.

Paypal are particularly proud of their US partnership with cash register manufacturer NCR that integrates smartphone payments with the point of sales systems in restaurants, convenience stores and gas stations.

eBay illustrated this with their examples of coupon offers being tied to smartphone payment systems so people paying for gas with their smartphone get a voucher offer for various up sells.

Studies in the US have found a $10 offer can result in sales of up to $100. A pretty compelling deal for most merchants.

With these technologies, we’re seeing how connected machines are changing even the most mundane business tasks.

It may well be that the days of the service station cashier are numbered; it’s quite possible that in one generation we’ll have gone from full staffed gas stations to totally automated facilities.

The example of gas station attendants and cashiers is just one example of how automation is changing many retail and sales tasks. It would be a brave person to say their job isn’t safe.

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Smelling digital garbage

Excel spreadsheets lie at the core of business computing, but what happens when they go wrong?

Excel spreadsheets lie at the core of business computing, but what happens when they go wrong?

James Kwak writing in the Baseline Scenario blog describes how Excel spreadsheets have an important role in the banking industry and their key role in one of the industry’s most embarrassing recent scandals.

In the early days of the personal computer spreadsheets; it was company accountants and bookkeeping clerks who bought the early PCs into offices to help them do their jobs in the late 1980s .

From the accounts department, desktop computers spread through the businesses world and the PC industry took off.

Over time, Microsoft Excel displaced competitors like Excel 1-2-3 and the earliest spreadsheet of all, VisiCalc, and became the industry standard.

With the widespread adoption of Excel and millions of people creating spreadsheets to help do their jobs came a new set of unique business risks.

The weakness with Excel isn’t with the program itself, it’s that the formulas in many spreadsheets aren’t properly tested and often incorrect data is put into the wrong fields.

In his story Kwak cites the JP Morgan spreadsheets that miscalculated the firms Value-At-Risk (VAR) calculations for synthetic derivatives. The result was the London Whale debacle where traders were allowed to take positions – some would call them bets – exposing the bank to huge potential losses.

It turns out that faulty spreadsheets had a key role as traders cut and paste data between various spreadsheets and the formulas that made the calculations had basic errors.

That a bank would have such slapdash procedures is surprising but not shocking, almost every organisation has a similar setup and it gets worse as a project becomes more complex and bigger numbers become involved. The construction industry is particularly bad for this.

Often, a spreadsheet will show out a bunch of numbers which simply aren’t correct. Someone made a mistake entering some data or one of the formulas has an error.

The business risk lies in not picking up those errors, JP Morgan fell for this and probably every business has, thankfully to less disastrous results.

My own personal experience was with a major construction project in Thailand. One sheet of calculations had been missed and the entire budget for lights – not a trivial amount in a 35 storey five star hotel – hadn’t been included in the contractor’s price.

This confirmed in my mind that most competitive construction tenders are won by the contractor who made the most costly errors in calculating their price. Little has convinced me otherwise since.

In the computer industry there’s a saying that “garbage in equals garbage out” which is true. However if the computer program itself is flawed, then good data becomes garbage.

Excel’s real flaw is that it can make impressive looking garbage that appears credible if it isn’t checked and treated with suspicion. The responsibility lies with us to notice the smell when the computer spits out bad figures.

Spreadsheet image courtesy of mmagallan through sxc.hu

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Democratising Big Data

Why a not for profit disrupting Google and the Big Data industry is important for business and society

Common Crawl is a not-for-profit web crawler service that makes the data collected open for all to use. A post on the MIT Technology Review blog speculates how the initiative might spawn the next Google.

One of the problems with Big Data is that it’s held mainly by large corporations and government agencies, both of which have the tendency to keep their data private on that basis that information is power and power means money.

We see this in the business models of Facebook, Google and many of Silicon Valley’s startups; the information garnered about users is as, if not more so, valuable as an utility from the product.

Initiatives like Common Crawl tilt the balance somewhat back towards consumers, citizens, and smaller businesses.

How well Common Crawl and other similar initiatives fare remains to be seen – Wikileaks was a good example of how such projects can flare out, collapse under the weight of egos or be harrassed by corporatist interests.

In search, Google are open to disruption as they tweak their results to suit initiatives like Google Plus. During the company’s earnings call earlier this week Larry Page spoke of the challenges of staying focused on the opportunities that matter, it may well be the company is more distracted from its core business than it should be.

Whether Common Crawl disrupts Google is up to history, it could just as well be a couple of kids called Sergei and Larry with a smart idea.

The imperative now though is to try and keep as much public data available for everyone to use and not lock it away for the privileged few. That will let the future Googles develop while making our societies more fairer and open.

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Tracking the knowledge graph

Facebook Graph search is powerful and dangerous which means we have to be careful about what we like and who we become friends with

“Married Men Who Like Prostitutes” is juicy search term and the results can wreck marriages, careers and lives.

This is one of the Facebook Graph searches UK tech commentator Tom Scott posted on his Actual Searches on Facebook Tumblr site which lists, mercifully anonymised, the results.

What should worry anybody who uses Facebook is that this data has been in the system all along, advertisers for instance have been able to target their marketing based on exactly this information, Graph Search just makes it quicker and easier to access. This is why you should be careful of what you like and who you friend online.

Tom Scott has a terrific Ignite London presentation which looks at just how vulnerable an individual is by over sharing online. In I know what you did five minutes ago, Tom finds an individual, discovers his mother’s maiden name and phone number all within two minutes.

Facebook isn’t the only service we should be careful of, it just happens to be the one we overshare data with the most. When you start stitching together social media services with government and corporate databases then a pretty comprehensive picture can be made of a person’s likes and preferences.

The best we can hope for in such a society is that picture is accurate, fair and doesn’t cast us in too unfavourable a light.

In same cases though that data can be dangerous, if not fatal.

As potential employers, spouses and the media can easily access this information, it might be worthwhile unliking obnoxious, racist and downright stupid stuff. There’s a very good chance you’ll be asked about them.

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Customer lock in as a business asset

Barnes and Noble’s problems show how high the stakes are when locking customers into an online business.

US booksellers Barnes and Noble has been struggling for years and things aren’t getting better reports the New York Times.

An important part of the New York Times story is the quote from a Forrester industry analyst,

“The problem is not whether or not the Nook is good,” said James L. McQuivey, a media analyst for Forrester Research. “What matters is whether you are locked into a Kindle library or an iTunes library or a Nook library. In the end, who holds the content that you value?”

Locking in customers lies at the heart of the Kindle and iTunes business model. Once users have a substantial investment in their book or music collections on one platform it’s unlikely they will go elsewhere as the costs, and risks, of moving are too great.

This doesn’t always end well for the customer and it gives online businesses great power which they often misuse.

Every online business tries to lock their customers into their ecosystem – Google, Amazon, Facebook and Apple are the most successful but every single social media and cloud service tries to make it hard for users take their business elsewhere.

In some respects this is no different to the phone company or bank which have historically tried to lock customers into their services, but the online social media, cloud computing and e-commerce platforms make a much more ambitious grab for their users’ data and assets like music and book collections.

The New York Times article illustrates just how critical that user lock in is to the success of online businesses. The question for us as consumers is how much we want to be locked inside the web’s walled gardens.

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Big data, mobile apps and smarter logistics – why Avis is buying Zipcar

Smartphone apps are more than just a funky way of getting information. The combination of big data, social media and mobile insights offer businesses deep market intelligence.

With no bad press over New Year’s Eve it looks like hire car service Uber avoided the surge pricing traps of 2011 and the good news continues for the online booking industry with the news that Avis is buying car sharing service Zipcar.

Assuming the acquisition isn’t another example of the greater fool investment model, Avis’ purchase of Zipcar makes good sense in expanding the hire car giant’s footprint into the share car business.

Regrettably Avis use the 1980s term “synergies” four times in their media release but it does seem the businesses are a good fit both in fleet sharing and improving both company’s services.

Zipcar’s technology is another asset which Avis can use,  with the car sharing service’s ability to track vehicle locations meaning better fleet management for the hire car business.

Car sharing logistics

The logistics angle of car share services is something that’s been highlighted by Uber’s CEO Travis Kalanick at various times, most recently at the service’s Sydney launch last November.

Another aspect of the car sharing and hire car booking services is their Big Data advantages which the online startups bring.

Historically, car hire companies have been reasonably good at gathering data on their customers with loyalty schemes, direct mailing and plugging into airline frequent flier programs. However they have been left behind by the Big Data boom in recent years.

Companies like Zipcar, Uber and taxi hailing apps like GoCatch have big data in their DNA, having been founded in the era of cloud computing and social media they have access to more information and a better ability to use the knowledge they gather.

Predicting the price surges

At Uber’s Sydney launch Kalanick described how Uber’s traffic volumes increase in San Francisco when the Giants win a game, the interesting thing is that the surge happens three hours before the match starts.

Insights like the traffic patterns around football games and holidays are gold to a high inventory business like hire car services. They are also important to the entire logistics industry.

This latter point is probably the most overlooked part of all with the current rush into social and mobile based apps – the market intelligence that these services gather.

While it’s tempting to dismiss that market intelligence as just monitoring who likes cats or cheeseburgers, the application of that data is transforming supermarkets, airlines and even concert venues.

Avis seem to have understood that it will be fascinating to see how they will use Zipcar’s data and whether their competitors will figure out the importance of what these services offer.

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Fiddling the prices

Has the Internet’s promise of transparency failed as online retailers vary prices.

Discriminatory pricing is nothing new, a good salesperson or market stallholder can quickly sum up a punter’s ability or willingness to pay and offer the price which will get a sale.

Anybody who’s travelled in countries like Thailand or China is used to Gwailos and Farang prices being substantially higher even for official charges like entrance fees to national parks and museums.

The Internet takes the opportunity for discriminatory pricing even further arming online stores armed with a huge amount of customer information which allows them to set prices according to what the algorithm thinks will be the best deal for the seller.

Recently researchers found that the Orbitz website would offer cheaper deals for people searching for fares on mobile phones and prices would vary depending of which brand of smartphone people would use.

Writers for the Wall Street Journal did an experiment with buying staplers and found the same thing.

Interestingly, one of the factors Staples’ seems to take into account is the distance customers live from a competitors’s store – the closer you live to the competition, the lower the price offered.

There’s also other factors at play; sometimes you don’t want a customer, or you don’t want to sell a particular product and it’s easy to guess the formulas used by Staples and other big retailers do the same thing.

One of the great promises of the internet was that customers’ access to information would usher in a new era of transparency. In this case it seems the opposite is happening.

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